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Mobile app automation testing has become essential for ensuring the quality and performance of apps in today’s competitive market. With shorter release cycles and tighter budgets, choosing the right automation testing framework can significantly impact your app’s success. While there are many automation frameworks available, Appium and Espresso have emerged as two of the most widely used frameworks for mobile app testing.
This blog provides a detailed comparison of Appium vs Espresso, highlighting their strengths, weaknesses, and ideal use cases to help you decide which framework is right for your needs.
Mobile app automation testing has evolved as a crucial aspect of the mobile app development process to help deliver better quality solutions, under controlled time cycles and cost schedules. But for delivering bug-free app, choosing the best suitable automation testing framework for your app is very important. There are many automation testing frameworks available in the market with exceptional capacities. This blog is all about Appium vs Espresso and we will analyze which of these two most widely used Automation testing frameworks is preferable for your app testing.
Espresso was not preferred because of its flakiness and instability issues. But, from the time Google has brought Android Test Orchestrator, a Gradle test option, instability and unreliability of Android Espresso tests have vanished. This, in turn, is creating a serious problem for the most popular automation framework Appium.
Let’s find out in this blog if Espresso now comes with a power to kill Appium or Appium can hold its stand in this fiercely competitive market.
Appium is an open-source, cross-platform mobile automation testing framework that supports the testing of native, hybrid, and web apps. It enables testing on real devices, emulators, and simulators, making it a versatile choice for mobile app testing. Appium’s architecture uses the Selenium WebDriver protocol, which allows cross-platform compatibility, enabling the same test scripts to work for both Android and iOS apps.
Appium enables testers to run automation tests without modifying or recompiling the app code, making it highly flexible for both native and cross-platform apps.
3. Automates Various Types of Mobile Apps
Whether it’s a web, hybrid, or native app, Appium supports automation across all app types using the same framework.
4. Supports Real Devices, Emulators, and Simulators
Appium enables testers to run tests on real devices for accurate usability testing while also supporting emulators and simulators for faster test execution.
5. Record and Playback Tool for Quick Test Creation
Appium’s inspector allows testers to record app behavior and generate scripts in multiple programming languages such as Java, Python, Ruby, and C#.
6. Cross-Platform Compatibility
Appium enables you to run the same test script on both Android and iOS platforms, reducing the effort required for cross-platform app testing.
7. Supports Multiple Programming Languages
Appium integrates with WebDriver-compatible languages, including Java, JavaScript, Python, PHP, Ruby, C#, and Objective-C, allowing testers to write scripts in their preferred language.
Common mobile gestures, such as double-tap, may not be natively supported in Appium’s Java-client libraries, requiring workarounds.
2. No Support for Concurrent iOS Simulator Testing
Appium does not allow running multiple test scripts on iOS simulators concurrently, which can slow down large-scale iOS testing.
3. Limited Image Recognition Capability
Appium struggles with image-based testing as it cannot recognize images automatically and requires screen coordinates for locating visual elements.
4. No Support for Older Android Versions
Appium only supports Android 4.2 and above, making it difficult to test apps targeting older Android APIs.
Espresso is Google’s UI testing framework for Android apps. It provides fast, reliable UI testing by synchronizing test actions with the app’s user interface and ensuring that the app’s activities have completed before the test starts.
With the introduction of Android Test Orchestrator, Google has addressed common issues like flaky tests and shared states, making Espresso more stable and reliable.
The Android Test Orchestrator runs each test in its own sandboxed environment, ensuring minimal shared state and isolating crashes, leading to more reliable test results.
3. Less Flakiness
Espresso’s built-in synchronization mechanism ensures that test actions are executed only when the app’s UI is idle, reducing flakiness caused by asynchronous operations.
4. Developer-Friendly Test Automation
Since Espresso is based on Java and JUnit, Android developers can quickly adopt it without additional learning curves or external dependencies.
5. Fast Feedback Loop
Unlike Appium, Espresso runs alongside the app without requiring a server, resulting in faster test execution and immediate feedback.
6. Simple Test Suite Management
Espresso allows developers to package their tests as standalone APKs, which can be installed alongside the app and executed easily.
1.Requires Access to the App’s Source Code
Espresso requires access to the app’s source code, limiting its use for black-box testing or when working with third-party apps.
2. Narrow Focus (Android-Only)
Espresso is designed exclusively for Android, so separate frameworks (like XCTest) are required for iOS testing, resulting in increased effort for cross-platform apps.
3. Requires Emulator Experience
Running Espresso tests requires familiarity with launching and managing Android apps on emulators, which may add complexity for QA teams unfamiliar with Android development.
Appium vs Espresso: Key Differences
Criteria
Appium
Espresso
Platform Support
Android and iOS
Android only
Source Code Access
Not required
Required
Test Type
Black-box and white-box testing
Primarily white-box testing
Programming Language
Supports multiple languages (Java, Python, C#, etc.)
Java and Kotlin (via JUnit)
Test Execution
Requires Appium server
Runs directly in the app process
Cross-Platform
Yes
No
Test Reliability
May face flakiness due to external dependencies
High reliability with built-in synchronization
Integration
Requires WebDriver integration for advanced features
Fully integrated with Android Studio
Both Appium and Espresso offer powerful capabilities for mobile app testing, but the right choice depends on your app’s requirements. If you need a cross-platform solution that supports both Android and iOS, Appium is the better option. However, if you’re focused solely on Android and need a reliable, fast UI testing framework, Espresso is ideal.
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Automation testing has become a cornerstone of modern QA processes, replacing repetitive manual testing with efficient, consistent execution. This approach saves time, enhances test coverage, and reduces the likelihood of errors. It is especially impactful for tasks like regression testing, where automation significantly boosts efficiency. Relying solely on manual testing wastes resources and increases the risk of human error. Automation testing mitigates these risks by executing predefined test cases consistently and accurately.
Choosing the right automation testing tool is the first step toward ensuring the success of your testing strategy. This guide will walk you through the key factors to consider when selecting the ideal tool for your needs.
Automation testing tools come in various types, each suited to specific use cases. Here’s a breakdown:
Overview: This method records user interactions and converts them into scripts for automated playback.
Advantages:
· Beginner-friendly; minimal programming knowledge required.
· Quick setup for straightforward scenarios.
· Effective for regression testing with static UI designs.
Challenges:
· Limited flexibility for dynamic UI elements.
· High maintenance as scripts require updates after UI changes.
Examples: Selenium IDE, Pcloudy
Overview: This approach uses screen coordinates (x/y axes) to automate interactions, relying on physical locations rather than logical properties.
· Works well for legacy systems with minimal element identifiers.
· Suitable for environments with limited development support.
· Fragile; even minor layout changes can break scripts.
· Incompatible with responsive designs.
Examples: Found in older or custom-built tools.
Overview: This method uses element properties (e.g., XPath, XML, CSS) to identify UI components.
· Robust and reliable for modern apps.
· Resilient to minor UI changes.
· Supports complex test scenarios.
· Requires technical expertise.
· May be challenging in poorly coded apps with undefined element properties.
Examples: Selenium, Appium, UFT.
Overview: OCR-based tools use image-based algorithms to recognize and interact with text on the UI.
· Ideal for dynamic environments or text-heavy applications.
· Effective for automating forms and document-heavy apps.
· Prone to errors in low-resolution or non-standard font environments.
· Slower due to image processing.
Examples: ABBYY FineReader, Pcloudy OCR Automation Feature.
Overview: These tools rely on screenshots of UI elements, matching them during test execution.
· Suitable for graphical or non-standard interfaces.
· Works where other methods fail.
· Sensitive to changes in resolution, themes, or colors.
· Requires frequent updates to reference images.
Examples: Sikuli, Eggplant Functional.
Overview: Combines multiple recognition methods to ensure flexibility and robustness.
· Versatile testing capabilities.
· More resilient and stable.
· Higher costs and steeper learning curves.
Examples: Pcloudy, integrating native recognition, OCR, and image recognition.
Your choice of tool should align with the platforms your application targets. For instance:
Framework integration is another key consideration. Tools like Appium and Selenium work seamlessly with open-source frameworks, enhancing collaboration, object identification, bug logging, and reporting.
Ease of adoption can be measured on the basis of the skills required to use the tool and the learning curve. If there are resources available easily on the internet to learn the functioning of the tool then it is a plus point. Also, the support should be good and it’s an advantage if there is an active community that will give a rough idea about the complexities of the tool. We have observed that the installation process is also lengthy for some tools and frameworks. But overall the team should be able to use the tool easily with the skill set or the experience they have.
Most of the automation testing tools provide flexible scripting options. It allows testing teams to write test scripts in their preferred languages. A good test automation tool helps in getting better reusability of test components and provides flexibility in scripts that can be reused across projects. Scripting time with object identification, speed of script execution, and support for CI/CD tools like Jenkins, usually these attributes are considered before selecting the tool.
If the testing team is using a test case or a bug management tool then the team would prefer an automation tool that can be easily integrated into those tools. It helps in managing the app development lifecycle properly.
The keyword-driven or data-driven automation framework should be easily integrated into any data source. It is convenient if the tool provides connectivity with different data sources easily.
Analytical reports form the backbone of test automation as it provides insights into the success of the process. Automation tools must provide customizable dashboards to view different types of reports shared across various teams.
Real-time reports traceability and sharing ensure feature validation and efficient test coverage. Quality metrics such as injection rate, defect density, and test execution status allow you to maintain quality at every stage of continuous testing. It’s convenient to analyze results to identify bugs, patterns, and do a root cause analysis with a good automation tool.
It’s better to go for open-source tools but not every open-source automation tool has all the attributes that you might be looking for. Even if you opt for the proprietary licensed tools, you need to figure out how much you need to spend on the maintenance.
Some companies offer live support and training for premium plans. So you might want to upgrade to avail of these services. There is also something called runtime license if you just want to execute the automation on different machines. Apart from that, there are options for a node-locked license for a single machine and a concurrent floating license to use the tool on multiple systems.
If you are still confused and want to further simplify the tool selecting process, then use a tool comparison matrix. Jot down your preferred 2,3 or even 5 tools and then rate them on the basis of all the factors that we have discussed earlier in this blog. This way it will be easier to make a decision on the basis of your requirements.
As far as mobile test automation tools are concerned, device coverage holds the key. It is recommended to use a cloud-based testing platform to run your automated test on multiple devices. Automation is the soul of any CI/CD pipeline and for the successful implementation of DevOps, it is crucial to choose the right automation testing tools.
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 competitive digital landscape, businesses are under constant pressure to accelerate their software development cycles and enhance digital capabilities. Although automation has become a staple in the software development lexicon, a surprising number of organizations—only 30% according to recent studies—have fully adopted automation testing. This gap highlights a significant opportunity: many companies invest heavily in digital transformations but fail to integrate comprehensive testing strategies, limiting their potential gains.
Continuous testing stands out as a critical methodology designed to align with the rapid pace of modern development cycles. This approach not only helps in detecting errors early in the development process but also ensures that software products consistently meet quality standards before reaching consumers.
Continuous testing is an advanced software testing strategy that involves evaluating software quality at every stage of the software development lifecycle (SDLC). This is done to identify defects early, thereby enhancing the quality of the final product while ensuring business continuity. It is a vital component of DevOps and Agile practices, integrating seamlessly with these methodologies to support continuous integration (CI) and continuous delivery (CD).
An effective continuous testing strategy is pivotal for organizations aiming to maintain robust software delivery pipelines. Here are detailed strategies and practices to enhance the efficacy of continuous testing frameworks.
Before exploring optimization strategies, it’s crucial to address the common obstacles that enterprises face: As organizations increasingly seek to accelerate their software deployment cycles, many grapple with significant challenges that hinder the effective implementation of a continuous testing strategy. Here are some key challenges:
These challenges underscore the necessity of a well-thought-out continuous testing strategy that is adaptable, scalable, and efficient to support the dynamic nature of modern software development.
Test automation strategy is the backbone of the final product that a business delivers. It should be strong and flexible enough to bear the impact of any change and every variable of the testing process. Let’s discuss how optimizing continuous delivery testing strategy helps improving the testing process and to increase the software quality:
Research indicates that many organizations tend to prioritize specific testing approaches—some focus on API integration and UI testing, while others may address these areas separately. However, a critical gap often exists in their lack of a detailed, automated continuous integration testing strategy that encompasses all these testing types. While selecting a particular testing method may be appropriate for certain business scenarios, it’s crucial for companies to develop a versatile testing plan. This plan should be capable of incorporating any testing type as needed. Understanding the distinctions and applications of continuous testing versus test automation is essential, given the varying scales and needs of businesses.
Incorporating unreliable and overly complex test cases early in the development process can result in significant waste of time and resources, as QA teams are forced to engage in ineffective analysis of each code commit. To avoid this, it’s advisable for QA teams to start with a minimal set of test suites. This approach helps mitigate major risks while allowing for incremental adjustments based on the impact observed. Over time, the focus should be on gradually integrating more robust and stable test cases. In a DevOps environment, the quality of test cases is far more critical than the quantity executed.
In building a comprehensive continuous testing strategy, choosing the right test automation tool is not just a requirement—it’s a cornerstone for achieving complete stability in your development process. It’s essential to select a tool that not only fits the technical requirements of your projects but also enhances operational efficiencies.
One standout category in the realm of test automation tools is that which offers codeless automation alongside self-healing capabilities. Codeless test automation tools are designed to enable users to create automated tests without writing extensive lines of code. This approach significantly lowers the barrier to entry for team members who may not have traditional programming skills but are nevertheless integral to the testing process. It allows subject matter experts, business analysts, and QA professionals to directly contribute to test automation efforts.
In a continuous testing environment, where quick iterations and frequent releases are common, the agility offered by a codeless, self-healing test automation tool becomes even more valuable. By automating tests without requiring extensive coding skills, teams can rapidly create and adapt tests to evolving application features and requirements. The self-healing aspect ensures that these tests remain valid and reliable over time, even as the application undergoes changes, thereby supporting a truly continuous approach to testing and development.
Moreover, such tools can significantly reduce time and maintenance costs associated with the lifecycle of automated tests. They enhance the reusability of test scripts and ensure a higher return on investment by minimizing the need for frequent manual updates and intervention.
By choosing a codeless automation tool with self-healing features, organizations can enhance their testing capabilities, accelerate their time to market, and ensure that their testing strategies can adapt to the dynamic nature of modern software environments.
For complex integrated applications, modular testing offers an effective strategy to simplify and manage functionality. By decomposing the application into distinct modules, teams can create a clear roadmap that aligns testing processes with different workflows. Modular testing facilitates the organization and restructuring of tests by separating test data, test flows, and element locator mappings. This approach not only streamlines the testing process but also enhances the adaptability and maintainability of the test suites.
Automated screenshots are invaluable for diagnosing the reasons behind test failures. They provide a visual reference that can be crucial for in-depth analysis of issues encountered during test execution. A robust automation tool should be capable of capturing screenshots at key interaction points automatically. However, not all tools support this feature. If your current test automation solution lacks this functionality, it may be worthwhile to consider switching to another platform that does, to fully benefit from the diagnostic advantages of automated screenshots.
With the rise of continuous testing, automation, and DevOps, alongside the demand for faster delivery, the standards for quality software have significantly increased. Companies are striving to stay competitive by refining their testing and development strategies, all while keeping costs low. Managing test execution costs is essential. As testing scales up, the use of cloud resources becomes necessary, which can be costly. An effective strategy would be to differentiate between high and low-level testing requirements—conduct more complex integration and compatibility tests on the cloud, and run basic tests on-premise. This approach helps maintain a cost balance while maximizing automation ROI.
When development and operations teams collaborate, numerous operational challenges emerge. Developers aim to deploy updates swiftly, while testers focus on ensuring the reliability of service delivery. Bridging this gap requires continuous testing and integration within DevOps frameworks. To effectively manage these challenges, investing in system monitoring tools is crucial. These tools help identify the root causes of discrepancies and failures, enhancing overall efficiency.
Outsourcing the QA process provides additional support, giving businesses a competitive advantage in delivering high-quality services. In the realm of continuous testing, outsourcing offers a significant boost by providing access to specialized areas such as impact analysis, performance, and security testing. This focused approach injects vital energy into specific phases of the development lifecycle, creating a mutually beneficial scenario for both developers and testers.
Continuous Testing and Delivery is not a luxury but a necessity in today’s era. A well designed continuous testing strategy is the foundation of continuous testing and quality service delivery. Although the journey is full of challenges if planned meticulously, the businesses would be able to streamline and reap the maximum benefits of test automation and continuous testing.
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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Automation testing has transformed how software is developed, tested, and delivered. By leveraging tools and frameworks to execute predefined test cases, automation testing offers speed, precision, and scalability that manual testing cannot match. Below, we delve into the advantages of automation testing, highlighting how it addresses key challenges and accelerates software development lifecycles.
Automation testing enables rapid feedback during various stages of the software development lifecycle. It enhances communication between developers, testers, product owners, and designers, ensuring issues are identified and resolved promptly.
Benefits:
Writing test cases manually is time-consuming, particularly for repetitive tasks like regression testing. Automation testing eliminates the need for repetitive manual efforts, reducing the overall testing time.
Automation testing allows bugs to be identified during the initial stages of development. This proactive approach prevents issues from escalating into larger problems.
Test scripts in automation can be reused across multiple projects with minimal modifications. This reusability is particularly beneficial for applications with frequent updates or releases.
Automated testing help test engineers to run their tests 24/7. If the test engineer has to leave early for the day, he can easily schedule the tests and leave the office. The test results will be ready by the time he logs in again next morning.
Automation testing cuts down complexities with its distributed test execution feature. It helps the testers to run a test script on more than one computer or shared network or servers simultaneously. So, only an automation testing tool is the requirement rather than multiple tools.
Automation testing gives us the benefit of tracking each test script. All the test scripts executed will be visible in visual logs. The reports generated can evidently show the number of test scripts already executed, scheduled, their reported bugs or issues and the ways in which they have been fixed.
Automated testing offers an unmatched and huge testing capability. The mobile app needs to be tested on multiple devices, OS versions, screen sizes etc. which can be efficiently done through automated testing and not by manual testing. In fact, it is almost impossible to get perfect results through manual testing.
Test automation can easily execute thousands of different complex test cases during every test run providing coverage that is impossible with manual tests. It can only be possible through automated testing as it can run test scripts on multiple computers with varied configurations. It can look inside an application and see memory contents, data tables, file contents, and internal program states to determine if the app is functioning as expected.
Automation testing significantly reduces dependency on manual testers for repetitive and time–consuming tasks. This allows QA teams to focus on higher-value activities.
We have been saying this time and again that automation testing overcomes the shortcomings of manual testing. It has improved the accuracy to a great deal by giving error-free results unlike manual testing where testing is error-prone, delays the delivery and increases the cost. It is especially a boon in stress testing where getting error free results in manual testing is almost impossible.
One of the most important advantages of automation testing is the return on investment to the organization. Every enterprise analyses the return it would get out of its investment and then would go for creating a test automation framework. Automated testing offers immense returns in terms of faster testing, error-free results, less manual effort. If the enterprise has automated testing tool, then the testing would be more efficient and accurate and easy.
You can run your tests on more than 500 devices in automation testing which is impossible in manual testing.
One of the most important business advantages of automation testing is the return on investment to the organization. There are many advantages of automation testing tools as they are a crucial component in the DevOps toolchain. The importance of automation testing comes into picture when you have to run the test cases with different data and conditions several times.
Automation testing not only saves time and improves accuracy but also adds significant value to all stakeholders involved in the app development lifecycle. Despite its many benefits, some organizations hesitate to adopt automation due to initial configuration costs. However, with Agile and DevOps methodologies becoming the industry norm, automating testing processes is no longer optional—it’s a necessity.
By investing in renowned automation testing tools and frameworks, organizations can ensure faster releases, error-free applications, and satisfied customers. Whether you’re new to automation or scaling your testing efforts, platforms like Pcloudy can help you achieve unparalleled efficiency and coverage.
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.
It is necessary to check cross-browser compatibility to ensure that the app is working fine on all the web browsers. Sometimes when you open an app on a web browser it might not look or feel convenient and there might be some issues like image/test overlapping, navigation, alignment, etc. These issues degrade the user experience which will eventually lead to low traffic and existing user attrition. This is why cross-browser testing is an integral part of the QA process and should not be avoided.
Automation has reduced the time and effort put into cross-browser testing by 80 percent. The only human work goes into writing the initial test script and selecting the tool. Let’s look at the reasons why we should automate cross-browser testing.
Run Multiple tests simultaneously: When it comes to regression testing and running multiple tests for an app, automated testing saves the day. So if your app is already in the market and you launch a new version then automated cross-browser testing helps you to deliver faster. When a new feature is to be launched in the app and the build is sent to the testing team, they will take some weeks to perform all types of testing. This time can be reduced to a few hours using Automation testing tools.
Improved test accuracy: Even the experienced testers can make an error while testing the app manually. Although in Automation testing the accuracy is very high and the detailed reports are recorded. Testers can review the testing process and create new Automated test with the help of those reports.
Save Time and Money: Cross-browser testing require repetitive tests and so it can be a boring and time-consuming process. These repetitive tests can be automated to save time, effort and return on investment. You just need to make sure that everything is included in the test script to avoid gray areas in the app functioning.
Better Test Coverage: The time taken to perform any web app testing is dependent on the type of feature or functionality you have to test. The length of the test affects the cross-browser testing process. For example, end to end testing can be difficult if done manually. It will take much time and effort to do so. This why automation testing can be used if you have to run the test on multiple devices with multiple browser-OS combinations.
There are many types of devices in the market with different screen sizes, OS versions, Browsers, etc. To create the desired test environment, you will have to have all these combinations and you will have to set up a device lab. This will take huge investments and efforts to maintain the lab. Also, there is an issue of geographically distributed teams accessing the devices. Apart from that, you will have minimum flexibility as scaling up or down will be difficult.
Advantages of Cloud-Based Cross Browser Testing
There are many Cloud-based cross-browser testing tools in the market which will help you achieve your testing goal without investing a lot. This is one of the reasons why cloud-based cross-browser testing is better than setting up a local test environment. Let’s have a look at some other advantages which will give you a reason to opt for cloud-based option.
Multiple Test Environment Support: Heterogeneity in the operating system versions, device screen sizes, browser versions makes it necessary to perform tests on many combinations of device/OS/browser. This means a lot of effort will be put in to test the functions of an app on multiple devices. This could be avoided by testing the app on a cloud-based device platform.
In the cloud-based testing platform, you will be able to select the devices of your choice and perform parallel testing on multiple devices without buying one. This will save you money and effort to put up a device lab. While running the test in parallel on multiple devices with different OS browser combination will save time, it will also increase the accuracy significantly as compared to testing the app feature manually.
All time access to resources: The testing team can access the tool at any time by just logging into the tool and selecting the devices according to the market research report on popular devices in the region. Testing can be performed at any time which means there is no foundation and this comes in handy when the deadline is near. Having all time access to the device cloud will contribute to continuous testing and ensure faster deployment.
Scalability: While handling multiple projects the team might have needed many devices at times and very few on some occasions. This means that most of the devices in your device lab might rarely be used and sometimes you might have to buy more to add in the environment. This improper management of resources can be avoided by using Cloud-based device platform. Here you can select the devices which you actually need to perform the cross-browser testing and as all the devices are virtual, there is no worry of managing the extra devices.
Collaboration: There are tools to communicate and collaborate with the team which impacts on your productivity in a good way. Test reports can be generated which are elaborate and provides all the information about the health of the app. These reports can be shared with the team online to analyze and resolve the issue.
Initial time and cost: To set up an actual device lab you will require dedicated cloud/network expertise and suitable infrastructure. On the contrary, if you use cloud-based platform for cross-browser testing then you don’t have to worry about the infrastructure and initial setup cost. Also, you will save a lot on maintenance cost and everything is preconfigured.
Comprehensive testing: To perform thorough cross-browser testing, you need a permutation and combination of mobile devices with different screen size, OS, browser, other features relevant to the app function. This will make a big hole in your pocket if you wish to buy that many devices. This is why cloud-based testing platforms are the best option.
There are three types of cross-browser functional testing, multi-browser testing, multi-version testing, and concurrent testing. Let’s get familiar with all three of them.
Multi-Browser Testing: The application under test is opened on different browsers like Chrome, Safari, Opera, UC Browser, etc to check if the app works consistently across all the browsers. The app feature can be tested on multiple devices of different configurations and browser combinations.
Multi-Version Testing: In this type of testing the AUT is tested with different versions of any browser to check if the functioning is smooth. So if your app supports chrome version 40.0.2214, then the app must be tested on all the versions of chrome after 40 to check the functionality. One tester can perform the task and multiple devices will be used to perform the testing.
Concurrent Testing: In this, the application under test is checked simultaneously on different web browsers. There are four variations of this testing – single browser distributed concurrent testing, multi-browser distributed concurrent testing, Multi-browser concurrent testing, and single browser and single browser concurrent testing.
Cross browser testing combined with cross-platform testing will ensure that the app works smoothly in any type of environment. Especially for web apps, cross-browser testing cannot be avoided. Studies have suggested that people uninstall the app after using it once if the UI is not user-friendly. Even the app ratings on App Store and Play Store are affected by the user experience, leading to a lower number of downloads. Enterprises can save a lot of money and build a good report among the users by proactively testing their app thoroughly.
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Testing framework plays a crucial role in the success of any automated testing process. Choosing the right test automation framework is important as it will maximize the test coverage and improve test efficiency which means a better return on investment.
There are some key points you need to keep in mind while choosing a suitable python testing framework. The framework should justify your testing needs and it should be easy to use. Check if the framework has integrations with other tools and frameworks that you might use. The features, support, stability, and extensibility are also important. So let’s compare the most popular python testing frameworks to make it easier for you to choose the right one.
It is still the most popular python testing framework that uses a keyword-driven testing approach and is used for acceptance testing. To run Robot you will have to install python 2.7.14 or any later version, python package manager, and a development framework like Pycharm. Advantages
Disadvantages
It is an opensource tool developed by the team that made Selenium. Gauge is immensely useful while integrating continuous testing in the CI/CD pipeline. It is gaining popularity as it supports many plugins like python runner, IDE plugins, build management, java runner, etc. Advantages
Although Pytest is used for different types of testing, it is more preferred for functional and API testing. There are no prerequisites needed for Pytest, just knowledge of python will be enough to get started. It has a simple syntax which makes test execution easier. Advantages
It is a unit testing framework much like Junit but for python language. Also referred to as unittest, it has five core modules. The test loader class is used to load all the test cases and test suites. The test runner shows the result of the test executed using an interface. The test suite is a collection of test cases that are clubbed logically based on the functionalities. A test case contains the actual implementation of the code and the test report contains the organized data of the test results. Advantages
In Behave, test cases can be written in simple language and lets teams execute behavior-driven development (BDD) testing with ease. Behavior-driven development encourages quality analysts, developers, and business managers to work in collaboration to achieve higher efficiency. Advantages
All the above-mentioned frameworks have their specialties like Pyunit is used for unit testing and Behave is good for behavior-driven testing. Although Robot framework is the best tool for a beginner to learn the nuances of automation framework. It’s always better to jot down your requirements based on their priority and then choose the right python testing framework.
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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