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The Android App Bundle (AAB) is an innovative app publishing format introduced by Google to enhance the development, distribution, and user experience of Android applications. Unlike traditional APKs (Android Package Kits), which are directly installed on user devices, the App Bundle is a more efficient .aab file that contains all necessary resources, assets, and code. Google Play processes this bundle to generate optimized APKs tailored to individual devices, ensuring a smaller app size and improved delivery efficiency.
Think of the App Bundle as a dynamic and modular container that allows developers to streamline app building while providing users with a customized, lightweight experience.
1. Dynamic Delivery
App Bundles utilize Google Play’s Dynamic Delivery system, ensuring that users only download the necessary resources for their specific device configurations, such as screen density, CPU architecture, and language packs. This eliminates unnecessary bloat, making app downloads faster and more efficient.
2. On-Demand Features
With Dynamic Feature Modules, developers can provide optional features that users can install later instead of bundling everything at once. This reduces the initial download size, enhances flexibility, and improves the overall user experience by allowing users to personalize their app features.
3. Smaller App Size
By excluding unnecessary resources, App Bundles significantly reduce the app’s overall size. This is especially beneficial for users with limited storage capacity as they no longer need to download assets that are irrelevant to their device. Reduced app size also improves installation speed and performance.
4. Google-Managed App Signing
Google Play manages the signing of APKs generated from the App Bundle, ensuring security and seamless updates. This eliminates the need for developers to manually handle key management, reducing the risk of key loss or compromise and ensuring app integrity.
5. Backward Compatibility
App Bundles are compatible with devices running Android Lollipop (API level 21) and above. This means developers can adopt the AAB format without worrying about excluding users with older Android versions, making it a flexible solution for app distribution.
The Android App Bundle leverages Google Play’s Dynamic Delivery system to generate and distribute optimized APKs specific to each user’s device. This eliminates unnecessary data, reducing app size and enhancing performance.
1. Split APK Mechanism
The App Bundle acts as a container file (.aab) that includes all app resources. Google Play then breaks it down into smaller modular APKs tailored for individual devices. Instead of downloading a large, universal APK, users receive only the parts necessary for their device.
Example:
2. Types of APKs Generated
a) Base APK
b) Configuration APKs
c) Dynamic Feature APKs
3. Dynamic Delivery by Google Play
4. Security & App Signing
5. Key Technologies Behind App Bundles
An Android App Bundle (.aab) is an upload format for Google Play that organizes app resources into modules. Google Play then generates multiple APKs based on this structure.
App Bundle’s Key Directories:
Unlike APKs, App Bundles cannot be directly installed on devices. Instead, developers upload a signed .aab file to Google Play, which then builds and signs APKs for distribution via Dynamic Delivery.
To generate and upload a signed app bundle:
Pcloudy supports the .aab format, allowing developers to upload and test their App Bundles on real devices in the cloud. This ensures smooth functionality before releasing the app to users, making it a crucial step in the testing phase.
The Android App Bundle is a game-changer for app development and distribution. By optimizing APKs for individual devices, reducing app size, and streamlining feature management, AAB improves the overall efficiency of Android app publishing. Developers benefit from simplified build management, while users enjoy faster downloads and reduced storage consumption, leading to higher app adoption rates.
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Automation testing has become a cornerstone for enhancing productivity and quality in software development. When implemented correctly, it accelerates delivery cycles, improves testing accuracy, and streamlines workflows. However, transitioning to automation isn’t without its hurdles. Teams, especially those new to automation, often face challenges that can slow down adoption and diminish the potential benefits.
In this blog, we will delve into the common challenges in automation testing and provide actionable solutions to overcome them effectively.
But first, let’s have a look at the most prevalent automation testing challenges:
Why is it a Challenge?
Choosing the right approach is the foundation of successful automation. However, teams often struggle to balance the effort required to design, implement, and maintain test automation frameworks with the evolving needs of agile development cycles. Key issues include:
Impact:
Without a clear strategy, teams may end up creating brittle test scripts that fail whenever the application under test (AUT) changes. This results in wasted resources and delays in the development pipeline.
Solution:
Implement self-healing test automation frameworks that can adapt to application changes automatically. These frameworks identify updates to the AUT (e.g., UI changes or element relocations) and adjust test scripts accordingly. Additionally, designing modular test suites with reusable components can significantly reduce maintenance overhead.
The automation testing landscape is vast, with numerous tools offering varied capabilities. Common issues include:
Using the wrong tool can lead to inefficiencies, increased costs, and suboptimal test coverage. A mismatch between the tool’s capabilities and the team’s skills can further delay automation initiatives.
Many teams opt for in-house device labs to conduct tests. While this approach offers full control, it comes with several hurdles:
In-house labs can become a bottleneck, diverting resources from testing to maintenance. Teams often struggle to keep pace with rapidly evolving technology, leading to inadequate testing.
Adopt cloud-based testing platforms that provide access to a wide range of devices, operating systems, and browsers. Cloud platforms eliminate the need for hardware maintenance, ensuring that your testing environment is always up to date. Platforms like Pcloudy enable continuous testing across multiple devices, significantly reducing time and cost.
Automation generates an overwhelming amount of data, including logs, test results, and performance metrics. Teams often face difficulties:
Without effective data analysis, teams may miss critical defects, leading to delays in resolving issues and potential impacts on product quality.
Invest in test analytics tools that organize data into meaningful, actionable insights. Features like real-time dashboards, defect tracking, and traceability help teams quickly identify bottlenecks and root causes. For example:
Deciding the right time to start and stop testing is a nuanced decision that depends on the software’s development stage, stability, and release deadlines. Challenges include:
Testing at the wrong stage can result in inefficient use of resources, delays in delivery, and inadequate test coverage.
Challenge
Impact
Solution
Selecting a suitable approach
High maintenance effort, unstable tests
Use self-healing frameworks and modular test suites.
Choosing the right tools
Inadequate test coverage, inefficiencies, high costs
Create a tool selection framework, invest in training, and evaluate ROI.
Rigorous lab management
Resource-intensive, outdated labs
Leverage cloud-based platforms for scalability and cost-effectiveness.
Sorting through data overload
Missed defects, slow analysis
Adopt test analytics tools for actionable insights and prioritized testing.
Knowing when to begin/stop testing
Wasted effort, delays in release cycles
Start with manual testing, automate incrementally, and align with teams.
The only way to successfully address the top challenges in automation testing is to use a solution that combines the four components listed above. If a solution is missing one of the components, a critical part of the continuous testing process is lost. What’s more, there is a good chance team will spend a significant amount of money accounting for gaps or compromising quality.
While the challenges mentioned here are not the only ones in the list of challenges for automation testing. There are other challenges also such as lack of collaboration and skills. But those challenges are not hard to overcome. Whether we talk about mobile automation testing challenges or Selenium automation challenges for web apps, cloud-based testing is the solution. It gives you the flexibility and scalability needed to deliver a quality product in less time. With the right tools, skillset, and infrastructure, these challenges can be overcome over time.
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 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.
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.
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.
Here I bring to you the 5th blog in the DevOps series showcasing our learning while #scalingup. Read our previous blog to know about the bunch of tactics that we used at different times during our evolution to achieve a successful clockwork during our DevOps journey.
Proper optimized code review is something that many startups miss. Some take the easy way out and ignore it and others spend years discussing the best practices, conventions and styles without ever committing code. Both these are slightly over exaggerated examples of paths to failure, but I am sure you can relate to these if you have ever tried to answer the all important question about code review “Exactly how much code review should your team do?”
For perfectionists, the answer is that code should always be reviewed and you should always be refactoring code and improving it wherever you see a scope. I have worked in companies, where people used to spend almost as many hours reviewing code as much as they would writing them. There are some practices like pair programming, which has maximizing code review as one of the results. So this is not exactly a wrong direction of thinking. The problem however is that when you are working with time constrained environments like that of a startup, you will not have a luxury where you can keep revisiting and improving code beyond a reasonable amount of time. And I have seen that surprisingly many people altogether avoid code review because timelines are constrained. I don’t even need to mention how risky this is and how dangerous this course of action is. However it seems many people do exactly that.
In this blog post, I will attempt to throw light on our experiences in deciding how much is enough. We too, like other startups have a time constrained environment, and a few (thankfully only a few) customers who want every feature done yesterday. So as a culture, we too try to make sure that we finish everything faster. Development faster, Testing Faster, Deployment to various environments faster. But we do not ignore code review. We ensure that we do code review. We have a few principles that we followed to make sure that code review happens all the time, and is neither too less nor too much. Here are they. What we have seen is that if you follow all these steps, then you have a sane code review process and you can guarantee a stable flow of god code into your repository. These points are in no particular order of importance.
You should do code review: The first principle is not a lame attempt at a joke. The idea is that code review should happen come what may. Without this principle being followed, every other principle in this list breaks down. We use git-flow as one of our developer methodologies with git. One of the advantages of this system is that code review is built in. Unless code is approved by a designated reviewer, the code does not go to the next level be it Testing or Production. The Approver is as responsible for a piece of code as the original developer. This way the reviewer spends more time reviewing and the original coder also reviews and corrects his code in advance to preempt the reviewer. This adds more points in the system where code review can happen and makes sure that code always gets reviewed and the review is not forgotten.
Requirement Matching: Does your code do what the requirements ask it to do? Are we doing less? Are we doing more? A quick inspection reveals mismatches if any. This goes a long way in finding out if there are any problems in the code.
Readability: There is an apocryphal statement that says that code is written once and read hundreds of times. While the statement may not be accurate, you may write more than once, and may not read hundreds of times, you still do get the picture. The basic premise is that code does get read many far more times than it gets written. Also once written, your code will also be read for review, bug fixes, enhancements, etc and not always by you. Also in the IT Sector, jobs switches happen a lot, so a new person should be able to understand and work with the code as soon as possible.. So it makes sense that whoever looks at your code after you have left is able to understand your code well and can alter if needed and maintain the code well till the product lifetime completes.
Reviewability: A further subset of this is that the code should also be reviewable, you and your code should be able to convey to the reviewer what the code is supposed to do and what the reviewer is supposed to review.
Scalability: Will your code be able to stand frequent and/or continuous requirement changes in the future? Will it be able to handle a reasonable amount of requirement change without having to have to rewrite the entire thing? Overall applications are live, especially in the Agile era, your requirements are never frozen, and hence the code also should never be frozen. It should be able to handle changes in requirements. A word of caution here, do not overdo this. While your code should be able to handle requirement changes, you cannot (and should not) make your code so generic that it can handle the proverbial ‘everything under the sun’. Your code should be reasonably scalable. Too much scalability also is as bad as too little. How much to go down this path will depend on your specific business needs. However it is not a bad idea to talk about specifics to your business stakeholders. They can tell you how and more importantly how much a feature will be used. You can then decide how scalable you want the code for that feature to be. The process of arriving at how much is just right, takes time to set, but once done, you will thank yourselves for the foreseeable future.
Improvements: This is one of the basic purposes of code review. This answers the question, “Can we do the same thing in a better way?”. Better way could mean one or more among, faster performance, better readability, more modularity, and others. You need to keep asking this question in a code review. If you can, then your code review is not complete, if you cannot improve any longer, then probably the code reached here after many rounds of reviews. Or was copied from well reviewed code. Again this is one of those things that has the potential to be overdone, so think carefully how far do you want to go down this rabbit hole without losing your wits.
BNBR: This is lifted from one of the policies of Quora, It means Be Nice, Be Right. The point is that while reviewing , you need to be nice and be right. Being Nice First. The point of a code review is to see if things can be done better by putting multiple heads instead of one. It is not to hurt or massage egos. What can be done by just pointing out issues with data should not descend into a shouting match (verbally or through the keyboard). Make sure that your comments are politely worded and are correct.
Code Scanners: Before you give your code for review, your code should be scanned by tools to make sure that basic checks are done for issues like parenthesis matching, formatting, typos, indentation, naming convention etc. Your reviewers will have a tougher time navigating your code if you do not fix these. If your reviewer finds these issues and not a code scanner, then you have not prepared for your review well.
The Unhappy Path: The code works fine, but some scenarios were not tested. How do you know if your code is able to handle most of the basic errors or exceptions. Your review should make sure that this is in place well before time. Again you need to use this judiciously. You should not overdo it.
Timeliness: Your code review should have a deadline. You cannot indefinitely keep reviewing the code, your review should finish within a deadline. If you ship years late, how will better code help you ?
Dark Spots: Every reviewer may not be able to review all aspects of the code. So it is a good practice to tell in the review comments what aspects were reviewed and what were not, so that everyone knows the extent of the code review. If everyone says it looks good to me, but everyone only happened to review the naming conventions, then it probably was better if only one person reviewed. If each reviewer mentioned this small info, then everyone knows in advance if there were any dark spots in that particular review and they will be able to redress it.
Fatigue: Do not review too many pieces of code at a time. If you happen to be spending a long time reviewing, then probably the code under review is too large or you are reviewing too many PRs at the same time. Reviewing is a thought intensive process and you need to make sure that it is done properly. So please take breaks, if you are tired of reviews and are still somehow powering through that will reflect in the quality of the reviews. A rule of thumb is to not review more than 60 minutes at a time or around 400 lines of code at a time.
Checklists: One good shortcut is to use checklist to review a PR or a piece of code against. These checklists ensure that your mind does not wander, wondering what you have missed and you will also be reviewing against pre decided metrics.
Defects: What do you do with the issues you found ? Not every issue needs to be or can be fixed immediately. You have to decide what to do with each review comment. Whether you will be fixing them, ignoring them or putting back into your backlog. Make sure this is a separate backlog for technical debt.
Overall these are the things that we follow while doing code review. Many of these helped us a lot to make sure that we are reviewing just enough to keep our process wrooming along while at the same time, not ignoring major issues.
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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