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Mobile apps have become indispensable in our daily lives, serving as tools for everything from communication to entertainment. However, many apps come with a frustrating downside: battery drain. Users quickly uninstall apps that consume excessive power, making battery performance a top priority for developers and QA teams. In this blog, we’ll explore the importance of battery drain testing, effective methods for testing battery consumption, and how platforms like Pcloudy can streamline the process.
Battery life is one of the most critical factors influencing the user experience and overall app retention. In a world where smartphones act as a lifeline for everything—from communication and entertainment to navigation and health tracking—users expect their devices to last longer on a single charge. If an app is consuming excessive battery, users are quick to uninstall it and move to a competitor.
The need for battery testing goes beyond just preventing app uninstalls. It also impacts brand perception, user engagement, and overall app performance. Here’s an in-depth look at why battery testing is essential for mobile apps:
Mobile users are highly sensitive to resource-heavy apps. A poorly optimized app that drains the battery will likely result in negative app reviews, reduced ratings, and eventual uninstalls. Studies indicate that users uninstall apps that:
Why it matters:
A single negative review highlighting excessive battery usage can deter hundreds of potential users. On the other hand, optimizing battery usage improves user satisfaction and encourages positive feedback.
Battery drain is often associated with excessive CPU and memory usage caused by inefficient processes, such as:
By testing for battery consumption, developers can identify and resolve these inefficiencies, leading to a more responsive and lightweight app.
When apps are optimized for resource consumption, they perform smoother, load faster, and are less prone to crashes—leading to a better user experience.
Apps that are known to consume minimal battery build trust among users. A reputation for delivering resource-efficient apps can significantly enhance a brand’s credibility and increase user loyalty.
Users are more likely to recommend apps that don’t compromise their device’s performance. Conversely, an app infamous for draining the battery can tarnish the brand’s reputation.
There are thousands of different smartphone models with varying hardware capabilities, operating systems, and power optimizations. An app that performs well on a flagship device might behave differently on mid-range or budget devices.
Battery testing ensures that the app behaves consistently across different devices, regardless of hardware limitations. Testing across multiple devices prevents issues that could disproportionately affect certain user segments.
Apps often interact with device components such as GPS, Bluetooth, cameras, and sensors. These components are major contributors to battery consumption, especially when used inefficiently.
By conducting battery tests, developers can identify areas where the app uses hardware unnecessarily (e.g., keeping GPS active even when not needed) and implement optimizations to reduce energy consumption.
With the rise of wearable technology, IoT devices, and connected ecosystems, mobile apps often communicate with external devices. These integrations can place additional demands on battery life.
Battery testing ensures that apps remain power-efficient when interacting with wearables (e.g., smartwatches), Bluetooth devices, or smart home systems. This is crucial for providing a seamless, long-lasting user experience.
Both Google Play and the Apple App Store emphasize app performance, including battery efficiency. Apps that are flagged for excessive resource consumption may face penalties, such as removal from the app store or poor visibility.
By proactively testing and optimizing battery usage, developers can ensure their apps comply with app store guidelines, maintaining app visibility and discoverability.
For enterprise apps used by field teams, healthcare workers, or logistics personnel, battery consumption can directly impact productivity. If the app consumes too much power, it can limit the user’s ability to work efficiently throughout the day.
Efficient battery usage in enterprise apps ensures that workers can rely on their mobile devices for an entire workday without constant recharging, improving operational efficiency.
Apps with optimized power consumption are more likely to remain installed and used regularly. Battery efficiency can directly impact how frequently users interact with an app and whether they keep it installed.
By addressing battery drain issues early in the development process, developers can create apps that users engage with more frequently, leading to higher retention rates.
As technology advances, consumers have grown more aware of resource consumption and expect their favorite apps to be optimized for performance and battery life.
Regular battery testing ensures that your app keeps pace with user expectations, building trust and maintaining competitiveness in the app marketplace.
Battery consumption can vary significantly depending on how the app is used. Here are some key scenarios to consider during testing:
Testing battery consumption requires both a systematic approach and the right tools. Below are steps to measure battery usage effectively:
1. Battery Test Flow
2. Testing from a User Perspective
Real-world conditions significantly impact battery performance. Test under:
3. Using Real Devices
Android’s OS fragmentation across OEMs makes it crucial to test on multiple real devices. Device labs or cloud-based platforms, such as Pcloudy, can help simulate these environments efficiently.
Tools for Battery Testing
Several tools can assist in monitoring and analyzing battery consumption:
1. Android Studio Profiler
A built-in tool for real-time monitoring of CPU, memory, and battery usage.
2. Battery Historian
This tool provides detailed insights into battery consumption patterns, highlighting resource-heavy processes.
3. Third-Party Tools
Pcloudy offers a comprehensive platform for battery consumption testing on real devices. Here’s how it helps:
Battery drain testing is no longer optional; it’s a vital step in delivering apps that users trust and love. By focusing on optimizing battery consumption, developers can enhance user satisfaction, retention, and brand loyalty. Tools like Pcloudy make it easier to test across diverse devices, ensuring your app meets user expectations and marketplace standards.
Ready to optimize your app’s battery performance? Discover how Pcloudy can help you deliver power-efficient apps.
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In today’s fast-paced development landscape, quality assurance is no longer the sole responsibility of QA teams. Developers and testers are increasingly working together as part of a DevOps-first approach, ensuring that quality is embedded throughout the development lifecycle. Nowhere is this collaboration more critical than in mobile app testing, where continuous iterations demand faster feedback and efficient testing strategies.
To keep pace with this, developers need tools that provide real-time testing capabilities on real devices. This is where cloud-based solutions bridge the gap between development and quality, empowering teams to test and debug seamlessly.
In the world of DevOps, where speed and agility define success, continuous testing is a crucial pillar. App testing in DevOps goes beyond finding bugs; it plays an integral role in ensuring seamless collaboration, faster releases, and enhanced product quality. Here’s an in-depth look at why app testing is indispensable in DevOps.
In DevOps, the objective is to deliver high-quality software quickly and continuously. Testing provides instant feedback on the quality of the code after every change, helping developers address issues early. This prevents defects from compounding and becoming costlier to fix later.
Key Benefits:
Continuous testing forms the backbone of CI/CD pipelines, ensuring that automated tests are executed with every build. This practice ensures that each integration of new code doesn’t break existing functionality.
DevOps encourages a shift-left testing approach where testing is conducted early in the development lifecycle. Additionally, shift-right testing focuses on post-deployment monitoring to gather user feedback and ensure stability in production.
App testing in DevOps accelerates the release cycles by automating repetitive test cases and integrating them into the CI/CD process. Automated tests enable teams to quickly validate code changes and release builds faster.
DevOps fosters a culture of collaboration between development, QA, and operations teams. Automated test reports and dashboards improve visibility, ensuring that all stakeholders are aware of the application’s health.
Manual testing is often limited by time and resources, while automated testing within a DevOps framework ensures comprehensive test coverage. This includes functional, performance, security, and compatibility tests.
One of the goals of DevOps is to minimize post-release issues. Automated testing detects vulnerabilities and inconsistencies in pre-production stages, reducing the risk of defects in live environments.
For mobile app testing, DevOps workflows require testing across different devices, operating systems, and screen sizes. Cloud-based testing platforms ensure that teams can scale their testing efforts without maintaining physical device labs.
In a DevOps environment, testing isn’t limited to functional validation. Performance and load testing are essential to ensure that the application can handle real-world usage patterns and peak traffic.
DevOps is centered around the concept of continuous improvement, and testing plays a key role in gathering insights for refinement. Test results, post-deployment feedback, and analytics help teams fine-tune their processes.
Without continuous testing, DevOps practices cannot achieve their full potential. Here’s why app testing is a critical component in DevOps:
By incorporating robust testing tools and strategies, teams can automate mundane tasks, improve coverage, and release high-quality software faster. Platforms like Pcloudy empower teams by providing cloud-based device access, real-time debugging, and seamless integration with CI/CD pipelines.
Despite advancements in DevOps, mobile app developers continue to face unique challenges when testing apps:
Developers need to test their apps on different device models, screen sizes, and operating system versions to ensure compatibility and performance. However, maintaining an in-house library of physical devices is expensive and difficult to manage due to:
This results in insufficient device coverage, leading to undetected bugs in production when users with different device configurations encounter issues.
2. Need for Robust Debugging Capabilities on Real Devices
Even when organizations provide device clouds, developers often lack the level of control they need for comprehensive debugging. Many platforms only allow basic interactions, such as installing and uninstalling apps, without:
Without robust debugging, identifying the root cause of complex issues becomes time-consuming, impacting development speed and overall productivity.
When an issue is reported in production, developers need access to the exact device model and OS version where the bug occurred. Unfortunately, this is not always feasible due to:
In such cases, developers often resort to inefficient workarounds or face delays in issue resolution, which can affect customer experience and app ratings.
In many workspaces, developers juggle multiple mobile devices connected to their computers via USB cables. This setup often leads to:
These inefficiencies slow down development cycles and create unnecessary frustration, especially when working on apps with frequent updates and tight release timelines.
To address the challenge of device access, many organizations have adopted device clouds that provide remote access to a library of real devices hosted in data centers. These platforms allow developers and testers to:
However, most device clouds are designed primarily for QA teams and automated testing, offering limited support for hands-on debugging by developers. Key limitations include:
Due to these gaps, developers often still rely on physical devices, undermining the benefits of cloud-based solutions.
Pcloudy’s DeviceTunnel bridges the gap between device clouds and developer needs by enabling complete control of cloud-hosted devices directly from the developer’s local environment.
How DeviceTunnel Works
Once connected, developers can perform a wide range of actions to debug and test their apps:
For a step-by-step guide on connecting to cloud devices using DeviceTunnel, click here.
DeviceTunnel transforms cloud-based mobile app testing by providing developers with real-time, hands-on access to cloud-hosted devices.
a. No need to maintain an in-house library of physical devices. b. Reduces clutter and time spent managing physical connections.
2. Real-Time Debugging a. Debug apps on real devices as if they were connected locally. b. Identify and resolve issues faster with direct ADB access and advanced debugging features.
3. Seamless Integration with IDEs
a.Works seamlessly with Android Studio, Eclipse, and command-line tools.
b. Enables uninterrupted workflows for faster development cycles.
4.Improves Collaboration Across Teams
a. QA and development teams can share device logs and testing results.
b. Ensures smoother handoffs between testing and debugging stages.
In an era where speed and quality are non-negotiable, DeviceTunnel helps teams bridge the gap between local development and cloud testing. By empowering developers with real-time device access, Pcloudy enables faster debugging, fewer production defects, and accelerated release cycles—ultimately enhancing the overall app experience.
The mobile market has seen exponential growth over the past decade, largely driven by the mobile application industry. With more than 3.5 billion smartphone users worldwide, mobile apps have become an integral part of our daily lives. This booming sector is expected to generate over $189 billion in revenue by 2020 through app stores and in-app advertising, and the demand shows no signs of slowing down. As mobile apps become more ubiquitous, the competition to create unique, high-performing apps has intensified.
Yet, as apps grow more complex and diverse, so do the challenges faced in ensuring their quality. Mobile app testing plays a pivotal role in meeting these challenges, especially as the industry evolves at a rapid pace. Below, we explore the common issues in mobile app testing and offer solutions to ensure apps remain competitive, reliable, and user-friendly.
One of the most significant challenges in mobile app testing is device fragmentation. With countless manufacturers, models, operating systems, and screen sizes, testing across all devices is a daunting task. Android alone has a wide range of OS versions, with older versions still in circulation despite new releases. This fragmentation means that an app may perform flawlessly on one device but crash on another.
Testing on a range of real devices is the best way to ensure compatibility. This is where cloud-based platforms like Pcloudy come in. Pcloudy offers access to real devices with varying OS versions and configurations, allowing testers to check how their app behaves across multiple devices without needing physical access to each one.
Pro Tip: It’s crucial to prioritize testing on the most popular devices and operating systems to maximize your app’s reach.
In today’s connected world, apps must perform well across a variety of network conditions. However, this introduces another layer of complexity in mobile app testing. Network issues, such as low bandwidth or weak signal strength, can drastically affect an app’s performance, leading to poor user experiences. According to studies, 53% of users will uninstall an app if it crashes, freezes, or has performance issues.
Testing apps under real-world network conditions is essential to ensure that they perform smoothly, even under poor network environments. Pcloudy offers network simulation tools that enable testers to replicate varying network conditions, from weak 2G signals to high-speed 5G or Wi-Fi, on real devices.
Pro Tip: Regularly test your app’s performance in low-bandwidth scenarios to ensure seamless user experiences in all conditions.
The choice of testing tools can significantly impact the efficiency and effectiveness of mobile app testing. There are numerous tools available in the market, each with its strengths and weaknesses. Selecting the right one based on your app type (native, hybrid, or web) and testing needs is critical.
To navigate this landscape, it’s crucial to evaluate tools based on your specific app requirements. Pcloudy supports a wide range of automation tools, such as Appium, Espresso, and Selenium, making it easier for teams to test apps across multiple environments.
Consider the following when evaluating tools:
Mobile devices come in various screen sizes, and ensuring that your app displays correctly on all of them can be challenging. Apps that look perfect on a large-screen phone may appear cluttered or disjointed on a smaller device.
Adopt responsive design principles to create adaptable UI layouts. This approach ensures that your app looks good on all screen sizes, from small smartphones to large tablets. Testing your app on real devices of varying screen sizes is crucial, and platforms like Pcloudy allow for testing on multiple screen configurations to ensure a seamless experience.
Pro Tip: Focus on adaptive designs rather than pixel-perfect layouts, as adaptive designs scale more effectively across different screen sizes.
Mobile apps come in three main forms: native, hybrid, and web-based apps. Each type requires a unique approach to testing.
Each app type comes with its own set of testing challenges, and it’s essential to customize your testing strategy accordingly. Pcloudy supports testing for all three app types, allowing teams to ensure that their apps meet the required standards of performance, usability, and functionality.
Artificial intelligence is revolutionizing mobile app testing by automating complex testing tasks, generating test cases, and predicting defects. AI-driven testing can significantly reduce time and effort, allowing testers to focus on more critical aspects of app development.
AI-powered test automation, like the solutions offered by Pcloudy, helps automate repetitive tasks such as regression testing, bug detection, and performance analysis. AI-driven bots can create test cases, execute tests, and analyze results, enabling faster releases and higher accuracy.
Pro Tip: Embrace AI-based testing early to stay ahead of the competition. Automating repetitive tests frees up resources for more creative problem-solving.
In an era where data privacy and security are of paramount importance, ensuring that your app is secure and compliant with regulations is vital. The increasing number of cyberattacks and data breaches highlights the need for robust security testing.
Incorporate security and compliance testing into your QA process. Test for data encryption, authentication, and security vulnerabilities. Pcloudy offers features like biometric authentication testing and encrypted device communication to ensure that your app meets the highest security standards.
Pro Tip: Regularly update your app’s security protocols to keep up with emerging threats and regulations.
Usability testing focuses on how user-friendly your app is, evaluating its ease of navigation, intuitive design, and overall user experience.
Conduct usability testing on real devices to gather feedback from real users. Cloud-based platforms like Pcloudy allow for real-device usability testing, providing insights into the app’s user experience across different devices and operating systems.
Battery consumption is a critical factor that can impact app usage and customer retention. An app that drains battery quickly is likely to be uninstalled by users.
Test for battery efficiency on various devices using real-device cloud testing environments like Pcloudy. Analyze how your app consumes battery power and optimize where needed to ensure it runs smoothly without excessive battery drain.
Memory leaks occur when an app uses excessive memory, causing performance issues like slowdowns or crashes. This can lead to a poor user experience, especially on devices with limited resources.
Implement memory profiling tools during your app’s development and testing phases. Regularly test your app on different devices using Pcloudy to identify and fix memory leaks.
For apps that rely on geolocation features, such as navigation or ride-hailing apps, ensuring that location services work across different regions is crucial.
Use cloud platforms like Pcloudy to simulate geolocation testing on real devices in different geographic regions. This ensures your app’s location services work accurately across the globe.
Apps often need to be localized to different languages, currencies, and cultural contexts. Ensuring proper localization is essential for expanding into global markets.
Conduct thorough localization testing, focusing on the user interface, translations, and regional features. Pcloudy allows testing in real-world scenarios for apps localized into multiple languages and regions.
Accessibility testing ensures that your app is usable by people with disabilities, such as visual or hearing impairments. Ensuring your app meets accessibility standards is vital for inclusivity and can be a regulatory requirement in many regions.
Use accessibility testing tools to check your app’s compatibility with screen readers, voice commands, and other assistive technologies. Test your app on different devices using Pcloudy to ensure it meets accessibility guidelines.
Interruption testing evaluates how well an app handles interruptions like phone calls, text messages, or low battery alerts. These interruptions are common during real-world app usage.
Perform interruption testing on real devices to evaluate how your app reacts to common disruptions. Cloud platforms like Pcloudy allow testers to replicate interruptions during active app sessions, ensuring smooth recovery and minimal disruption.
Each app store (Google Play, Apple App Store) has specific guidelines for app submission. Failing to comply with these guidelines can result in rejection, delaying your app’s release.
Before submitting your app, ensure it meets all necessary guidelines. Test your app’s experience, security, and overall quality on multiple devices and operating systems using Pcloudy to minimize the risk of rejection.
Mobile app testing involves overcoming a wide range of challenges, from ensuring compatibility across numerous devices to handling network variability, memory leaks, and accessibility. A successful testing strategy combines real-device testing, cloud-based automation, AI-driven test automation, and comprehensive security testing to deliver a high-quality app experience.
Pcloudy provides a robust cloud-based platform for mobile app testing, offering access to real devices, network simulation, and AI-powered automation. By adopting a well-rounded approach to testing, you can ensure
In today’s highly competitive mobile app market, delivering a flawless user experience is essential. Mobile apps are constantly updated with new features, bug fixes, and optimizations to meet user expectations. To ensure quality across diverse devices, operating systems, and networks, different types of testing methods are required. These testing techniques help ensure that apps not only function well but also provide a seamless, reliable, and enjoyable user experience. In this blog, we’ll explore seven essential types of mobile app testing, along with the challenges that arise and the solutions to overcome them.
Compatibility testing ensures that a mobile app works across a variety of operating systems, device models, screen sizes, and hardware configurations. This type of testing is critical because mobile users access apps on a wide range of devices with varying capabilities, and failure to support even a subset of these can lead to user frustration and lost customers.
Key factors that impact compatibility testing include:
Challenge:
One of the biggest challenges in compatibility testing is the sheer number of device combinations that need to be tested. Managing physical devices in-house is expensive and resource-intensive.
Solution:
Cloud-based testing platforms like Pcloudy provide an efficient solution by giving access to thousands of real devices with different OS versions and hardware configurations. This helps teams to automate compatibility tests and scale their testing efforts without maintaining physical labs. Pcloudy also enables parallel testing across multiple devices, speeding up the overall process.
Installation testing is one of the first interactions a user has with a mobile app. It ensures that an app installs, uninstalls, and updates without issues. This testing is critical to verify the app’s ability to install smoothly across various devices and handle future updates seamlessly.
Key areas to focus on include:
The main challenge in installation testing is handling various installation environments, especially on devices with low memory or unstable network connections. Additionally, testing installation scenarios across different OS versions and devices can be complex.
Using a cloud-based testing product like Pcloudy, QA teams can test on real devices under real-world conditions. Pcloudy provides access to thousands of actual mobile devices with varying configurations, enabling teams to test scenarios like low-memory conditions, update handling, and different installation environments. Automation tools help execute various user actions during the installation process, ensuring robust testing across multiple environments without manual intervention. This ensures that your app installs, updates, and uninstalls smoothly across different devices and conditions, providing users with a seamless experience.
Interruption testing evaluates how well a mobile app handles unexpected events, such as incoming calls, network disruptions, or battery drains, while the app is running. The goal is to ensure that the app resumes normal functionality after an interruption.
Common interruptions to test include:
Replicating real-world interruptions, especially across different devices, OS versions, and network conditions, can be difficult to reproduce consistently.
Pcloudy provides a reliable environment to automate and simulate interruptions such as network loss, incoming calls, or device shutdowns. Tools like Monkey (for Android) or UI Auto Monkey (for iOS) help simulate interruption scenarios, allowing testers to monitor how well the app recovers from these events. Automating these tests across multiple devices ensures thorough coverage.
Localization testing ensures that a mobile app is tailored to a specific geographic region, considering cultural, linguistic, and regional differences. This testing verifies that the app works seamlessly when localized for various languages, currencies, time zones, and formatting conventions.
Four key types of localization testing include:
Managing translations and ensuring cultural accuracy across multiple regions can be challenging, especially with languages that have different text directions, such as Arabic or Hebrew. Additionally, it’s important to ensure that all text is properly displayed without breaking the app layout.
Tools like Pcloudy allow testers to run localization tests across real devices in different regions, ensuring linguistic and functional accuracy. Automated scripts can be used to check for proper translation, layout adaptation, and functionality. Pcloudy provides access to a wide range of devices from different locales, helping to ensure comprehensive localization testing across multiple regions.
Performance testing is essential to ensure that the mobile app performs optimally under various conditions, such as high load, different network speeds, and limited device resources. It identifies performance bottlenecks, stability issues, and overall app responsiveness.
The three primary areas of focus in mobile performance testing are:
Replicating real-world conditions like varying network speeds or high traffic loads is a significant challenge. Ensuring that the app works well under different device configurations while maintaining performance consistency is also complex.
Pcloudy’s network simulation feature allows QA teams to replicate different network conditions, such as low bandwidth or high latency, to test how well the app performs under challenging conditions. Additionally, using tools like Pcloudy to run performance tests across multiple devices ensures that device-specific issues, such as excessive battery drain or memory usage, are identified and addressed early in the development cycle.
Usability testing ensures that the app is user-friendly and provides an intuitive, seamless experience. This type of testing focuses on how easy it is for users to navigate through the app, complete tasks, and interact with the app’s features.
Key factors in usability testing include:
Example of Navigation Path
Usability testing can be subjective, as user preferences and behaviors vary. It’s difficult to ensure that the app will be intuitive for all user types and across different demographics. Additionally, collecting meaningful feedback from users to guide improvements can be challenging.
Tools like Mr. Tappy or Reflector can capture real user interactions during usability testing, allowing testers to observe how users navigate and respond to the app. Recording user sessions helps teams identify pain points and optimize the user experience. Pcloudy’s cloud-based platform allows for testing on a wide range of devices, ensuring that the app remains user-friendly across different screen sizes, input types, and configurations.
Conformance testing, also known as compliance testing, ensures that your mobile app adheres to industry standards, regulatory requirements, and marketplace guidelines. This type of testing is critical, especially when submitting apps to app stores or meeting enterprise policy guidelines. Ensuring conformance can prevent rejections from app marketplaces and avoid penalties related to non-compliance with industry regulations.
The two key areas of conformance testing include:
Enterprise Policy Compliance: In some industries, apps must comply with industry-specific regulations. For instance, healthcare apps may need to comply with HIPAA (Health Insurance Portability and Accountability Act), while pharmaceutical apps may fall under FDA (Food and Drug Administration) guidelines. Meeting these standards is essential to maintaining credibility and avoiding legal issues.
Staying up-to-date with app store guidelines and ensuring that the app meets the ever-changing standards of different marketplaces can be difficult. Moreover, managing compliance with strict industry regulations can be overwhelming, particularly when apps are released across multiple regions with differing legal frameworks.
Pcloudy offers a comprehensive conformance testing solution that helps validate whether your app meets both app store guidelines and industry regulations. Automated checks ensure your app complies with the latest app store rules before submission, while the platform’s flexibility allows for testing specific compliance criteria related to industries like healthcare or finance. Pcloudy’s regular updates keep testers informed of any changes to app store guidelines, reducing the risk of non-compliance.
In an increasingly competitive mobile app market, delivering a high-quality user experience is crucial to success. Testing your app across various dimensions—compatibility, installation, interruptions, localization, performance, usability, and conformance—ensures that it functions seamlessly and meets user expectations across different devices, regions, and conditions. Each type of testing addresses specific challenges that can impact an app’s performance, usability, or compliance with industry standards.
The challenges associated with these testing types can be daunting, but with cloud-based testing platforms like Pcloudy, teams can automate, scale, and simplify the testing process. From testing real-world interruptions to ensuring app store compliance, Pcloudy offers the tools and resources to ensure comprehensive mobile app testing without the hassle of managing physical devices or manual testing efforts.By incorporating these testing strategies, mobile app developers and QA teams can confidently release bug-free apps that provide a flawless user experience, leading to higher user satisfaction, increased app downloads, and long-term customer retention.
Industry leaders consider CI/CD to be an essential part of the app development cycle as enterprises are keen to reduce the time to market. Continuous integration and continuous delivery help in improving and enhancing the quality of the product while reducing the cost of the project. This blog will help you understand the of a functioning CI/CD pipeline, its challenges, and its benefits. Before we get into the details, let’s have a look at the basic terminology.
Continuous integration (CI) is a software development practice where developers frequently make changes in the code and add it to the central repository after which automated tests are run. CI is the integration stage of the software release process which depends on automation and constant integration. The main goal is to find the bugs and resolve the issue quickly to improve the software quality and reduce the time to market.
In continuous integration, developers focus on smaller commits several times a day. Developers pull the code from the repository before pushing it to the build server where the build server runs various tests to verify the code commit.
Continuous delivery is a software development practice that ensures a faster and stable release of the changes in the code. In this, the changes are automatically built, tested, and prepared for production release. The code changes are deployed to a testing environment or a production environment after the build stage is completed. When continuous delivery is implemented, developers always have a deployment-ready build artifact that has passed through a standard test process. In continuous development, the code revisions to a production environment automatically which allows for a continuous feedback loop early in the development cycle.
Continuous deployment is a bit similar to continuous delivery but is a step further towards process automation. The change that passes through all the production stages is released to the client directly without the need for any human intervention. Continuous deployment accelerates the feedback loop as only a failed test will stop the change from getting deployed to production.
It is the practice of executing automated tests throughout the software development life cycle. Instead of the old testing method where testing occurs at the end of the software development cycle, CT occurs at multiple stages, including development, integration, pre-release, and in production. It is done to ensures that bugs are caught and fixed at the earlier stages in the development process, saving a significant amount of time and money.
While building an application that will be deployed on the live servers there will be a team of developers responsible to write the code. The developers commit the code into a version control system like Git, from where it goes to the build phase. The built is then sent to the next phase with a proper version tag.
For instance, you have a code that needs to be compiled before execution. When the code enters the built phase, all the features of the code are merged from various repositories and compiled using a compiler.
The next phase is the testing phase where various types of testing are performed. Sanity testing and unit testing are the most crucial part of this process as individual units of the built are tested to check if they meet the requirements.
The builds are moved to the deployment phase after passing the test and then pushed into a test server. Here developers simulate the product in a production-like environment to examine the features.
Before the build features are deployed to production, the automation test phase will perform the final tests to qualify the features. continuous testing is implemented in this phase to ensure there are no bugs remaining.
In case there is an error at any stage of the CI/CD pipeline, feedback will be sent to the development team so that issues are addressed immediately. Thereafter, code changes will go through the production pipeline once again.
In the final phase, the code is moved to the production server after code passes all the tests. The constant feedback loop helps make the CI/CD pipeline a closed process where builds are continuously committed, tested, and deployed to production.
Limited environments
During the CI/CD pipeline implementation, a limited number of shared test environments increases the risks of a bottleneck. You would need to reserve an environment to avoid multiple CI/CD pipelines running side by side from attempting to deploy and test in the same environment. One of the leading causes of deployment failures is misconfigured environments modified by previous teams or test runs.
Security and Ownership
Sometimes it’s difficult to know who needs to fix the pipeline when the stages fail as delivery pipelines span multiple teams in an organization. An owner has to be assigned at every stage of the CI/CD pipeline who will be responsible to fix the issues and ensuring that the delivery runs smoothly. The owner will also contribute to the feedback-driven improvement of the pipeline.
The orchestration tool used by the team should have an effective security model that could provide better visibility into the state of the entire CI/CD pipeline. For instance, to identify the causes of test failure, the team would have to examine the result of the test phase. But they should not be given permission to modify or disable the configuration of that test step.
Managing multiple custom CI/CD pipelines
There will be multiple CI/CD pipelines in large organizations as they have diverse portfolios spanning different departments, technology platforms, and customers. It would be difficult to analyze metrics like throughput, successful execution, and cycle time if every pipeline ends at different stages in the delivery process. It’s easier to manage a large set of CI/CD pipelines if each one is based on a standard template. This will help in meaningful comparative reporting and it will provide useful feedback to improve other pipelines.
Massive applications
Large apps with several components that need to be compiled, tested and deployed are tough to update incrementally which leads to long testing and deployment cycles. It’s harder to perform quality control and root cause analysis as multiple teams commit several changes at the same time. It’s difficult to create a standardized delivery pipeline as the release process needs to differ slightly. Teams often initiate a workstream to incrementally break out components of the app into different modules so that they can be built and deployed separately, allowing for faster feedback cycles with smaller sets of code changes.
Complex Branching Strategies: Navigating complex branching strategies can be a significant challenge in CI/CD pipelines. Without a clear and consistent strategy, such as GitFlow or trunk-based development, teams may struggle with merge conflicts, delayed features, and integration issues. Establishing a streamlined branching strategy that aligns with the CI/CD objectives is crucial for minimizing integration headaches and facilitating continuous integration.
Handling Dependencies: Modern applications often rely on numerous external libraries and services. Managing these dependencies can become a challenge, particularly when updates to dependencies break the build or introduce vulnerabilities. Effective dependency management tools and practices, such as semantic versioning and automated dependency updates, are essential to maintain the stability and security of the CI/CD pipeline.
Flaky Tests: Automated tests are the backbone of CI/CD pipelines, ensuring that code changes do not introduce regressions. However, flaky tests, which produce inconsistent results, can undermine confidence in the build process. Addressing test flakiness requires a disciplined approach to test writing, including isolating tests from external dependencies and ensuring that tests are deterministic.
Scaling the Pipeline: As projects grow in complexity and team size, scaling the CI/CD pipeline can become a challenge. Issues such as increased build times, resource contention, and the management of parallel jobs need to be addressed. Techniques such as build matrix reduction, parallel test execution, and the use of scalable cloud resources can help maintain pipeline efficiency at scale.
Third-Party Integrations: CI/CD pipelines often integrate with various third-party services for code analysis, deployment, monitoring, and more. Managing these integrations, especially when dealing with API rate limits, service downtimes, or incompatible updates, requires careful planning and fallback mechanisms to ensure the pipeline’s resilience.
Avoiding Configuration Drift: Ensuring consistency across development, testing, staging, and production environments is crucial. Configuration drift, where environments become inconsistent over time, can lead to “works on my machine” issues and deployment failures. Infrastructure as Code (IaC) tools and practices can help mitigate this risk by codifying environment configurations and making them part of the version-controlled repository.
Skill Gaps: Implementing and maintaining a CI/CD pipeline requires a broad set of skills, including coding, automation, infrastructure management, and security. Talent gaps in these areas can hinder the effectiveness of CI/CD initiatives. Continuous learning and cross-training, along with the hiring or consulting with experts, are strategies to overcome these challenges.
CI/CD provides several benefits for your software development team including improving developer productivity, automating the process, improving code quality, and delivering updates to your customers faster. Let’s have a look at some more benefits of implementing a CI/CD pipeline.
Improve Developer Productivity
CI/CD practices enhance your team’s productivity by freeing developers from manual tasks, working on complex dependencies, and returning focus to delivering new features. Instead of integrating their code with other parts of the business and spending time on how to deploy this code to a platform, developers can focus on coding logic that delivers the features you need.
Automated Software Release Process
Continuous delivery provides a method for your team to check-in code that is automatically built, tested, and prepared for release to production so that your software delivery is efficient, resilient, rapid, and secure.
Improve Code Quality
CD can help you discover and address bugs early in the delivery process before they grow into larger problems later. Your team can easily perform additional types of code tests because the entire process has been automated. With the discipline of more testing more frequently, teams can iterate faster with immediate feedback on the impact of changes. This enables teams to drive quality code with a high assurance of stability and security. Developers will know through immediate feedback whether the new code works and whether any breaking changes or bugs were introduced. Mistakes caught early on in the development process are the easiest to fix.
Deliver Updates Faster
CD helps your team deliver updates to customers quickly and frequently. When CI/CD is implemented, the velocity of the entire team, including the release of features and bug fixes, is increased. Enterprises can respond faster to market changes, security challenges, customer needs, and cost pressures. For example, if a new security feature is required, your team can implement CI/CD with automated testing to introduce the fix quickly and reliably to production systems with high confidence. What used to take weeks and months can now be done in days or even hours.
Continuous integration and continuous delivery is an ideal solution for an organization’s app development teams. Developers just need to push the code to a repository. The code will be integrated, tested, deployed, tested again, merged with infrastructure, go through security and quality reviews, and be ready to deploy with extremely high confidence. A CI/CD pipeline helps improve code quality and software updates are delivered quickly.
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In the dynamic world of software development, ensuring the reliability and stability of your application is of utmost importance. Unit testing stands as a first line of defense against bugs and errors, playing a crucial role in securing the application’s robustness. Let’s delve deeper into the intriguing world of unit testing, beginning with what it is and then exploring its indispensable role in modern app development.
Unit testing, a fundamental practice in app development, is the process of testing individual units or components of a software application. It is generally conducted during the development phase, primarily by developers, to validate that each unit of the software performs as designed.
A “unit” in this context refers to the smallest part of a software system that can be tested in isolation. It might be a function, method, procedure, or an individual module, depending on the complexity of the software. The primary goal is to validate that each unit functions correctly and meets its design specifications.
Below, we delve into the importance of unit testing in the realms of web and mobile applications:
Unit testing allows developers to identify bugs early in the development cycle, which not only saves time but also significantly reduces the cost of bug fixing. Early bug detection ensures that issues are nipped in the bud before they escalate to more critical stages.
With a well-established unit testing practice, developers can make changes to the code or refactor it with confidence. Unit tests act as a safety net, helping to identify unforeseen impacts of the modifications, thus ensuring the consistency of the application.
When developers write unit tests, it naturally leads to better code quality. Developers are more likely to write testable, modular, and maintainable code, fostering an environment of excellence in code craftsmanship.
Unit testing can significantly improve developer productivity. Since bugs are caught early, developers spend less time debugging and more time building new features. Moreover, the immediate feedback provided by unit tests helps streamline the development process.
When a unit test fails, it is much easier to identify and fix the issue, as you only need to consider the latest changes. This contrasts sharply with higher-level tests where a failure might be the result of a myriad of factors, making debugging a complex and time-consuming task.
Unit tests facilitate smoother integration processes. When integrating various components or modules, unit tests can quickly pinpoint issues at the unit level, making the integration process more efficient and less error-prone.
In web and mobile applications, security is paramount. Unit testing helps in identifying vulnerabilities at the code level, allowing developers to fortify the application against potential security breaches, thus safeguarding user data and privacy.
By ensuring the stability and reliability of web and mobile applications through unit testing, developers can significantly enhance customer satisfaction. A bug-free, smooth-running application is more likely to earn user trust and build a loyal customer base.
Performing unit testing is an essential practice in ensuring the robustness and reliability of your application. Whether you are working on a mobile or web application, incorporating unit testing into your development process can help you deliver a high-quality product. Here is a step-by-step guide to effectively performing unit testing on apps:
Before you start with unit testing, familiarize yourself with the codebase and understand the functionalities of different units. Having a clear picture will aid in writing more effective and relevant tests.
Set up a separate testing environment where the unit tests will be executed. This environment should be isolated from production to avoid any unintended consequences. Utilize unit testing frameworks suitable for your programming language to streamline the process.
3.1 Choose the Units to be Tested
Identify the critical components that need testing. Start with the core functionalities that form the backbone of your application.
3.2 Create Test Cases
For each unit, create test cases that cover various scenarios including edge cases. Each test case should focus on a single functionality.
3.3 Mock External Dependencies
Use mocking frameworks to simulate external dependencies, ensuring the unit is tested in isolation. This helps in pinpointing the issues more accurately.
Run the tests using the testing framework. Ensure to cover different cases including:
Positive Cases: Where the input meets the expected criteria.
Negative Cases: Testing with inputs that are supposed to fail, to ensure proper error handling.
Edge Cases: Testing the limits of the input parameters.
After execution, analyze the results thoroughly. If a test fails, investigate the cause and fix the issue before proceeding.
Integrate the unit tests into a Continuous Integration system to automate the testing process. The CI system should be configured to run the unit tests automatically each time code is pushed to the repository.
As the application evolves, continually update the test cases to mirror the changes in the application. Remove obsolete tests and add new ones for the newly added functionalities.
Maintain a well-documented record of all the test cases, including the input parameters and expected outcomes. This documentation will serve as a reference and aid in understanding the expected behavior of the application units.
Encourage collaboration in the team where code and test cases are reviewed by peers to ensure the quality and effectiveness of the unit tests.
Continuously improve your unit testing skills through training and learning. Stay updated with the latest trends and best practices in unit testing to enhance the quality of your tests.
The process of unit testing can be substantially improved by adhering to a set of best practices and methodologies. These practices not only streamline the testing process but also enhance the overall quality and reliability of the software product. Here are several strategies to consider for optimizing your unit testing efforts:
Implement a coherent and descriptive naming convention for your test cases. This facilitates easier identification and understanding of the tests, fostering smoother collaboration and maintenance.
Focus on testing individual units of code separately to isolate potential issues effectively. This strategy ensures that each component functions correctly in isolation, paving the way for a more robust application.
Whenever there is a modification in the code, ensure to create or update the corresponding unit test cases. This practice helps maintain the relevance and effectiveness of your test suite, allowing for the timely detection of issues introduced by the changes.
Prioritize the immediate resolution of identified bugs before progressing to the next development phase. Quick bug resolution minimizes the potential for escalating issues and maintains the stability of the codebase.
Integrate unit testing into your code commit cycle to foster a test-driven development environment. Conducting tests as you commit code helps in the early detection of issues, reducing the chances of errors proliferating through the codebase.
Concentrate your testing efforts on scenarios that significantly influence the system’s behavior. Adopt a behavior-driven testing approach to ensure that the application behaves as expected under various conditions, enhancing reliability and user satisfaction.
Leverage virtualized environments, such as online Android emulators, to conduct unit tests in scenarios that closely resemble real-world conditions. These environments offer a convenient platform to test the application under different settings without the need for physical devices.
Incorporate unit testing into a continuous integration (CI) pipeline to automate the testing process. CI allows for the regular and systematic execution of unit tests, ensuring that the codebase remains stable and bug-free as it evolves.
Promote the practice of peer reviews for both code and test cases. Reviews foster collaboration and knowledge sharing, enhancing the overall quality and robustness of the application.
A notable limitation of unit testing is its inability to verify all execution paths and detect broader system or integration errors. Since unit tests focus on individual components, they might overlook issues that only emerge during the interaction between different units or systems.
Unit testing might not be comprehensive enough to identify complex errors that are generally captured during integration or system testing. It is, therefore, essential to complement unit tests with other testing methodologies for a well-rounded verification of the software.
In light of the above discussion, it becomes unequivocally clear that unit testing stands as a cornerstone in safeguarding the integrity and reliability of software development. Steering clear of it is not only detrimental to the code quality but could potentially escalate the costs and efforts involved in the later stages of development.
Adopting a Test-Driven Development (TDD) approach further amplifies the benefits of unit testing. In this paradigm, developers construct tests before writing the corresponding code, thereby ensuring that the codebase develops with testing at its core. This not only engrains a quality-first mindset but also facilitates a workflow that is more organized and less prone to errors.
Moreover, the utilization of appropriate tools and frameworks can streamline the unit testing process substantially, making it less cumbersome and more efficient. These tools can automate various aspects of testing, helping to detect issues swiftly and reducing manual effort considerably.
As we navigate through an era where software forms the backbone of many critical systems, the role of unit testing in fostering robust, secure, and reliable applications cannot be understated. It emerges not as an option but a necessity, carving pathways for innovations that are both groundbreaking and resilient.
By embracing unit testing as an integral part of the development cycle, developers are not only upholding the quality and reliability of their applications but are also taking a step towards crafting products that stand the test of time, offering optimal performance and user satisfaction.
In today’s digital age, mobile applications have become an integral part of our lives. We rely on them for various tasks, from socializing and entertainment to productivity and financial transactions. However, nothing is more frustrating than using an app that crashes frequently, behaves erratically, or fails to meet our expectations. Such experiences often lead users to uninstall the app and move on to alternatives.
To ensure that mobile applications meet user expectations and deliver a seamless experience, thorough testing is crucial. Testing plays a vital role in identifying and rectifying issues, thereby improving the overall quality of the app. Functional testing and non-functional testing are two key categories of testing that focus on different aspects of the application.
Functional testing is a process of evaluating the behavior, features, and functionality of an application to ensure that it works as intended. The primary goal of functional testing is to validate that each function of the application performs correctly according to the specified requirements. This type of testing focuses on user-friendliness and ensuring that the application meets the expectations of its intended users.
To perform functional testing, first we need to identify the test input and compute the expected outcomes with the selected test input values. Then we execute the test cases and compare the actual data to the expected result.
Unit testing involves testing individual components or units of code in isolation to verify their functionality. It is usually performed by developers during the development phase. The purpose of unit testing is to ensure that each unit of code functions as intended and meets the specified requirements. It helps identify defects early in the development cycle, promotes code reusability, and provides a solid foundation for integration testing.
In unit testing, test cases are created to validate the behavior of individual functions, methods, or classes. Mock objects or stubs may be used to simulate dependencies and isolate the unit under test. By testing units in isolation, developers can easily identify and fix bugs, making the code more reliable and maintainable.
Integration testing focuses on validating the interaction between different components or modules of the application. It ensures that the integrated parts work harmoniously and produce the expected output. Integration testing can be performed using various approaches:
Top-down approach: Integration testing starts from the highest-level components, and gradually lower-level components are integrated and tested. This approach allows early identification of integration issues in major components.
Bottom-up approach: Integration testing begins with the lower-level components, and higher-level components are gradually added and tested. This approach is useful when lower-level components are more stable and critical to the application’s functionality.
Sandwich or hybrid approach: This approach combines elements of both top-down and bottom-up approaches. It aims to achieve a balanced integration of components by identifying and addressing issues at different levels simultaneously.
Integration testing verifies that components can communicate and exchange data correctly, handle errors gracefully, and maintain data integrity throughout the system.
Sanity testing, also known as smoke testing, is a quick evaluation of the application’s major functionalities after making small changes or fixes. Its primary objective is to determine if the critical functions of the application are working as expected before proceeding with further testing.
Sanity testing focuses on the most crucial features and functionality to ensure that the recent changes have not introduced any major issues. It is not an in-depth or exhaustive test but rather a superficial check to provide confidence that the application is stable enough for further testing.
By performing sanity testing, teams can catch critical issues early and avoid wasting time on extensive testing if the application’s fundamental functionality is compromised.
Regression testing involves retesting the previously tested functionalities of the application to ensure that any new changes or bug fixes have not introduced new defects or caused existing functionalities to fail. It aims to maintain the stability and integrity of the application.
When new features or bug fixes are introduced, regression testing helps ensure that these changes do not impact the existing functionality of the application. It involves rerunning test cases that cover the affected areas to confirm that the system behaves as expected after modifications.
Regression testing can be performed manually or through automated testing tools. Automated regression testing is often preferred for efficiency and accuracy, especially when there are frequent code changes or a large number of test cases.
System testing evaluates the entire system as a whole to verify its compliance with the specified requirements. It covers end-to-end scenarios, including various functionalities and interactions between different components.
System testing can be performed in both black box and white box testing approaches, depending on the level of access to the system’s internal workings. It tests the system’s behavior, performance, security, and other non-functional aspects to ensure it meets the desired standards and user expectations.
System testing typically involves creating comprehensive test cases that simulate real-world scenarios and user interactions. It aims to identify any discrepancies between the expected behavior and the actual behavior of the system.
Beta testing, also known as user acceptance testing (UAT), involves releasing the application to a limited set of end-users or external testers to evaluate its performance and gather feedback. It helps validate the application’s usability, compatibility, and overall user experience.
During beta testing, real users test the application in a production-like environment, providing insights into its strengths, weaknesses, and potential areas of improvement. Feedback collected during this phase helps identify bugs, usability issues, and other areas for refinement.
Beta testing is particularly valuable for identifying user-centric issues that might not have been discovered during earlier testing phases. It allows the development team to make necessary adjustments before the application’s full release, enhancing its quality and user satisfaction.
Overall, these different types of testing play crucial roles in ensuring the quality, reliability, and usability of software applications at various stages of the development process.
Non-functional testing focuses on evaluating the quality attributes and performance of the application beyond its functional aspects. It aims to ensure that the application meets specific criteria related to reliability, performance, usability, security, compatibility, and other non-functional requirements.
Performance testing is crucial to ensure the smooth functioning of an application under expected workloads. Its primary objective is to identify performance-related issues such as reliability and resource usage, rather than focusing on finding bugs. When conducting performance testing, it is essential to consider three key aspects: quick response time, maximum user load, and stability across diverse environments. Even if you are primarily focused on mobile testing and employ online Android emulators, performance testing remains indispensable.
Endurance testing, also known as soak testing, verifies the application’s ability to handle sustained loads over an extended period. It aims to identify any performance degradation or resource leaks that may occur during continuous usage. By subjecting the application to a prolonged workload, endurance testing helps ensure that it can sustain high usage without issues such as memory leaks, performance degradation, or resource exhaustion.
Scalability testing measures how well the application can handle increased workload or user demand by adding more resources, such as servers or network bandwidth. It evaluates the application’s ability to scale seamlessly as the user base grows. Scalability testing helps determine the system’s capacity to handle additional load without significant performance degradation or loss of functionality.
Load testing evaluates the application’s behavior and performance under expected and peak loads. It involves simulating user interactions and subjecting the system to high concurrent user activity or data volumes. The purpose is to determine the maximum capacity of the application and identify potential bottlenecks or performance issues. Load testing helps ensure that the application can handle the anticipated user load without crashes, slowdowns, or data inconsistencies.
Usability testing plays a critical role in identifying usability defects within an application. It involves a small group of users evaluating the application’s usability, primarily during the initial phase of software development when the design is proposed. The focus is on assessing the ease of use and whether the system meets its intended objectives. Usability testing can also be conducted on online Android emulators for mobile applications.
Several methods can be employed for conducting usability testing. During the design phase, one approach involves evaluating the design concept using paper prototypes or sketches. Another method involves conducting random tests once the application is developed to assess its usability. Real users can be engaged on the site to perform these tests, providing valuable feedback and results. Additionally, tools that provide statistical analysis based on design inputs and wireframes can be utilized to support usability testing efforts.
The first step in conducting structured usability testing is to identify the target users who will be interacting with the application. Users should be selected based on their characteristics, such as geography, age, gender, and other relevant factors that align with the application’s intended user base. The next step involves designing specific tasks for the users to perform, which will help evaluate the application’s usability. The results of the testing are then analyzed and interpreted.
Usability testing can be performed in a controlled test environment with observers present. These observers closely monitor the testing process and create a comprehensive report based on the users’ assigned tasks and their interactions with the application. Another option is remote usability testing, where both the observers and the testers are located in separate locations. In remote testing, the users perform the assigned tasks from their own environment, and their reactions and interactions are recorded using automated software.
By conducting usability testing using appropriate methods and involving representative users, organizations can gain valuable insights into their application’s usability, identify potential issues, and make informed design decisions to enhance the overall user experience.
Security testing is an integral part of the mobile app testing process and holds utmost importance in ensuring the app’s resilience against external threats, such as malware and viruses. It plays a critical role in identifying vulnerabilities and potential loopholes within the application that could lead to data loss, financial damage, or erosion of trust in the organization.
Let’s explore the key security threats that need to be addressed during security testing:Privilege Elevation: This threat involves a hacker exploiting an existing account within your app to increase their privileges beyond what they are entitled to. For example, if the app offers credits for referring friends, the hacker might manipulate the system to obtain more credits and gain financial advantage.
Unauthorized Data Access: One of the most prevalent security breaches is unauthorized access to sensitive information. This can occur through hacking login credentials or gaining unauthorized access to the server where the data is stored. Security testing aims to identify and rectify vulnerabilities that could lead to such unauthorized access.URL Manipulation: Hackers may manipulate the URL query string if the app or website employs the HTTP GET method for data transfer between the client and server. Security testing includes assessing if the server properly validates and rejects modified parameter values, ensuring that unauthorized manipulation of data is prevented.
Denial of Service: This type of attack disrupts app services, rendering them inaccessible to legitimate users. Hackers may exploit vulnerabilities to overwhelm the app or server, making it unstable or unavailable for use. Security testing aims to identify weaknesses in the app’s infrastructure and implement safeguards against such attacks.
By conducting comprehensive security testing, organizations can strengthen the app’s defenses, mitigate potential security risks, and safeguard user data, revenue, and the overall reputation of the organization. It is crucial to stay proactive in identifying and addressing security vulnerabilities to maintain a secure and trusted app environment.
Compatibility testing ensures that the application functions correctly across different devices, operating systems, browsers, and network environments. It helps guarantee a consistent user experience and broadens the application’s reach to a wider audience. Compatibility testing involves verifying that the application’s features, functionality, and user interface are compatible with various platforms and configurations. By conducting compatibility testing, developers can address issues related to device-specific behaviors, screen resolutions, browser compatibility, and network compatibility.
Accessibility testing verifies that the application is accessible to users with disabilities. It ensures compliance with accessibility standards and guidelines, making the application usable for individuals with visual, hearing, or mobility impairments. Accessibility testing involves evaluating factors such as screen reader compatibility, keyboard navigation, color contrast, alternative text for images, and adherence to accessibility guidelines. By conducting accessibility testing, developers can ensure that their application is inclusive and can be accessed by a wider range of users, regardless of their abilities.
These different types of non-functional testing are essential for ensuring that the application not only functions correctly but also meets performance, usability, security, compatibility, and accessibility standards. By thoroughly testing these aspects, developers can deliver a high-quality application that provides a positive user experience, addresses potential issues, and meets the needs of a diverse user base.
Functional Testing
Non-Functional Testing
Validates the actions, operations, and functionalities of an application.
Verifies the performance, reliability, and other non-functional aspects of the application.
Focuses on validating user requirements and ensuring the application functions as intended.
Focuses on evaluating user expectations, such as performance, usability, security, scalability, and other non-functional attributes.
Executed before non-functional testing to ensure basic functionality is in place.
Executed after functional testing to assess the application’s non-functional characteristics.
Functional requirements are relatively easier to define as they directly align with user actions and expected outcomes.
Requirements for non-functional testing, such as performance targets, security standards, usability guidelines, or regulatory compliance, can be challenging to define precisely.
Example: Testing the login functionality to ensure users can successfully log into the application.
Example: Verifying that a web page loads within one second, ensuring a fast and responsive user experience.
Functional testing is often performed manually to simulate user interactions and validate functionality.
Non-functional testing, especially for aspects like performance, load, stress, and security testing, is best executed using automated tools to simulate real-world scenarios and generate accurate results.
Ensures the application meets functional requirements and performs the expected tasks correctly.
Evaluates the application’s performance, usability, reliability, compatibility, security, and other non-functional aspects.
Typically focuses on individual features, modules, or components of the application.
Takes a holistic approach, assessing the application as a whole, including its integration, performance under different conditions, and adherence to industry standards.
Regression testing is commonly performed in functional testing to ensure new changes or fixes do not impact existing functionality.
Regression testing may also be performed in non-functional testing to ensure changes or optimizations do not adversely affect non-functional attributes.
Functional testing is generally carried out by business analysts, testers, or domain experts.
Non-functional testing may involve a broader range of stakeholders, including performance testers, security analysts, usability experts, and infrastructure specialists.
Focuses on “what the system does” in terms of features and functionality.
Focuses on “how well the system performs” in terms of various non-functional attributes.
The primary focus of functional testing is to validate the application’s behavior and functionality according to the specified requirements. It ensures that the application performs the intended tasks correctly. Non-functional testing, on the other hand, emphasizes assessing quality attributes, performance, and user experience beyond the functional aspects. It evaluates how well the application performs in terms of speed, scalability, security, usability, compatibility, and accessibility.
Functional testing aims to ensure that the application works as intended and meets user expectations in terms of features and functionalities. It focuses on validating the functional requirements and ensuring that the application delivers the desired functionality. Non-functional testing, on the other hand, focuses on evaluating aspects such as performance, usability, security, compatibility, and accessibility to enhance the overall user experience. It aims to identify any issues or limitations related to these quality attributes and improve them for a better user experience.
Functional testing is typically performed during the development phase, starting with unit testing and progressing through integration testing and system testing. It ensures that the application’s core functionality is working as expected. Non-functional testing is often conducted after functional testing, once the application’s basic functionality has been validated. It focuses on assessing the application’s performance, usability, security, compatibility, and accessibility in different environments and scenarios.
Functional testing relies on test cases derived from functional requirements, user stories, and use cases. It involves techniques such as boundary value analysis, equivalence partitioning, and decision tables to validate the expected behavior of the application. The emphasis is on ensuring that the application meets the functional requirements and performs the desired tasks correctly. Non-functional testing requires specific test cases and techniques tailored to each quality attribute being assessed. For example, performance testing may involve the use of load testing tools to simulate heavy user loads and measure the application’s response time. Accessibility testing may involve the use of assistive technology tools to evaluate the application’s accessibility features. Each type of non-functional testing requires specialized techniques and tools to assess the specific quality attribute.
Functional testing focuses on testing individual functions or features of the application to ensure they work correctly. It involves verifying inputs, outputs, and the expected behavior of specific functionalities. Non-functional testing, on the other hand, assesses broader aspects of the application beyond individual functions. It evaluates performance, usability, security, compatibility, and accessibility across the entire system or application.
In functional testing, the success criteria are typically defined based on whether the application performs the expected functions correctly. Test cases are designed to verify specific requirements or user stories. Non-functional testing, however, requires different success criteria depending on the quality attribute being assessed. For example, in performance testing, success criteria may include response time thresholds or maximum load capacity. In security testing, the success criteria may involve identifying and fixing vulnerabilities or achieving compliance with security standards.
Functional testing can often be conducted independently of external factors or dependencies. It focuses on testing the internal behavior of the application. Non-functional testing, on the other hand, often requires external dependencies, such as specific hardware configurations, network environments, or test tools. For example, performance testing may require dedicated performance testing tools, while compatibility testing may require testing across different browsers or devices.
Functional testing can typically be performed in a controlled test environment that mimics the production environment. It allows for consistent and repeatable testing. Non-functional testing, however, often requires different test environments that reflect real-world conditions. For example, performance testing may require using a production-like environment with representative user loads, while compatibility testing may involve testing on various devices, operating systems, and network configurations.
Functional testing usually requires specific test data that represents different scenarios and inputs relevant to the functionality being tested. Non-functional testing may require additional or specific test data related to the quality attribute being assessed. For example, in security testing, test data may include malicious inputs to test vulnerabilities, while performance testing may involve generating large datasets to simulate realistic workloads.
On average, it is observed that an app tends to lose 95% of its new users within the first three months. One of the primary reasons for this high attrition rate is the presence of bugs and issues within the app, which could have been avoided with a robust testing strategy. By implementing thorough functional testing and non-functional testing, app developers can ensure a smoother user experience and reduce the likelihood of losing users.
To facilitate effective testing, tools like pCloudy offer a range of features that simplify and expedite both functional and non-functional testing processes. These tools enable testers and developers to quickly identify and rectify bugs, ensuring that the app meets the desired quality standards before its release.
By investing in reliable testing tools and adopting a proactive testing approach, developers can save valuable time and resources. Early detection and resolution of issues contribute to enhancing the overall app performance, stability, and user satisfaction. Ultimately, this helps businesses retain users, prevent revenue loss, and establish a strong reputation in the competitive app market.
Test cases are the first step in any testing cycle and are very important for any project. If anything goes wrong at this step, the impact gets proliferated in the entire software testing process. This can be avoided if the testers use proper procedure and guidelines while creating the test case template.
In this blog, I am going to share some simple yet effective tips which you could use for writing effective test cases. These tips will save you time and effort while optimizing the use of resources.
Let’s have a look a the tips to write better test case template.
Domain knowledge in information technology means deep knowledge of business and operational dynamics, the risks involved and the opportunities in that particular project. It is required to follow the best practices in the domain.
It is better to break the test case into a group of smaller ones if it has too many steps. It would be easier for the developer to backtrack and repeat the test steps if an error occurs somewhere in the test script. If not done than there are high chances that the developer will miss the bug.
Before starting on the test case it is suggested confirm all the assumptions that apply to the test and the preconditions that must be met before execution. There can be data dependency or the dependencies on the test environment or any other test cases.
Relevant artifacts should be attached to the test cases. This can be done using a test management tool. At the time of product delivery, It will help to track the changes in the application. I will be easy to understand the flow of the function when there is a change at any step which will not be easy to relate otherwise.
While writing a new test case a tester can share test data wherever applicable to be used for the Test Case within the test case description or add with the specific test case step. This will save time as there is no need to look for the test data anywhere else.
If the values are to be verified then testers can specify the value range or describe what values are to be tested for a particular field. Choose a few values from each class which will give good coverage for your test. It’s better not to mention the real test data value but the type of data which is required to run the test. In projects where multiple teams use the test data and it keeps changing, mentioning only the type of data will be a wise choice.
Use a test management tool to manages your test cases instead of using a spreadsheet. There are many test management tools that can be used to organize the test cases in one place which will increase the productivity of the team.
It is better to refer to the specification document. Assumptions about the features or functionalities can lead to disagreements between the client and the developers. This gap between the client’s requirement and the application under development will impact the business.
To write tests which are easy to understand, we have to stop coding on autopilot and pay attention to the naming conventions. It is required to name our test classes, fields of our test classes, test methods and the local variables while writing automated tests for our application.
It does not matter which team member wrote the test, others will know what feature is tested under what scenario without even looking at the test code.
If the testers miss a bug or write test cases that do not relate to the real world scenarios then it’s just a waste of resources and time. The goal is to meet the customer’s expectations and that can be attained only if the testers think from the users perspective.
It is important to write well-defined test case verification steps covering all the verification points for the feature under test. To make sure that the test Case covers all the verification points match your test case steps with the artifacts given for your project.
Do test automation when needed as it will reduce the manual effort and save a lot of time. The test scripts should be written in such a way that they can be used afterward for some other project.
Create test case template which could be re-used in the future by other teams. Also, before writing a new test case for your module, find out if there are similar test cases written already for some other project. Doing this you will avoid any redundancies in your test management tools. Call the existing test case in pre-conditions or at a specific design step if there is a need for a particular test case to execute some other test case.
Test cases should include all the features and functionalities mentioned in the software requirement. Requirement traceability matrix will help in finding the untested functions of the application.
A test run is a collection of test cases that testers should execute in a particular order. Test cases are often grouped in test runs. It’s preferred to put preconditions at the beginning of a test run rather than inserting them into each test case.
Actually, only a few of the test cases need preconditions, so the field is often left empty. A test management tool will help to customize your forms and create a test case template which will save your time and effort when writing test cases. Another thing to keep in mind is to avoid writing the same instructions several times by moving repeated preconditions to a test run.
The test cases should be well defined with comments where ever needed so that any other software tester can work on it in the future. Whatever project you work on, when designing test cases, you should always consider that the test cases will not always be executed by the one who designs them. Therefore, the tests should be easily understandable and to-the-point.
In a scenario where the person who wrote all those test cases leaves for some reason and you have a completely new testing team to work with, the entire effort spent during the design phase could go down the drain.
In the description, the testers need to mention all the details about what is going to be tested, what needs to be verified, the test environment and test data.
The information mentioned below should be there in a well-written test case description:
All the test cases should be updated with the new requirements so it’s easier to execute them in the future if there is a need. Even if some other tester wants to use the test case he/she wouldn’t have to go through the details of the script.
The tester needs to have good domain knowledge and should write presentable test cases from the users perspective. A good test case template will make it easier for testers to write good test cases. If there are only a few test steps, consider making a checklist instead and have a look at some relevant test case examples before working on your test case. A test case example will be helpful in creating test case templates too. A test management tool will definitely help in improving the way test cases are created and managed.
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In the year 2028, there will be around 7.8 Billion mobile users which accounts for 70% of the world population. More mobile users mean more apps and more competition and to lead the competition we need to make sure that our app is flawless. If nearly half of the bugs in your mobile app are discovered by the users, your app’s ratings are going to decline and so are the downloads. This is why the right choice of mobile app testing techniques must be followed in the decision-making process.
Today, the mobile app market is highly competitive. To be better every day and survive for long, the QA team has to follow a mix of plans that would be responsible for taking the right testing decisions. The testers have to formulate testing strategies to face every situation fearlessly and immaculately. Mobile apps have to be perfect before reaching to the end users so there have to be certain decisions to be taken regarding the testing plan. The following model of mobile app testing plans can be considered for better execution.
In the planning Stage, decisions like Selection of Device matrix, Test Infrastructure (In-house vs. Cloud, Simulator vs. Real device), Testing scope, Testing Tools, Automation (Framework/Tool) are taken. Since it is the first stage, it is the most important one as all the further stages would depend on these decisions. In the next stage which is execution and review, decisions regarding Test Case Design, Testing of user stories, testing types as per Sprint Objective, Progressive Automation, Regression Testing, Review and course correction are taken.
We are going to discuss the planning stage aspects more elaborately
It is an important factor, choosing the device as per your target audience’s behavior matters in decisions regarding resting. There are different approaches to the selection of the device matrix.
Determine the set of devices with your target operating System that will have the highest occurrence of accessing your application by using app purchase data and analytics. For Example- if you support both Android and iOS, and your application will be used across millions of Samsung, Google Nexus and Moto G devices but only thousands of iPhones, you prioritize testing on the Google Nexus and Moto G above the iPhone device. So, this test plan will consist of testing on devices which are prioritized by your market analysis.
This approach highlights the categorization of the devices based on certain mobile aspects which can be considered in formulating the testing strategy. The categorization goes as:
This is another element of the planning stage. This focuses on Strategizing on the Infrastructure components like hardware, software, and network which are an integral part of test infrastructure. It ensures that the applications are managed in a controlled way.
Choosing the right platform to test as per the testing needs is very important i.e whether to test on the Real device or an emulator or on the cloud
Testing on a real device is anytime more reliable than testing on a simulator. The results are accurate as real-time testing takes place on the device in a live environment. It carries its own disadvantages as it is a costly affair and not all the organizations are able to afford a complete real device laboratory of their own.
Pros:
Reliable- Testing on Real devices always gives you an accurate result
Live Environment- Testing on real devices enables you to test your application on the actual environment on which your target audience working on. You can test your application with different network technologies like HSPDA, UMTS, LTE, Wi-Fi, etc.
User experience- Testing on Real devices is the only way to test your Real-time User experience. It cannot be tested through Emulators or devices Available on Cloud.
Cons: Maintaining the matrix- You cannot maintain such a huge matrix of mobile devices in your own test lab. Maintenance- Maintaining these physical devices is a big challenge for organizations. Network providers- There are more than 400 network providers all over the world. Covering all these network providers in their own test lab is impossible. Locations- You cannot test how your application behaves when it is used in different locations.
The emulator is another option to test mobile apps. These are free, open source and can be easily connected with the IDE for testing. The emulator simulates the real device environment and certain types of testing can be run on it easily. However, we cannot say that the results of emulators are as good as those of real devices. It is slower and cannot test issues like network connection, overheating, battery behavior, etc.
Price- Mobile emulators are completely free and are provided as part of the SDK on every new OS release.
Fast- As Emulators are available on the local machine so they run faster and with less latency than Real devices connected to a local network or devices available on the cloud.
Cons:
The wrong impression- Even if you have executed all test cases on emulators, you cannot be 100 % sure it will actually work in the real environment.
Testing Gestures- Gestures like Pinching, Swipe or drag, long press using the mouse on simulators are different in using these gestures on real devices. We cannot test these functionalities on emulators. Can’t test Network Interoperability- With the help of Simulators you cannot test your application with different network technologies. Like HSPDA, UMTS, LTE, Wi-Fi, etc.
Mobile cloud testing can overcome the cost challenges like purchasing and maintaining mobile devices. It has all different sets of device types are available in the cloud to test, deploy and manage mobile applications. The tests run virtually with the benefit of choosing the right type device-OS combinations. Privacy, security, and dependency on the internet can be a challenge in this case but it has many benefits that can cater to different testing scenarios.
The organization can choose the right mix of above-mentioned platforms as every platform carries its own advantages and disadvantages. Sometimes a combination of real and emulators is preferred and sometimes all three can be considered as per the testing strategy.
Devices Availability- Availability of Devices and network providers is a big gain for cloud users. Maintenance- When you are using cloud services. Forget about maintenance. These providers take responsibility for maintaining these devices. Pay per use- You don’t need to buy a device. You only have to pay for the duration you use that device.
Parallel Execution- You can test your complete test suite on multiple devices.
Cons: Cost- Some providers are a bit costly
Nowadays, there are so many automation tools available in the market. Some are expensive and some are freely available in the market. Every tool has its own pros and cons. Choosing the right tool for testing would reduce the QA team effort providing seamless performance at the same time. We will discuss the best mobile app testing automation tools for iOS and Android platforms in 2018.
1. Appium: It is one of the preferred MAT tools by testers. It is open source and free tool available for Android and iOS. It automates any mobile app across many languages and testing frameworks like TestNG. It supports programming languages like Java, C# and other Webdriver languages. It provides access to complete back end APIs and database of the test codes. Top Features: -Appium supports Safari on Ios and Other browsers on Android -Many Webdriver compatible languages can be used such as Java, Objective-C, JavaScript to write test cases -Support languages like Ruby, Java, PHP, Node, Python.
2. Robotium: It is a free Android UI testing tool. It supports in writing powerful black box test cases for Android Applications. It supports Android version 1.6 and above. The tests are written in Java language and basically, Robotium contains a library of unit tests. Apart from this, Robotium takes a little more effort in preparing tests, one must work with program source code to automate tests. Robotium does not have play record and screenshot function.
Top Features: -The tests can be created with minimum knowledge of the project -Numerous android exercises can be executed simultaneously. -Syncronises easily with Ant or Maven to run tests.
3. Calabash: It is an open source MAT tool allowing testers to write and execute tests for Android and iOS. Its libraries enable the test codes to interact with native and hybrid apps. It supports cucumber framework which makes it understandable to non-tech staff. It can be configured for Android and Ios devices. It works well with languages like Ruby, Java, .NET, Flex and many others. It runs automated functional testing for Android and ios. It is a framework that is maintained by Xamarin and Calabash.
4. Espresso: It is a mobile app testing automation tool for Android. It allows writing precise and reliable Android UI tests. It is a tool targeted for developers who believer automated testing is an important part of CI CD process. Espresso framework is provided by the Android X Test and it provides APIs for writing UI tests to simulate user interactions on the target app. Espresso tests can run on Android 2.33 and above. Provides automatic sync of test actions with the app UI.
5. Selendroid: An open source automation framework which drives off the UI of Android native, hybrid and mobile web application. A powerful testing tool that can be used on emulators and real devices. And because it still reuses the existing infrastructure for web, you can write tests using the Selenium 2 client APIs.
6. Frank: Is an open source automation testing tool for the only iOS with combined features of cucumber and JSON. The app code needs not to be modified in this tool. It includes Symboite live app inspector tool and allows to write structured acceptance tests. It is tough to use directly on the device but is flexible for web and native apps. It can run test both on simulator and device. It shows the app in action by showing its recorded video of test runs.
Above are a few promising, popular and most commonly used and mobile app testing automation tools. Choice of tools certainly resolves many testing-related problems faster and efficiently. Implementing these tools requires skill and experience and so an organization needs to have a proper testing team in place to make all of this possible.
We are moving toward a future where everything is going to be autonomous, fast and highly efficient. To match the pace of this fast-moving ecosystem, application delivery times will have to be accelerated, but not at the cost of quality. Achieving quality at speed is imperative and therefore quality assurance gets a lot of attention. To fulfill the demands for exceptional quality and faster time to market, automation testing will assume priority. It is becoming necessary for micro, small, and medium-sized enterprises (SMEs) to automate their testing processes. But the most crucial aspect is to choose the right test automation framework. So let’s understand what a test automation framework is.
A Mobile Testing automation framework is the scaffolding that is laid to provide an execution environment for the automation test scripts. The framework provides the user with various benefits that help them to develop, execute and report the automation test scripts efficiently. It is more like a system that was created specifically to automate our tests. In a very simple language, we can say that a framework is a constructive blend of various guidelines, coding standards, concepts, processes, practices, project hierarchies, modularity, reporting mechanism, test data injections etc. to pillar automation testing. Thus, the user can follow these guidelines while automating applications to take advantage of various productive results.
The advantages can be in different forms like the ease of scripting, scalability, modularity, understandability, process definition, re-usability, cost, maintenance etc. Thus, to be able to grab these benefits, developers are advised to use one or more of the Test Automation Framework. Moreover, the need of a single and standard Test Automation Framework arises when you have a bunch of developers working on the different modules of the same application and when we want to avoid situations where each of the developers implements his/her approach towards automation. So let’s have a look at different types of test automation frameworks.
Now that we have a basic idea about Automation Frameworks, let’s check out the various types of Test Automation Frameworks available in the marketplace. There is a divergent range of Automation Frameworks available nowadays. These frameworks may differ from each other based on their support to different key factors to do automation like reusability, ease of maintenance etc.
Types of Mobile testing automation frameworks:
Module-Based Testing Framework, as the name implies, depends on a number of modules to function. In order to produce the greatest results from the automation test, you would need to develop unique scripts for each module and ensure that they work together. Changes to the application’s functionality won’t have an impact on the modules. The scripts are safe unless they are manually changed. Given that a high level of modularization is produced by merging multiple modules, this provides a cost-effective management approach. Productivity is still at its highest level. But, if necessary, it can take a lot of time and effort to make modifications to the test data individually.
Based on the modular foundation, the library architecture framework for automated testing offers several extra advantages. Instead of separating the programme under test into the many scripts that must be executed, related jobs inside the scripts are found and afterwards grouped by function, allowing the application to be eventually divided up into common goals. The test scripts can access this library of functions anytime they are required.
A number of tests must be run while testing an automation framework before a successful result can be determined. In these situations, you might need to alter the test results to try and draw a different conclusion. You can keep the test data on an external drive and access it later for adding a new script to the test case thanks to the Data-Driven Testing Framework.
The keyword-driven testing framework, which is frequently regarded as an extension of the data-driven testing framework, collects your test data from an external source and securely preserves the set of codes. These codes, which are also known as “keywords,” can be used to change the test script and draw additional conclusions from the test framework. Also, these keywords effectively determine what tasks each programme performs.
To maximize the effectiveness of the aforementioned frameworks, the hybrid testing framework combines the data-driven and keyword-driven frameworks. It provides more room for more efficiency and success, making it the ideal automation foundation.
The goal of the Behavior Driven Development framework is to build a platform that encourages active participation from all users, including developers, testers, business analysts, etc. Also, it improves cooperation on your project between the developers and testers. For this behavior-driven testing, test specifications can be written in plain, non-technical language.
Apart from the minimal manual intervention required in automation testing, there are many advantages of using a test automation framework. Some of them are listed below:
1. Robot Framework Robot Framework is the best choice if you want to use a python test automation framework for your test automation efforts. The Robot Framework is Python-based, but you can also use Jython(Java) or IronPython(.NET). The Robot Framework uses a keyword-driven approach to make tests easy to create. Robot Framework can also test MongoDB, FTP, Android, Appium and more. It has many test libraries including Selenium WebDriver library and other useful tools. It has a lot of API’s to help make it as extensible as possible. The keyword approach used by Robot Framework is great for testers who are already familiar with other vendor-based, keyword-driven test tools, making the transition to open source much easier for them.
2. WebdriverIO WebdriverIO is an automation test framework based in Node.js. It has an integrated test runner and you can run automation tests for web applications as well as native mobile apps. Also, it can run both on the WebDriver protocol and Chrome Devtools protocol, making it efficient for both Selenium Webdriver based cross-browser testing or Chromium based automation. As WebDriverIO is open source, you get a bunch of plugins for your automation needs. ‘Wdio setup wizard’ makes the setup simple and easy.
3. Citrus Citrus is an open-source framework with which you can automate integration tests for any messaging protocol or data format. For any kind of messaging transport such as REST, HTTP, SOAP, or JMS, Citrus framework will be suited for test messaging integration. If you need to interact with a user interface and then verify a back-end process, you can integrate Citrus with Selenium. For instance, if you have to click on a “send email” button and verify on the back end that the email was received, Citrus can receive this email or the JMS communication triggered by the UI, and verify the back-end results, all in one test.
4. Cypress Cypress is a developer-centric test automation framework that makes test-driven development (TDD) a reality for developers. Its design principle was to be able to package and bundle everything together to make the entire end-to-end testing experience pleasant and simple. Cypress has a different architecture than Selenium; while Selenium WebDriver runs remotely outside the browser, Cypress runs inside of it. This approach helps in understanding everything that happens inside and outside the browser to deliver more consistent results. It does not require you to deal with object serialization or over-the-wire protocols while giving you native access to every object. Cypress can synchronously notify you of every single thing that happens inside the browser as you’re pulling your app into it, so that you have native access to every DOM element. It also makes it easy to simply drop a debugger into your application, which in turn makes it easier to use the developer tools.
5. Selenium One of the most popular open source test automation frameworks for web apps. Selenium also serves as a base for a lot of other testing tools as it has cross-platform and cross-browser functionality. Selenium supports a wide range of programming languages such as Java, C#, PHP, Python, Ruby, etc. It is easy to maintain as it has one of the largest online support networks. Selenium is highly extendable through a wide range of libraries and APIs to meet everyone’s needs and requirements. Selenium is preferred by testers as it is possible to write more advanced test scripts to meet various levels of complexity. It provides a playback tool for test authoring without the need to learn a specific scripting language.
6. Cucumber It is a cross platform behavior driven development (BDD) tool which is used to write acceptance tests for web applications. Cucumber is quick and easy to set up an execution and allows reusing code in the tests. It supports languages like Python, PHP, Perl, .NET, Scala, Groovy, etc. Automation of functional validation in easily readable and understandable format. One good feature is that both specification and test documentation are uploaded in a single up-to-date document. Cucumber makes it easy for the business stakeholders, who are not familiar with testing, as they can easily read the code as test reports are written in business readable English. The code can be used together with other frameworks like Selenium, Watir, Capybara, etc.
7. Gauge It is an open source tool agnostic test automation framework for Mac, Linux and Windows. People who work on TDD and BDD will appreciate Gauge’s focus on creating living/executable documentation. Specs – the Gauge automation tests are written using a markdown language with C#, Java and Ruby within your existing IDEs like Visual Studio and Eclipse. Gauge’s functionality can also be extended with its support of plugins. It was developed as a BYOT (Bring Your Own Tool) framework. So you can use Selenium or you can use anything else for driving your tests UI or API tests. If you want a readable non-BDD approach to automation, you should try Gauge.
8. Serenity If you are looking for a Java-based framework that integrates with behavior-driven development (BDD) tools such as Cucumber and JBehave, Serenity might be the tool for you. It’s designed to make writing automated acceptance and regression tests easier. It also lets you keep your test scenarios at a high level while accommodating lower-level implementation details in your reports.
Serenity acts as a wrapper on top of Selenium WebDriver and BDD tools. It abstracts away much of the boilerplate code you sometimes need to write to get started which makes writing BDD and Selenium tests easier. Serenity also offers plenty of built-in functionality, such as handling running tests in parallel, WebDriver management, taking screenshots, managing state between steps, facilitating Jira integration, all without having to write a single line of code.
9. Carina Carina is built using popular open-source solutions like Appium, TestNG and Selenium, which reduces dependence on a specific technology stack. You can test mobile applications (native, web, hybrid), WEB applications, REST services, and databases. Carina framework supports different types of databases like MySQL, SQL Server, Oracle, PostgreSQL, providing amazing experience of DAO layer implementation using MyBatis ORM framework. It supports all popular browsers and mobile devices and it reuses test automation code between IOS/Android up to 80%. API testing is based on the Freemarker template engine and it provides great flexibility in generating REST requests. Carina is cross-platform and tests may be easily executed both on Unix or Windows OS.
10. EarlGray Developers often face difficulty with some of the existing test automation framework in synchronization of the app and the instrumentation. Also, executing tests on apps as synchronized and advanced only when UI elements are visible on the screen has caused issues for many developers. Google EarlGrey has built-in synchronization that makes test scripts wait for UI events to occur before the script tries to interact with the UI of the app. This type of implementation makes the test script concise as all steps of the test script shows how the test will proceed and UI gets synchronized with it. One more key aspect of EarlGrey is that all actions on UI elements happen only on visible elements. This provides a fast and robust approach to ensure UI testing goes through as clicks, gestures and other user interactions do not get done if the UI element is not fully shown.
This list of top tools here represents the best tools that are mature, popular, and provide test automation capabilities using AI/ML to address the challenges that organizations are now facing to deliver Quality at Speed. This list also includes the tools that provide API and services testing which is essential for successful DevOps transformation. The emerging technologies like AI, codeless, big data and IoT testing, are making test automation more efficient while creating opportunities for the existing tools and new players to assert value to the testing communities.
The choice of automation tools should not only meet your current needs but should also focus on potential trends and improvements. An efficient test automation tool should support basic optimization, data generation, smarter solutions, and analytics. As of now, the level of test automation in organizations is low at between 14% and 18%. But organizations are working towards increasing the automation coverage upto 80%. API and services testing is also a trend that should see further development in the future.
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