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
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
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
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.
Continuous Testing
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.
Challenges in CI/CD Pipeline
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.
Why CI/CD matters
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.
In a Nutshell
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.
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.
Section 1: Functional Testing
1.1 What is Functional Testing:
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.
1.2 Types of Functional Testing:
1.2.1 Unit Testing:
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.
1.2.2 Integration Testing:
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.
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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.
1.2.4 Regression Testing:
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.
1.2.5 System Testing:
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.
1.2.6 Beta/User Acceptance Testing:
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.
Section 2: Non-Functional Testing
2.1 What is Non Functional testing?
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.
2.2.1 Performance Testing:
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.
2.2.1.1 Endurance Testing:
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.
2.2.1.2 Scalability Testing:
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.
2.2.1.3 Load Testing:
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.
2.2.2 Usability Testing:
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.
2.2.3 Security Testing:
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.
2.2.4 Compatibility Testing:
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.
2.2.5 Accessibility Testing:
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.
Section 3: Key Differences between Functional Testing and Non-Functional Testing
3.1 Focus:
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.
3.2 Objectives:
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.
3.3 Timing:
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.
3.4 Test Cases and Techniques:
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.
3.5 Scope:
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.
3.6 Success Criteria:
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.
3.7 Dependencies:
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.
3.8 Test Environment:
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.
3.9 Test Data:
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.
Conclusion:
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.
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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.
What is Cross Browser Testing?
Browser compatibility testing can be automated or done manually.
In manual cross-browser testing, the testers have to test the app on multiple OS, device and browser combinations. This is why it is a time-consuming process.
The main issues are with the UI and the main features are tested on different screen sizes to check if the look and feel are similar to what was expected.
In automated cross-browser testing, there is a need to create the test script initially then there is minimal human supervision is required.
Efficient automation tools will take much less time to perform the testing.
Automation for Cross Browser Testing
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.
Feasibility of Local Test Environment
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.
Types of Cross Browser Functional Testing
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.
Conclusion
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.
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.
Robot framework
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
Opensource
Platform independent
No need to learn a programming language to write Robot Framework test cases
Automatic report generation after executing each built
Supports behavior-driven, data-driven and keyword-driven approaches
Easy installation
Disadvantages
Not enough support for parallel testing
It’s difficult to create customized HTML reports
Gauge
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
Quick defect detection
Easy to write test cases
Supports multiple programming languages
Command-line support
Supports all major plugins
Cross-browser tests can be automated
Disadvantages
It is relatively new so it will evolve in the coming years
Pytest
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
Supports Fixtures and Classes that help in creating common test objects available throughout a module
It allows the use of multiple fixtures
It does not require a debugger
Xdist and other plugins support makes parallel execution easier
It supports parameterization, which is essential while executing the same test with different
configurations using a simple marker
Large community support
Disadvantages
Test written in Pytest cannot be shared with other platforms
Pyunit
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
No need for high-level python knowledge for test execution
Extensive report generation
Pyunit comes with Python package, no need to install any additional module
Simple and flexible test case execution
Disadvantages
Requires boilerplate code
Pyunit is derived from Junit and so it still uses camelCase naming instead of snake_case naming method
It supports abstraction so the code intent sometimes becomes unclear
Behave
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
Easy execution of all kind of test cases and easy coordination
Better clarity on the developers and testers output as the format of the spec is similar
Domain vocabulary that keeps the behavior consistent in the organization and the system behavior is expressed in a semi-formal language
Detailed reasoning and thinking promotes better product specs
Disadvantages
Only for black-box testing
To sum it up
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.
How to write test cases in a better way
Let’s have a look a the tips to write better test case template.
1. Detailed Domain Knowledge
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.
2. Break long test cases into many smaller ones
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.
3. Preconditions
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.
4. Attach Artifacts
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.
5. Test data input
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.
6. Organize your work
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.
7. Stop Assuming
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.
8. Test Case Naming Conventions
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.
9. Meet Customer’s Requirements
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.
10. Cover All Verification Points
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.
11. Avoid Repetitions
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.
12. Make it Reusable
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.
13. All-Inclusive Test Coverage
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.
14. Group Similar Test Cases
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.
15. Easy to Understand
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.
16. Test Case Description
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:
Any dependencies like preconditions and assumptions
Test Data to be used
17. Maintenance and Update
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.
Conclusion
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.
Today, there are many smartphone users in the world and so is the popularity of mobile apps. In order to be competent enough, mobile apps have to be unique and should provide the best user experience to increase the user base. With the users getting more informed and intelligent, the apps built should keep up with the pace. In order to be impeccable, the mobile app should undergo a rigorous testing process and during that process, the testing team faces many challenges in this aspect which will be covered in this blog. But before we dive in, let’s look at the different types of apps that are available in the market.
Types of mobile applications
The creation of mobile applications is a fantastic approach to boost brand recognition, attract new clients, and improve the user experience for existing customers. In light of this, let’s examine the three primary categories of mobile apps: native, web, and hybrid.
Native apps:
Native mobile applications are ones created exclusively for a given operating system. As a result, software created for one System cannot be used on another, and vice versa. Native applications are more effective, quick, and offer greater phone-specific functionality. Thus, the difficulties of testing mobile apps for compatibility with native user interfaces of devices involve ensuring that such traits are preserved strictly.
Web apps:
Similar to native apps, web applications do not require users to download them. Instead, the users’ web browsers on their phones can access these apps because they are incorporated within the website. So, it is envisaged that web applications will operate flawlessly across all platforms. Testing teams must carefully examine the application on a wide range of real devices and browsers to ensure high app quality. Yet in addition to taking a lot of time, this operation is essential because failing to work on a few devices can severely reduce the app quality and incur heavy losses when the app doesn’t function as required.
Hybrid apps:
The features of both online and native apps are available in hybrid apps. These are essentially web applications that mimic native apps in design. These applications are easy to maintain and load quickly. Teams that test mobile apps are in charge of making sure hybrid applications don’t lag on some devices. Any operating systems with the capacity to support the said features have access to all their functionality.
While each of these app types are slightly similar to each other the technical teams face a different challenge with each type of mobile application. Combining these challenges greatly increases the complexity, making the entire procedure laborious and time-consuming. Let’s quickly look into what some of these challenges are?
Different Operating Systems and their versions
There are different types of operating systems available in the market such as iOS, Android, Windows etc. Also, these OS have different versions too. So, it becomes challenging to test so many versions of the mobile app in a shorter period of time. One app that works well in one type of OS may not work well in the other. It is very important to test the application with all supported platforms and their version because we don’t know where the user is going to install the application. As per research, iOS users upgrade quickly as compared to Android but in Android the device fragmentation is larger. That means the developers have to support older versions and APIs and testers also have to test accordingly.
Device Variations: Based on Screen size
Android comes with a mix of features and variations in pixels densities and ratios which varies in each screen size. Even in the case of Apple, the screen new size was introduced with the launch of the iPhone 6. Now, it is not just about being picture perfect screen design rather designing an adaptive screen design. Well with such a variety in screen sizes, the role of the tester becomes serious as they need to check if all the features are working well in different screens and pixel and aspect ratios are maintained well.
Based on the number of Devices
The picture below shows the number of devices in the market by different brands. The number of device manufacturers has increased. According to OpenSignal, there are around 1294 distinct Android phone manufacturers alone, imagine if we add up other brands. The pace with which this data is increasing is a bit alarming for the testers as the testers have to check the app performances on different devices, they would probably need a device library to do the same. The challenge remains in context to functionalities like Complex user interactions on touch screen and keypad devices as well. Having a device library is certainly is a costly affair unless emulation is adopted which can simulate multiple device types and testing can run easily on it.
Image Source: venturebeat.com
Various Networks
The QA team also faces challenges when it has to test the devices connected to different networks. Generally, there are 2G, 3G,4G mobile data available. These provide different data transfer speed and transmission. These varying speeds of the networks by various providers remain a challenge for the testers even today. In this case, testers have to check that the app must perform well at different network speeds and connectivity quality and a check on bandwidth usage of the app. This remains a challenge as it is partially controllable based on different network providers and connectivity access in different geographies.
Frequent OS releases
Mobile Operating Systems keeps changing. Both Android and iOS have more than 10 versions of their operating systems. They keep enhancing and updating their versions for better performance and user experiences. This frequent OS release comes as a testing challenge as the testers needs to validate the complete application with each of new OS release. It is very important to test the application with the latest OS release otherwise the app performance would be a major issue and consequently loss of users using the app.
Script Execution
Another major challenge of mobile testing is what we call scripting, the method of defining a test. Script execution can either be manual or automated. You can write down the scripts in a document, which is then used by a test engineer who manually interacts with the test environment to determine the result, else you can run automated scripts that in turn drive interaction with the device and app, and record the results.
Automated scripting needs to be kept away from the device to be of any real use because there are so many different devices with different interface options. A script that follows strict keystrokes on an Apple iPhone would not have any chance of working on a Samsung device, because the UI is different. Fortunately, most real device automated testing software provides high-level scripting that operates on the text, image, or object layer. Device emulators can automate testexecution using a higher-level, abstracted scripting language that is not device dependent. When you use automated scripting, the cost of setting up the script will typically be higher than the cost of a single manual execution of a test. But if it is a test script that you run on a periodic basis, every time that you subsequently run the script, the more time and effort you will save. You will eventually recover the cost of initial scripting If you run the script enough.
So to conclude, to build a better user experience, an app tester needs to work had in overcoming the challenges of testing. By adopting some analytical skills and methods, testers can really cope up with these situations. For eg. Testing only those apps and OS which are mostly used by their user segment, by adopting a strong testing strategy to take situational decisions eg. Decisions regarding when to choose Automation and manual testing. Strategically, the challenges can be overcome.
Screen Size
The Android world is not simple. The variety of different aspect ratios and pixel densities can be overwhelming. With the launch of iPhone Xs Max which has a screen size of 6.5 inches, Apple brings new screen sizes to the iOS world as well. Though iOS developers are used to pixel perfect screen design, they now need to change their mindset to the adaptive screen design instead. For testing, it means that we need to check on various devices that all the necessary screen elements are accessible with different screen sizes and aspect ratios. There are many phones with a screen size of 5 inches which are still popular.
Security Issues
Traditional testing tools like selenium and QTP weren’t designed with cross-platform in mind. Automation tools for web apps and mobile apps are different. Operating systems especially Android further adds to the complexity with API level fragmentation. The most common automation testing tools for mobile app automation testing are Appium and calabash. Each tool has it’s own advantages and disadvantages and you need to choose on the basis for your app’s functioning.
Weak Hosting Controls is one of the most common issues. The server on which your app is hosted should have security measures to prevent unauthorized users Weak Encryptions can lead to data theft which will impact the trust factor of the users. Most of the mobile apps require user data such as email ID, password, age, location etc. This data should be encrypted and stored with proper security. Hackers often use this kind of data to get money out of users account online. Encryption will make it difficult for anyone unauthorized to intrude and retrieve that data rather than keeping it in plain text.
Power consumption and battery life
We haven’t seen much innovations in the mobile battery but the mobile usage and specifications are increasing rapidly. People are using more apps nowadays and the apps are more complex than ever. This is why testers need to test the apps power consumption because if the apps use lots of CPU cycles and some apps will also run in the background than the battery will drain out quickly. We need to make sure that the app uses less battery power so that users can use it for a longer period of time.
Conclusion
Mobile apps are evolving with device technology and user expectations. Developers are emphasizing on reducing the app size and battery usage. Testers play a major role to ensure that the app works smoothly and does not crash or have bugs. This is why testers must be aware of the latest trends in mobile app testing to deal with the mobile app testing challenges.
As we all know that Appium is the most preferred test automation tool for mobile applications. It is the first choice of the testers because of its flexibility i.e. it is open source, it has the best supported and highly active community of experts, Appium works across different platforms and works well with different scripting languages. Even after gaining such popularity and having a strong community base, surprisingly, the users still make mistakes while running the mobile test automation with Appium.
Here are a few common mistakes that Appium users encounter while using Appium Mobile Test Automation Tool:
1.Unrestricted X Path Usage:
Over usage of X Path could be found in case of Selenium as well but when it comes to Appium world, it has more outrageous effects because X Path is a more dynamic way to unearth the elements. But the biggest stumbling block in this scenario is its huge performance cost due to which it becomes elusive an area. This is because Google and Apple do not provide XML or XPath related queries in a way we would need them to be. All of this hospitalizes an unmanageable cost finding elements using X Path. Undoubtedly, X Path is the most trusted method but there are several other better locator methods like ‘Accessibility IDs’ that can be used in this sitch.
2. Neglected usage of Accessibility IDs:
The accessibility ID locator strategy is formulated to read a unique identifier for a UI element. For both iOS and Android, getting an element by their accessibility ID is the best method. Most importantly, it is preferable because it is quicker. It should be noted that semantically accessible IDs are different than the Web IDs. However, the two shouldn’t be combined. In many cases, the accessibility IDs are used only for the purpose of testing even though they have a larger purpose. So, in order not to spoil the accessibility of the applications just for the sake of testing, the bigger purpose of the accessibility IDs should be known. If the accessible IDs are set up on the elements to make the apps testable, the app accessibility also increases, provided that the accessibility labels are sensible to the users using them. But the foremost criteria not to make automation efforts a failure is to make the application testable in the first place.
3. Not making a testable App:
Developing an app should be a forecasted move where in the developers, even before writing the first line of code, plan to develop an app keeping the automation in mind. This they can achieve by keeping in mind the hooks and the unique IDs for the elements in order to make the app more testable. This strategic approach would be a reason for a successful mobile app test automation. Apart from this, there should also be a concentration on the different testing scenarios in order to elude the chances of overlapping before even getting into Appium coding. An open discussion forum with the development teams to discuss the plotting of right accessibility IDs, labels or Unique IDs for the application’s elements would reduce many test automation reliability concerns.
4. Disregarding Application View States:
One of the challenge faced in Mobile Test Automation is not setting up the application. Most of the developers do not set up the application in order to access specific views and user states rapidly. To quote an example given by Jonathan Lipps,one of the key contributors to the Appium project.
A shopping cart functionality of the app might have ten different tests, and ninety percent of the tests might go through the same steps of logging in and searching items to be put in the cart which is a huge waste of time.
So, your team should be able to set up an app’s state and start the test in that apposite state, straightaway. This is highlighted in Appium scenario due to the fact that the mobile simulators and emulators are slow and take longer than usual to reach to the right position on the test.
5. Query for every element visibility:
Not querying for the visibility of every element is another way to speed up the run-time of the Appium test scripts. This leads to an additional load of calls and waiting time for Appium while in the every activity of retrieving an element. The lag can be reduced by only requesting the element attributes which are important in perspective of the test code.
6. Native Testing tools – Always better?
According to some developers, usage of the native testing tools is the best way to get unfailing mobile tests. For example- Espresso in case of Android and XCUITest in case of iOS. This is not good advice as neither of Google or Apple are going to release and new automation technology. When the question is of stability, the stability of code should be chosen rather than technology and in this scenario, Appium is the best choice!
As an exception, if the development team writes the tests and it’s most comfortable in mobile SDK language, using Google and Apple providers to build development environments. Also, when the constricted test-app or test code-app code integration is needed, then Appium might not be of much help. The utmost value is that Appium provides the WebDriver layer on top of the technology, which means the code can be written in any language and acts as a stable interface to that specific automation technology. Also, being a cross-platform tool, Appium allows to saves a lot of code and architecture in case of testing both iOS and Android devices.
7. Appium is slow:
Appium might be slower in some circumstances and also there are points in Appium codes where it does not seem efficient. Appium backs upon technologies that are slower than Appium and the curators of Appium have strategically chosen to utilize slower strategies for specific instances. For eg: Appium will certainly be slower if you are relying on XPath. The efficiency of the tool depends on how it is being used. Mostly, Appium is favored because of stability than the speed.
8. Not Using Appium Documentation:
The earlier Appium docs were not very user friendly. As a result, they weren’t used as much as they needed to be but the new Appium documents have been completely redesigned and reorganized. Information about the API reference to Appium, client libraries, supported drivers and Appium commands, code examples which was not provided before is all documented in the updated version. It deserves a revisit due to its newness and can be accessed at Appium.io.
9. Not creating reusable code
Repetitive or duplicate code can cause several issues for Appium mobile testing process. When the same code is repeated in several test scripts, any updates or modifications must be copied across all instances. This increases the chance of failures and complicates the debugging procedure. It also increases the maintenance cost for the organization.
Duplicate code makes identifying the primary reason for a test failure challenging. It can be difficult to pinpoint which occurrence of the code caused a test to fail if the same code is used repeatedly throughout several test scripts. This could increase the duration required for debugging the software and expand the market time.
Therefore, it’s crucial to use appropriate coding principles to prevent these issues. This includes creating simple reusable code, utilizing libraries and frameworks, and modifying code to remove redundancies.
10. Ignoring the Test-driven Deployment
Test-driven deployment is an Appium mobile test automation approach that stresses developing automated test cases before writing application code.
It lets the developer test all the application features before being deployed. This way, they can detect and resolve any bug in the early stage. This saves not only the organization’s time but also valuable resources.
Not just this, Test-driven deployment also helps developers in developing more reliable and enduring codes. By allowing them to understand the needs and provide a solution accordingly. Which lets them create more modular, maintainable, and error-free codes.
11. Choosing the right tool for API testing
APIs may have several endpoints, each with a unique set of parameters, methods, and authentication requirements. Writing and maintaining tests that accurately reflect the behavior of the API can be challenging due to this complexity.
Another difficulty is the requirement to simulate various scenarios and inputs. Testing for different response codes, error messages, and payloads might be part of this. To ensure the API can manage a high volume of queries, developers might also need to simulate load and stress testing.
Developers use a testing framework or library like RestAssured and Postman, which provides integrated support for API testing. These tools streamline and simplify the testing process by providing pre-build methods for common API testing scenarios, these tools streamline and simplifies the testing process. Alternatively, they can mimic various scenarios and inputs using mock data or a staging environment.
Developers can test their API in a safe setting before releasing it for production. Moreover, they can evaluate the API’s capacity by simulating heavy requests using load-testing tools like JMeter or LoadRunner.
12. Need to follow a good design pattern.
In Appium mobile test automation, the Page Object Model (POM) and the Page Automation Layer Model (PALM) are popular architectural patterns. Both techniques increase automated tests’ maintainability, scalability, and reusability.
POM is a design pattern that emphasizes the creation of reusable and modular code by isolating the application’s user interface from the test automation code, making it simpler to update tests when UI changes are made. POM builds an object repository that holds all the web elements and methods.
PALM is another design pattern that builds upon the principles of POM. But unlike POM, which focuses on UI elements, PALM emphasizes creating an abstraction layer between the test automation code and the application’s business logic. This approach distinguishes the test automation code from the underlying implementation. Thus making it easier to modify the test code without affecting the business logic.
Technology and innovation are two sides of the same coin. Technology is the power that lets the mankind turn ideas into reality within no time. At pCloudy, the power of innovation has led us to stay aligned and be in pace with the dynamics of the mobile app industry. We cannot afford to let our customers stay deprived of any technological advancements happening in mobile app testing. Once again we are back with another new feature called QR code scanner and we are proud to announce that it is already launched on our platform.
Nowadays many mobile applications use QR code scanners for a product or user identification. The QR Code scanning feature in pCloudy enables users to test the QR code feature through mobile applications on multiple devices present in pCloudy. This feature ensures the smooth functioning of the QR code function present in the mobile application. To use this feature, all you need to do is upload the mobile app under test, a QR code image file, and with the help of some simple steps, you can smoothly perform testing of the QR code scanning function of your mobile application.
The app will scan the injected QR code. You can scan multiple QR codes while testing your app on different mobile devices. So from now on you can easily perform QR code testing in pCloudy. This feature is supported on Android 5.0 devices and later versions. Supported QR Code file formats are .png,.jpeg and jpg.
Android uses a centralized system for all logs and application programmers can also write custom log messages. The tooling to develop Android applications allows you to define filters for the log statements you are interested in. Log analysis is a phase of development and developers encounter it from time to time. Bug log helps in identifying the bugs in the Android application while in the development phase. Once the app is released into the market, the support engineers analyze the bug logs to resolve the issue. There are for different types of Logs available in the Android Eco-System – Application Logs, Android System Logs, Event Logs & Radio Logs.
The logging system consists of a kernel driver and kernel buffers for storing Android log messages, C, C++ and Java classes for making log entries and for accessing the log messages, a standalone program for viewing log messages (logcat) and the ability to view and filter the log messages from the host machine (via eclipse or ddms).
There are four different log buffers in the Linux kernel, which provide logging for different parts of the system. Access to the different buffers is via device nodes in the file system, in /dev/log. The four Android log buffers are main, events, radio and system. The main log is for the application, events is for system event information, radio is for phone related information and system is low level system messages and debugging.
Each message in the log consists of a tag indicating the part of the system or application that the message came from, a timestamp (at what time this message came), the message log level (or priority of the event represented by the message) and the log message itself (detail description of error or exception or information etc).
What Each Android Log Type Contains:
1. Application log
use android.util.Log class methods to write messages of different priority into the log
Java classes declare their tag statically as a string, which they pass to the log method
The log method used indicates the message “severity” (or log level)
Messages can be filtered by tag or priority when the logs are processed by retrieval tools (logcat)
2. System log
Use the android.util.Slog class to write message with different priority with its associated messages
Many Android framework classes utilize the system log to keep their messages separate from (possibly noisy) application log messages
A formatted message is delivered through the C/C++ library down to the kernel driver, which stores the message in the appropriate buffer(system buffer)
3. Event log
Event logs messages are created using android.util.EventLog class, which create binary-formatted log messages.
Log entries consist of binary tag codes, followed by binary parameters.
The message tag codes are stored on the system at: /system/etc/event-log-tags.
Each message has the string for the log message, as well as codes indicating the values associated with (stored with) that entry.
4. Radio log
Used for radio and phone (modem) related information
Log entries consist of binary tags code and message for Network info
Logging system automatically routes messages with specific tags into the radio buffer
Device Logs on pCloudy Platform.
Device Logs Filter Options
Log format on Android
A common log format in android:
tv_sectv_nsec priority pidtid tag messageLen Message
tag: log tag
tv_sec&tv_nsec: the timestamp of the log messages
pid: the process id of where log messages come from
tid: the thread id
Priority value is one of the following character values, ordered from lowest to highest priority:
V — Verbose (lowest priority)*
D — Debug*
I — Info*
W — Warning*
E — Error*
F — Fatal*
S — Silent (highest priority, on which nothing is ever printed)
Log-File locations
There are several directories where Android log (including those from crashes) stores and it are not standardized (i.e. some may be ROM-specific). I am putting some of common here.
/data/anr : Dalvik writes stack traces here on ANR, i.e. “Application Not Responding” aka “Force-Close”
/data/dontpanic : contains some crash logs including traces
/data/kernelpanics :- Stores “kernel panic” related logs
/data/tombstones :- may hold several tombstone_nn files (nn is a number from 0 to 10 and after 10 again repeat it)
‘Log’ command line tool
To capture Android log from the devices/emulator Below is the some command line tool. In real life project there are log capture application/tool used to capture the logs on user device and shared it back to Developer/maintainer for analysis .
adb logcat (shows all type logs for current android system
adb logcat -v threadtime (it will include date and time)
adb logcat -v threadtime> logfile.txt (Store logs in logfile.txt)
Useful filter patterns
You can use below filter in your adb command to filter logs. You can also use this filter to search your logs file(Android logs provided by user device).
adb logcat -f Save all logs into a file
adb logcat “*:E” Get all errors and fatals
adb logcat | grep -i “foo.example.” #get all logs related to “foo.example.*” tagname
adb logcat “application_or_tag_name:*” “*:S” Get all logs by application name
adb logcat -b events “gsm_service_state_change” “*:S” Get all GSM state changes
adb logcat -b radio Get all Radio events
Log Analysis
In this blog we got the basic understanding of the Android Log System. While analyzing the Android logs from your app you can divide it in two parts, debug Logs – file coming during development and testing phase and production Log – file coming directly from end user. The best way to do it is by using useful Filter Patterns and by using Some Tool like GoogleLogTool and SonyLogTool.
We all understand the importance of software testing and how it transforms the goodwill of the business by enabling delivery of quality product to its clients in shorter delivery cycles. It becomes challenging to run the test cases manually by evaluating the quality of each line of code at every step of the continuous Delivery process. This is where Continuous testing in DevOps comes into picture.
Continuous testing in DevOps Pipeline
In traditional ways of testing the software used to pass through different development and QA phases which took more time until the final delivery of the product. According to a research by Gartner, Continuous testing in DevOps is aimed at providing early and quick detection of signs of risks related to the product release. DevOps Continuous Testing is an inevitable activity of the delivery process rather than just a mere stage in the delivery process. The main purpose is to inculcate quality into the CI/CD pipeline by utilizing the key benefits of continuous testing in DevOps.
DevOps Continuous testing is a critical aspect responsible for seamless Continuous Delivery. It involves the usage of agile development methods and processes into the QA process further providing a productive testing process.
Here are a few points to understand the benefits of Continuous testing in DevOps at the deeper levels:
a. Provides Sustained Risk Analysis:
There has never been any code build that is error free and in a ready-to-release form. Even if the final release candidate has come without any glitches, passes all the tests, it has to be ‘prepared well’ for the final release and approved by the business leaders. Continuous Testing evaluates the code at a deeper level to estimate all the possible risks connected to it so that a corrective action could be taken at the right time without breaking the ‘continuous delivery’ chain.
b. Cuts down the feedback cycle:
The key benefit of continuous testing is that it evaluates the code layer by layer at each stage of delivery pipeline, allowing testers to understand the source of the problem. The actionable insights helps the QA team to act on time and avoid longer queues
c. Broader Test Coverage:
A broad range of tests can be applied throughout the testing process with the help of continuous testing tools for DevOps such as Selenium, etc. It covers both functional and non-functional testing types to increase test coverage by emulating testing like cross-browser testing, API testing, regression testing, integrated testing, unit testing and non-functional testing like security, reliability, scalability, usability and many more.
d. Delivering High Quality Product:
‘Test-early-test-often’ is the key mantra of continuous testing which is self explicable. In order to ensure delivery of high-quality product to the end user, there needs to be a process to continuously monitor the progress along the entire delivery pipeline. Achieving high product quality is the result of continuous testing that strives to finding and addressing risks effectively and by gaining feedback at the early phases of software development lifecycle.
e. Faster Software Delivery:
The whole point of introducing Continuous Testing in DevOps is to speed up the product delivery cycle. Following a multi-point testing at different stages allows the QA team to detect the glitches early and take quick corrective actions so that the final delivery is not impacted.
f. Easy Integration with the DevOps Process:
Continuous testing seamlessly integrated with the DevOps process right from the early stages of the development process rather than functioning just before the release. Continuous integration into the software pipeline enables quick fixes so that the development process can be aligned with the business requirements on time.
Tools for continuous testing in DevOps
For a seamless experience in the entire CI CD process, Continuous testing has to be supported by the best tools for continuous testing in DevOps. For performing smooth Continuous Testing, the Automation Framework has to be integrated with the CI tool, version control and various automated continuous testing DevOps tools to execute different types of testing at various stages of the process. For example, :
Using Selenium for performing functional testing
Load runner for performing load testing at its best,
Secure code analysis using Fortify and static code analysis using Sonar, etc.
Apart from these there are many other trusted DevOps Continuous testing tools available in the market for an efficient continuous testing, like JIRA, Jenkins, Bamboo, Docker, Appium, SoapUI, PagerDuty, CodeCluster etc. The concern is that not all the tools support comprehensive automation solution. Some organizations prefer to create self-made automation frameworks depending upon the version control used to enable complete automation of the CD pipeline.
Since Continuous testing is the most critical aspect to be covered by the business in order to achieve quality product release, it has to be backed by the choice of right, suitable tools and frameworks to achieve speedy and quality delivery.
Challenges in DevOps Continuous Testing and how to overcome them
Even after understanding the advantages of adopting continuous testing in the DevOps process, many organizations face the challenges of successful implementation of it. Establishment of an efficient automation framework is a daunting deal as it involves a huge investment, expertise and effort. Moreover, the organizations are not equipped with the scalable infrastructure to run tests continuously. Also, without a strong coordination among the product, development and testing team, this seems even tougher. Although there are challenges in successful adoption of Continuous testing, with a little sensibility one can overcome it. Here are a few of the key points to comply in order to overcome the challenges :
By proper team engagement, the cultural and communication barriers can be dealt with enabling the SDLC team to have better coordination, collaboration and understanding of the scenarios.
Reducing unnecessary and extensive testing plans, the focus should be on keeping it simple and logical. Instead, the energy could be diverted to more important test objects in order to create much better measurable results.
Automation would ease the successful implementation of continuous testing in DevOps. Well, complete automation isn’t achievable but more the process automation, easier it becomes to carry on the continuous testing.
Carry out testing at all stages of production and QA environment would continuously providing feedback to developers to improvise on the product quality.
Last but not the least, implementing artificial intelligence and other intelligence programs for problem solving and to think beyond automation at every stage of delivery would boost up the SDLC.
By now we all know how significant continuous testing in DevOps for any business. It essentially brings together all the stages of designing, developing and deploying the software. Merely providing a software product does not help but providing best products faster than the competitors would be the key differentiator of your business. If practiced earnestly, it provides consistent insights about the software development to ensure speedy delivery.
