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.
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.
We are moving toward a future where everything is going to be autonomous, fast and highly efficient. To match the pace of this fast-moving ecosystem, application delivery times will have to be accelerated, but not at the cost of quality. Achieving quality at speed is imperative and therefore quality assurance gets a lot of attention. To fulfill the demands for exceptional quality and faster time to market, automation testing will assume priority. It is becoming necessary for micro, small, and medium-sized enterprises (SMEs) to automate their testing processes. But the most crucial aspect is to choose the right test automation framework. So let’s understand what a test automation framework is.
What is a Test Automation Framework?
A Mobile Testing automation framework is the scaffolding that is laid to provide an execution environment for the automation test scripts. The framework provides the user with various benefits that help them to develop, execute and report the automation test scripts efficiently. It is more like a system that was created specifically to automate our tests. In a very simple language, we can say that a framework is a constructive blend of various guidelines, coding standards, concepts, processes, practices, project hierarchies, modularity, reporting mechanism, test data injections etc. to pillar automation testing. Thus, the user can follow these guidelines while automating applications to take advantage of various productive results.
The advantages can be in different forms like the ease of scripting, scalability, modularity, understandability, process definition, re-usability, cost, maintenance etc. Thus, to be able to grab these benefits, developers are advised to use one or more of the Test Automation Framework. Moreover, the need of a single and standard Test Automation Framework arises when you have a bunch of developers working on the different modules of the same application and when we want to avoid situations where each of the developers implements his/her approach towards automation. So let’s have a look at different types of test automation frameworks.
Types of Mobile Automated Testing Frameworks
Now that we have a basic idea about Automation Frameworks, let’s check out the various types of Test Automation Frameworks available in the marketplace. There is a divergent range of Automation Frameworks available nowadays. These frameworks may differ from each other based on their support to different key factors to do automation like reusability, ease of maintenance etc.
Types of Mobile testing automation frameworks:
Module Based Testing Framework
Module-Based Testing Framework, as the name implies, depends on a number of modules to function. In order to produce the greatest results from the automation test, you would need to develop unique scripts for each module and ensure that they work together. Changes to the application’s functionality won’t have an impact on the modules. The scripts are safe unless they are manually changed.
Given that a high level of modularization is produced by merging multiple modules, this provides a cost-effective management approach. Productivity is still at its highest level. But, if necessary, it can take a lot of time and effort to make modifications to the test data individually.
Library Architecture Testing Framework
Based on the modular foundation, the library architecture framework for automated testing offers several extra advantages. Instead of separating the programme under test into the many scripts that must be executed, related jobs inside the scripts are found and afterwards grouped by function, allowing the application to be eventually divided up into common goals. The test scripts can access this library of functions anytime they are required.
Data Driven Testing Framework
A number of tests must be run while testing an automation framework before a successful result can be determined. In these situations, you might need to alter the test results to try and draw a different conclusion. You can keep the test data on an external drive and access it later for adding a new script to the test case thanks to the Data-Driven Testing Framework.
Keyword Driven Testing Framework
The keyword-driven testing framework, which is frequently regarded as an extension of the data-driven testing framework, collects your test data from an external source and securely preserves the set of codes. These codes, which are also known as “keywords,” can be used to change the test script and draw additional conclusions from the test framework. Also, these keywords effectively determine what tasks each programme performs.
Hybrid Testing Framework
To maximize the effectiveness of the aforementioned frameworks, the hybrid testing framework combines the data-driven and keyword-driven frameworks. It provides more room for more efficiency and success, making it the ideal automation foundation.
Behavior Driven Development Framework
The goal of the Behavior Driven Development framework is to build a platform that encourages active participation from all users, including developers, testers, business analysts, etc. Also, it improves cooperation on your project between the developers and testers. For this behavior-driven testing, test specifications can be written in plain, non-technical language.
Benefits of a Mobile Testing Automation Framework
Apart from the minimal manual intervention required in automation testing, there are many advantages of using a test automation framework. Some of them are listed below:
Faster time-to-market: Using a good test automation framework helps reduce the time-to-market of an application by allowing constant execution of test cases. Once automated, the test library execution is faster and runs longer than manual testing.
Earlier detection of defects: The documentation of software defects becomes considerably easier for the testing teams. It increases the overall development speed while ensuring correct functionality across areas. The earlier a defect is identified, the more cost-effective it is to resolve the issue.
Improved Testing efficiency: Testing takes up a significant portion of the overall development lifecycle. Even the slightest improvement of overall efficiency can make an enormous difference to the entire timeframe of the project. Although the setup time takes longer initially, automated tests eventually take up a significantly lesser amount of time. They can be run virtually unattended, leaving the results to be monitored toward the end of the process.
Better ROI: while the initial investment may be on the higher side, automated testing saves organizations many a lot of money. This is due to the drop in the amount of time required to run tests, which leads to a higher quality of work. This in turn decreases the necessity for fixing glitches after release, thereby reducing project costs.
Higher test coverage: In test automation, higher number of tests can be executed pertaining to an application. This leads to a higher test coverage, which in a manual testing approach would imply a massive team, limited heavily with their amount of time. An increased test coverage leads to testing more features and a better quality of application.
Reusability of automated tests: The repetitive nature of test cases in test automation helps software developers to assess program reaction, in addition to the relatively easy configuration of their setup. Automated test cases can be utilized through different approaches as they are reusable.
Top ten test automation frameworks
1. Robot Framework Robot Framework is the best choice if you want to use a python test automation framework for your test automation efforts. The Robot Framework is Python-based, but you can also use Jython(Java) or IronPython(.NET). The Robot Framework uses a keyword-driven approach to make tests easy to create. Robot Framework can also test MongoDB, FTP, Android, Appium and more. It has many test libraries including Selenium WebDriver library and other useful tools. It has a lot of API’s to help make it as extensible as possible. The keyword approach used by Robot Framework is great for testers who are already familiar with other vendor-based, keyword-driven test tools, making the transition to open source much easier for them.
2. WebdriverIO WebdriverIO is an automation test framework based in Node.js. It has an integrated test runner and you can run automation tests for web applications as well as native mobile apps. Also, it can run both on the WebDriver protocol and Chrome Devtools protocol, making it efficient for both Selenium Webdriver based cross-browser testing or Chromium based automation. As WebDriverIO is open source, you get a bunch of plugins for your automation needs. ‘Wdio setup wizard’ makes the setup simple and easy.
3. Citrus Citrus is an open-source framework with which you can automate integration tests for any messaging protocol or data format. For any kind of messaging transport such as REST, HTTP, SOAP, or JMS, Citrus framework will be suited for test messaging integration. If you need to interact with a user interface and then verify a back-end process, you can integrate Citrus with Selenium. For instance, if you have to click on a “send email” button and verify on the back end that the email was received, Citrus can receive this email or the JMS communication triggered by the UI, and verify the back-end results, all in one test.
4. Cypress Cypress is a developer-centric test automation framework that makes test-driven development (TDD) a reality for developers. Its design principle was to be able to package and bundle everything together to make the entire end-to-end testing experience pleasant and simple. Cypress has a different architecture than Selenium; while Selenium WebDriver runs remotely outside the browser, Cypress runs inside of it. This approach helps in understanding everything that happens inside and outside the browser to deliver more consistent results. It does not require you to deal with object serialization or over-the-wire protocols while giving you native access to every object. Cypress can synchronously notify you of every single thing that happens inside the browser as you’re pulling your app into it, so that you have native access to every DOM element. It also makes it easy to simply drop a debugger into your application, which in turn makes it easier to use the developer tools.
5. Selenium
One of the most popular open source test automation frameworks for web apps. Selenium also serves as a base for a lot of other testing tools as it has cross-platform and cross-browser functionality. Selenium supports a wide range of programming languages such as Java, C#, PHP, Python, Ruby, etc. It is easy to maintain as it has one of the largest online support networks. Selenium is highly extendable through a wide range of libraries and APIs to meet everyone’s needs and requirements. Selenium is preferred by testers as it is possible to write more advanced test scripts to meet various levels of complexity. It provides a playback tool for test authoring without the need to learn a specific scripting language.
6. Cucumber
It is a cross platform behavior driven development (BDD) tool which is used to write acceptance tests for web applications. Cucumber is quick and easy to set up an execution and allows reusing code in the tests. It supports languages like Python, PHP, Perl, .NET, Scala, Groovy, etc. Automation of functional validation in easily readable and understandable format. One good feature is that both specification and test documentation are uploaded in a single up-to-date document. Cucumber makes it easy for the business stakeholders, who are not familiar with testing, as they can easily read the code as test reports are written in business readable English. The code can be used together with other frameworks like Selenium, Watir, Capybara, etc.
7. Gauge
It is an open source tool agnostic test automation framework for Mac, Linux and Windows. People who work on TDD and BDD will appreciate Gauge’s focus on creating living/executable documentation. Specs – the Gauge automation tests are written using a markdown language with C#, Java and Ruby within your existing IDEs like Visual Studio and Eclipse. Gauge’s functionality can also be extended with its support of plugins. It was developed as a BYOT (Bring Your Own Tool) framework. So you can use Selenium or you can use anything else for driving your tests UI or API tests. If you want a readable non-BDD approach to automation, you should try Gauge.
8. Serenity
If you are looking for a Java-based framework that integrates with behavior-driven development (BDD) tools such as Cucumber and JBehave, Serenity might be the tool for you. It’s designed to make writing automated acceptance and regression tests easier. It also lets you keep your test scenarios at a high level while accommodating lower-level implementation details in your reports.
Serenity acts as a wrapper on top of Selenium WebDriver and BDD tools. It abstracts away much of the boilerplate code you sometimes need to write to get started which makes writing BDD and Selenium tests easier. Serenity also offers plenty of built-in functionality, such as handling running tests in parallel, WebDriver management, taking screenshots, managing state between steps, facilitating Jira integration, all without having to write a single line of code.
9. Carina Carina is built using popular open-source solutions like Appium, TestNG and Selenium, which reduces dependence on a specific technology stack. You can test mobile applications (native, web, hybrid), WEB applications, REST services, and databases. Carina framework supports different types of databases like MySQL, SQL Server, Oracle, PostgreSQL, providing amazing experience of DAO layer implementation using MyBatis ORM framework. It supports all popular browsers and mobile devices and it reuses test automation code between IOS/Android up to 80%. API testing is based on the Freemarker template engine and it provides great flexibility in generating REST requests. Carina is cross-platform and tests may be easily executed both on Unix or Windows OS.
10. EarlGray
Developers often face difficulty with some of the existing test automation framework in synchronization of the app and the instrumentation. Also, executing tests on apps as synchronized and advanced only when UI elements are visible on the screen has caused issues for many developers. Google EarlGrey has built-in synchronization that makes test scripts wait for UI events to occur before the script tries to interact with the UI of the app. This type of implementation makes the test script concise as all steps of the test script shows how the test will proceed and UI gets synchronized with it. One more key aspect of EarlGrey is that all actions on UI elements happen only on visible elements. This provides a fast and robust approach to ensure UI testing goes through as clicks, gestures and other user interactions do not get done if the UI element is not fully shown.
In a nutshell
This list of top tools here represents the best tools that are mature, popular, and provide test automation capabilities using AI/ML to address the challenges that organizations are now facing to deliver Quality at Speed. This list also includes the tools that provide API and services testing which is essential for successful DevOps transformation. The emerging technologies like AI, codeless, big data and IoT testing, are making test automation more efficient while creating opportunities for the existing tools and new players to assert value to the testing communities.
The choice of automation tools should not only meet your current needs but should also focus on potential trends and improvements. An efficient test automation tool should support basic optimization, data generation, smarter solutions, and analytics. As of now, the level of test automation in organizations is low at between 14% and 18%. But organizations are working towards increasing the automation coverage upto 80%. API and services testing is also a trend that should see further development in the future.
With Appium creating a buzz in enterprise mobility, mobility teams are still finding ways to successfully automate tests leveraging Appium. Appium being an open source tool is the perfect choice for automating native, mobile web and hybrid applications on their respective platforms.
Let us now see the major factors behind Appium being the best choice for mobile automation tool:
An impressive expression by Appium.io showing why to choose Appium
1. Use of standard API: Appium is widely popular because modification of codes or a recompilation of your app is not required as it uses the standard API in all the platforms. Appium makes it effortless to create your tests against iOS and Android platforms with same API. But, separate iOS and Android scripts are still needed as the UI elements vary on both the platforms.
2. Use any WebDriver compatible language: Appium gives the freedom from getting locked into a particular language or framework to write and run the tests. Any WebDriver compatible language like Perl with Selenium WebDriver API, Java, PHP, C#, Python, Ruby, Javascript with Node.js can be used for writing the tests.
3. Testing Framework of Choice: Appium gives flexibility to mobility teams to use testing framework of their choice. Earlier, tests could only be written through Javascript using the UI Automation of library for Apple or Java based tests could only be written through UI Automator of Google. Appium completely changed this scenario.
4. Cross-platform test automation: Having the capabilities to test on both Android and iOS devices makes it the best cross-platform mobile app test automation tool. In order to interact with Android and iOS with Selenium WebDriver, Appium uses the JSON wire protocol. Appium makes use of the libraries provided by Apple with the help of an application called Instruments to automate iOS apps. In newer versions of iOS after v9.3, the Instruments api has been deprecated and now use XCUITest framework.
The method is similar in Android also where Appium proxies the automation command to the UIAutomator test case running on the device. Android has a native UI automation framework called UIAutomator which supports running JUnit test cases from the command line directly into the device.
5. Open Source: Being an open source testing framework is one of the biggest advantages of Appium as it supports Simulators, Emulators, real devices, and of course, native, hybrid and web application testing of iOS and Android. Appium having a large and thriving open community makes it easier for new automation engineers to clarify their doubts.
You can instigate test scripts created from Appium libraries locally, on a session reserved by the Cloud, for any iOS or Android device. Appium integrates with continuous integration servers to ensure better results and drives GUI-related widgets and controls, allowing the same scripts to run for different software versions of various apps. Appium can automate native, web and hybrid mobile apps, and you can test on a real device, a simulator, or an emulator. It also supports Safari on iOS and Chrome Mozilla or any built-in ‘Browser’ app on Android.
There are many automation tools for mobile application testing. Testers usually choose Appium as the best mobile testing tool. Mobile automation testing tools comparison can be done on the basis of language support and continuous integration. The most common automation testing tools used for mobile application testing are Appium, Robotium, and Calabash. If you are looking for iOS app automation testing tools then Appium and Calabash can do the job for you.
Here is tabular representation for you to understand Appium’s compatibility with different features and tools.
Teams who are getting started with Automation or are considering Appium as an option, must explore an alternative to go for a mobile device cloud with built-in Appium.
A mobile device cloud not only assists in managing and sharing devices, but also helps in streamlining automated testing and continuous delivery processes. A mobile device cloud with built-in Appium makes it easy for teams to get started with automation and scale up later. Furthermore, it will give additional cushion against any sort of roadblock that might occur while using an open-source platform for tests. Let’s have a look at some of the benefits of having a built-in Appium support on a mobile device cloud:
At pCloudy, we are dedicated towards helping enterprise mobility teams make the process of mobile development, testing and device sharing seamless and faster by integrating it with cutting edge tools like Appium. Read this blog to get a comprehensive analysis sheet to quickly choose which open-source test automation tool will be right for your automation testing.
Sign up on pCloudy and automate your tests using best open source automation tool for faster and better delivery of apps.
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.
In today’s organizational environment, ‘DevOps’ is the most used buzzword and has become a part of its agile software culture. Organization’s DevOps success is not a single goal approach; it requires deeper involvement for making a switch to DevOps. Broadly, it requires adoption of new DevOps automation tools, contemporary processes and cultural shift, especially in case of Mobile DevOps tools selection. A business has to be equipped with ever-evolving principles and DevOps automation tools in order to embrace these steps to successful DevOps test automation.
There are multiple Mobile DevOps Tools with different strengths contributing to a reliable Mobile DevOps process. Today, the businesses and the development teams are investing in intelligent systems that are capable of monitoring the production and development metrics in real-time. This acts as great deal for the development firms unless it covers all important aspects of the process allowing perfect optimization of the resources based on the reports.
The journey from planning, development, deployment and beyond, generally called ‘shift left’ process which is a part of continuous testing. In this approach, the testing is mostly focused on earlier stage of production life cycle aiming at delivering applications faster and with much lesser time and money. When it comes to mobile apps testing, the shift left approach works well because the application has to be tested well in order to perform well in the real-environment. In case of Mobile DevOps, using production environment to test the mobile application on real physical devices would help highlight and fix issues in the earlier phases of SDLC, reducing costs and time.
Gone are the days when testing was only executed as a final step of the processes where as nowadays, it has to be performed after every build, at every stage of the process. It is with the help of multi-step testing and maximum data capture after each test cycle, that the status of development and testing hasn’t been compromised enabling early bug-fixing and building more strong applications especially when this process is simplified with the help of DevOps automation tools. DevOps and Automation go hand in hand. Despite many challenges, it carries a much strategic role to bring the whole business making faster and better applications. A developer has to have a combination of agile development methods along with Mobile DevOps to win in mobile application; this can be achieved with the help of right DevOps automated testing tools.
Below are the 7 most common Process Steps with Mobile DevOps Tools:
CODE
Anything related to real development is related to continuous integration whether it is code development or code reviews. The way developers work today by collaborating; integrating all the things together is all a gift of the agile approach which is responsible for making continuous integration popular. With the adoption of continuous integration early stage issues are detected which ultimately reveals any integration glitches, faults in the code commits, etc. It generates a lot of data required for making right choices to be made by the developer as it showcases a lot of data about the mobile application that the developers can use to make the code better. This thus ultimately helps in estimating the scheduling and time consumption more accurately.
BUILD
Build is nothing but application components that are collected repeatedly and compiles for the purpose of testing to produce a reliable final software product. This is not a one-time job, instead it is a developer’s everyday task of creating various builds of applications. In Mobile DevOps scenario, in order to notify the status of the build, the developers use various version controls and source code management techniques. Software Engineers normally follow branching techniques in case of Mobile DevOps like no branching, release branching, maintenance branching and branching for features.
TEST
Testing is something that acts as a backbone of building a quality product. It is the QA team that is responsible of maintaining the sanity of the software, detecting errors early and quick bug fixing. Testing is the most integral aspect of SDLC. Considering the Continuous integration principles, automation testing needs to be automated in order to enjoy the seamless results i.e rich and flawless application. Testing in Mobile DevOps for a production environment should always be performed on real mobile devices and not on Simulators.
PACKAGE
Packaging in Mobile DevOps is already known. It is all about tools for package repositories and storage mechanisms for the binaries created during the software build. Binaries like scripts, configuration files and other files facilitate deployments; these are contained in the asset repositories. Continuous deployment eases the application testing and production with the help of automation, flawlessly. Packaging enables the releases of new versions and features of applications to the end-users.
RELEASE
In Mobile DevOps process, there are myriad of tools that are used in aiding in the process of CI/CD and continuous release. As a part of this, there are application release tools as well that help in packaging and deployment of an application right from the development to production, to be available to the final users using automation. Release management is a critical expertise which involves planning of every release and deployment by easy collaboration with the stakeholders. This is accomplished with the usage of release management tools that help stakeholders to plan and execute and trace the releases from a single platform.
CONFIGURE
Configuration is a second name to Infrastructure as a Service. Configuration tools enhance the cost-effectiveness and create applications with better flexibility and performance. The aim of this process step is to remove any unwanted manual configuration. In DevOps , the focus is on automation and collaboration, so configuration being a part of the ecosystem is also automated across various development flows.
MONITOR
Without valid data, no corrections and improvements can happen. Thus, monitoring becomes a very important aspect of the Mobile DevOps ensuring that the organizations get the right metrics about the processes, stage wise results and final outcome. Continuous monitoring allows stakeholders, developers, testers and other people involved, the access to right information for evaluation and decision making. This step is guide to all teams involved and has an impact on all the other steps. Thus making it a critical process step with Mobile DevOps tools.
Traditionally, the Process Steps involved planning, developing, testing and deploying but this is not it, there are many more aspects to it that are the key deciders in selecting the tools and how they fit together to enable tool flow in SDLC. DevOps test automation helps in achieving integrated development and delivery using the right combination of DevOps automated testing tools.
Healthcare organizations are largely dependent on digital technology to deliver quality products and services. In the last 5 years, we have seen the healthcare sector going through a digital transformation and mobile apps are at the core of this transformation. Healthcare mobile apps are used by patients as well as healthcare professionals to handle daily tasks like medical references and maintaining databases. Meeting the quality standards set by healthcare regulatory authorities like FDA is crucial as in many instances, people’s lives are at stake. So let’s see how mobile apps are helping healthcare companies to enhance productivity and deliver quality services.
The Evolution of Mobile Healthcare Apps
Since the arrival of smartphones, we have witnessed a rise in the number of mhealth apps and the type of services they offer. In the initial stages, we saw apps that offered information about the healthcare centers in the vicinity and these apps also provided the option to book appointments. The advancement in mobile and wearable technology opened the doors for healthcare organizations to unleash their full potential.
In the last couple of years, enterprises are using technologies like AI and predictive analytics to develop better mHealth apps. Now we can see a variety of mHealth apps in the market providing different solutions to the healthcare professionals and the patients. Let’s have a look at the categories of mHealth apps that we can find on Google Play Store and Apple App Store.
The most downloaded apps are among healthy lifestyle and women’s health categories. Smart fitness bands are in trend these days and fitness tracking apps are also one of the most used apps around the world. Apart from this, apps that provide health insurance services also come under mHealth apps. It bridges the gap between the policyholders and the insurance company by providing all the information on the fingertips.
Challenges in healthcare app testing
By the first quarter of 2020, there were more than 45,000 mHealth apps available on the app store. This shows how competitive the market has grown in recent years. But to stay ahead of the competition you need to overcome the challenges in testing and deliver a quality app. So let’s look at some of the major challenges in mHealth app testing.
Meeting the usability expectations
Whether it’s patients or healthcare professionals, usability is the most sought for quality in a mHealth app and EHR systems are a good example. So if the app is being built to maintain and search health records or to recommend a nutritional diet, the app should be convenient to use for all age groups.
There can be emergency scenarios where an elderly patient needs help and the app needs to alert the doctor or the caregiver. In this scenario, the elderly patient should be able to tap on the button quickly or the app should have a function to initiate a video call so that the caregiver can help the patient without wasting time.
This was just one scenario where only the caregiver and the patient were involved. But a healthcare app can be multifunctional and can be used by other stakeholders like administrative staff, insurance advisors, nurses, and more. This is why testers need to make sure that the app supports different workflows by creating user stories and scenarios as per the user’s needs. For instance, an insurer might want to track a patient’s treatment plan activities, including tests, office visits, and procedures remotely. While a physician might want to review a patient’s treatment progress remotely. Also, a caregiver should be able to access the supervisee’s current health status remotely.
Some patient management apps might need to access their medical documents to monitor the care receiving activity. In such cases, testers and developers can create a list of documents that can be accessed by the caregiver using some category filters. The documents can include medical prescription, procedure notes, lab and imaging results, consent forms, identification form, and medical conditions.
Building a foolproof app
It is crucial to develop a secure healthcare app that can withhold all the confidential data safe from malicious attacks, viruses, and other types of security breaches. To achieve this level of safety the app needs to be compliant with a legislative regulation like HIPPA.
The Health Insurance Portability and Accountability Act focuses on the security and privacy of confidential healthcare data and testers need to have knowledge of this act to make the app compliant. Some of the key areas to focus while checking the app’s HIPAA compliance are access control, encrypted data transfer, audit log, data sanitization, load testing, and information on correct/incorrect data usage.
Ensuring quality in healthcare apps
Overcoming the challenges in healthcare app testing is essential but not enough to deliver a quality healthcare app. There are certain aspects of healthcare apps that need to be taken care of. So let’s take a look at the best practices that we need to focus on to achieve the level of quality that users expect from a healthcare app.
1. Continuous testing
Continuous testing gives you the confidence you need to meet the user expectations from a healthcare app. By implementing continuous testing you will be testing the code continuously at each and every step of the testing cycle. Continuous testing also means that you will use automation often to reduce the chances of human error while reducing the release cycle. The added advantage of shift left in testing will result in test automation scripting and defect identification in the coding phase resulting in a superior quality build. The best way you can deliver a flawless app is through implementing continuous testing.
2. Data confidentiality
While testing healthcare mobile apps, authentication, and user authorization process has to be given due attention. But there are still some areas that a quality engineer sometimes forget like report generated data and departmental boundaries. Restrictions on data availability should be implemented in the main EHR (Electronic health record) work process of an app. Also, protected health information (PHI) should be available for the patient care team. EHR restrictions should be included in the reporting module for drill-down reports. Reporting is regularly executed as a part of the data warehouse. If the caregiver does not access the patient’s data then the relevant PHI fields must be concealed.
3. Test Data Management
To get better test coverage and get better results of testing you need diverse test data. Especially in the case of testing clinical and non-clinical workflows through test automation. Therefore for successful automation testing of healthcare apps, you need to have production-like data including the inconsistencies that might be there in the production data. The app should be able to retrieve data swiftly whenever required. Protected health information must be organized to assure compliance. The data that mirrors its authenticity in production must be the foundation of a current test data management strategy.
4. User experience
Attributes of usability should be fixed prior to reaching the testing phase. However, a QA is not directly responsible for this. IT must be focused on the issues related to the usability, during the QA process. The reason is that IT adoption is the biggest issue in healthcare, unlike other sectors. Similarly, usability related problems can give rise to clinical issues. A recent example of this is when a patient in UCSF Benioff Children hospital got overdosed by 300%. The main reason was that the medication management interface was unsuccessful in preventing the user from committing the mistake.
5. App performance
Health apps usually serve a small number of users in a definite geographical boundary, unlike social media apps that have users across the globe. Still, a healthcare app should go through a rigorous load and scalability testing process. There can be scenarios where the user traffic might spike and the app should be able to handle the load smoothly. insights from performance systems would assist product managers to define areas such as archival strategy, local data size, scalability model, and so on. If the mHealth app does any CPU intensive actions or uses storage more often then there must an extensive evaluation of its performance.
In this blog we shared insights into the evolution of mHealth apps, challenges in healthcare app testing and ways to ensure quality in healthcare mobile apps. But to implement the new healthcare app testing trends, enterprises are opting for cloud solutions. A cloud testing platform like pCloudy provides the option to test healthcare apps on hundreds of real devices from anywhere, anytime. Refer to our case study where you will see how pCloudy helped a US-based multinational to achieve accelerated app adoption. In the recent turn of events, the flexibility of testing apps from anywhere in the world is much required. And you can make sure that you deliver a great app using next-gen features like an autonomous testing bot and Wildnet.
Some testing teams set up their own staging environment to test internal servers but as there is no public access which makes it difficult to perform local testing on remote devices. So how would you test your app which can be accessed through your internal network? We launched a feature called Wildnet, that enables you to test private or internal servers using pCloudy. You can test your privately hosted apps on any Android or iOS devices and implement continuous testing to ensure reduced release cycle.
Some times testers want to test their internal servers to protecting unsecured data and credentials, hide new features, and general security. But if an app hasn’t been made public, it should not delay testing across environments. When the Wildnet feature is enabled, a secure connection is created between your machine and pCloudy remote devices so you can perform testing even if the devices are connected remotely.
Let’s see how you can test local or private servers using Wildnet.
Prerequisite:
User should be registered on pCloudy platform
Executables can be downloaded from below links
Once “Wildnet” is enabled, the user can connect more than one device.
User will get authenticated as shown in the below screenshot
This is how users can initiate Wildnet.
2. Go to the Device page in pCloudy platform, connect the device and click on Enable Wildnet as shown in the screenshot:
Open any local URL that you wish to test and enjoy local testing on pCloudy platform.
3. To disable the service simply run ctrl+c to exit
Activating Wildnet for Appium Automation
1. Run the below mentioned executable command on the terminal:
For Windows:
.\pCloudyWildNetWindows -i Emailadress –k accesskey -u URL
For Mac:
./pCloudyWildNetOSX -i Emailadress –k accesskey -u URL
For Linux
./pCloudyWildNetLinux -i Emailadress –k accesskey -u URL
3. Once the capability is added, users can perform local testing on pCloudy devices and verify the execution in live view page.
The most important advantage of Wildnet is that you can be confident about the application as you can rectify all the defects prior to delivery. Try it yourself. Use Wildnet to find more bugs and defects in your internal server before deploying it to production.
As the world battles with turbulent, uncertain times, most of the workforce across the globe is working remotely. Organizations have acknowledged the importance of remote working as it helps in maintaining business continuity. But in some scenarios, it is difficult to maintain business continuity or distribute resources within the teams while the team is working remotely.
For instance, if you have some physical device infrastructure to test your app on multiple mobile devices, how would you do it? How would you share the devices with other testers and developers in your team working from different locations? Most importantly, how will you make sure that the app works smoothly on all the popular devices? We will address these issues in this blog, so buckle up for some interesting insights into the remote testing advantages that can ensure a better app experience for your users.
1. Abate device fragmentation and ensure better app compatibility with remote testing
Device fragmentation is any testers Achilles heel as it limits their potential of extensive testing. Testing from a physical device lab at this global lockdown situation is not feasible, and testing on a few devices won’t yield good results. But this issue can be rectified by testing on a device cloud. In pCloudy, users can test on multiple devices based on the popularity of devices in a particular region and its penetration to get the optimum device coverage.
Both manual and automation testing can be performed with unlimited parallel test runs remotely on hundreds of real devices. This is also convenient for globally distributed teams, as the users won’t have to wait for the devices to be available for testing.
2. Deliver Better Quality App with Rapid Automation
Enterprises can ensure better quality apps without missing out on any deliveries by leveraging remote devices for automation testing. pCloudy helps in speeding up automation testing with codeless scripting and test orchestration using integrated tools like Jenkins. Capability configurator is a feature in pCloudy that generates the desired capability based on a set of filters, which saves time and effort while performing test automation. Integration with popular automation and collaboration tools like Appium, Espresso, Jira, etc., makes it convenient for users to perform automated testing on remote devices.
3. Better collaboration and continuous feedback
In pCloudy, users can manage teams and distribute credits among themselves. The user management feature allows managers to become the system administrator and create teams to allocate the credits to the members according to the task assigned. This helps in user and task as the hierarchy is maintained to distribute workload systematically.
Once the tests are complete, detailed test reports are generated automatically, which can be easily shared across the team. The progressive reports also show the tests failed, passed, and those with errors. This helps in focusing only on the tests that failed and doing a root cause analysis to rectify the issues. Continuous access to a range of devices available for remote testing will provide stability to your CI/CD pipeline.
4. Assured data privacy and security
Enterprise-grade security gives assurance to our users that their data is safe on the cloud platform. Our data centers comply with internationally recognized security standards like ISO27001, SOC2, and SSAE-16. Keeping your security issues in concern, we have another useful feature called Wildnet. This feature enables you to test your internal sites or apps on your local network, keeping all your data and information secure.
5. Advanced features to improve manual testing
Take advantage of next-gen features like Certifaya, an AI-powered autonomous testing bot to save time and effort. FollowMe is another feature that enables the user to run a test on multiple devices in parallel. This will save your resources while reducing the testing time by multifold. Apart from this, there are many features in pCloudy, like taking screenshots, recording the test video, cross-browser testing, etc. that will make manual app testing a piece of cake.
In a Nutshell
Remote testing is convenient, and it will help you save big bucks while you deliver a better quality app in less time. Continuous access to numerous devices helps in accelerating automation testing, as the app can be tested on multiple devices in parallel. All these advantages of remote testing make it the optimum choice for enterprises.
Automation testing forms the core of any CI/CD pipeline and enterprises are keen to practice test automation to enhance the efficiency of the development process. Test automation saves resources and reduces the cost of any project in the long run. But there are some important points to keep in mind while testing to avoid automation failure. Let’s have a look at these salient points.
Leverage Parallel Execution
Once you are done automating the test cases, the challenge will be the complex test suites taking a long time to get executed. It affects the quality of the test queue in the test automation framework or IDE. This leads to queue timeout issues and test cases being halted abruptly due to the sequential execution of the test cases.
Parallel execution in different test environments is preferred over sequential execution as it saves a lot of time. Although in automated testing, unintended code interactions could happen. This is why you need a thorough reporting mechanism to debug the causes of test failure.
Pick The Right Tools
Choosing the right tool for test automation is critical to the success of automation testing. There has to be a set of clear requirements/parameters on the basis of which the tools have to be selected. Some important points that are to be kept in mind while selecting the tool are:
The team should be clear about the test tool requirements.
The testing requirements of the application under test (AUT) should be analyzed thoroughly.
The team’s skill set should be accessed accurately.
The cost-benefit analysis should be performed to calculate the return on investment.
Tool vendor and capability should be evaluated as technical support might be required while using the tools.
One tool might not be enough to meet any organization’s automation needs. Also, test automation engineers have to be a part of the tool evaluation process so that they can help in selecting the right set of tools. For example, you can use Appium for test automation but you need pCloudy to perform automation testing on multiple real devices in parallel.
Analyze The Test Reports
Test reports provide insights into the underlying issues that are to be resolved. A detailed test report gives an idea of the efficiency of the test automation and the automation team can analyze the report to look for the scope of improvement. While selecting an automation tool you need to make sure that the tool generates test reports to be analyzed by the test automation engineer. There will always be some tests that will fail to execute and it is necessary to analyze the test report to get an understanding of the scenario.
Test Automation Metrics
Test automation metrics will help you gauge the quality of the tests performed based on some essential parameters like test duration, unit test coverage, path coverage, number of defects found, percentage of broken builds, etc. The test metrics will give you a clear picture of how well the code is tested. In an agile process, there are frequent iterations to the builds and it becomes important to track the quality of each build. With test automation metrics you can figure out what is the percentage of your tests that passed and what was the reason behind the failed tests.
Optimum Device Coverage
Test automation is effective when the tests are executed on multiple devices in parallel. Device coverage is the most prevalent challenge as we have witnessed growing device fragmentation across the world. To ensure the smooth functioning of mobile apps on all the devices, you need to perform automation testing on hundreds of device-OS combinations.
Test automation should be designed to make the app compatible with most of the popular devices. The frequent release of new versions of OS from both Android and iOS is a major factor that drives device fragmentation. The only way to overcome this challenge is by testing the app on a cloud-based testing platform. In pCloudy, you will get the benefit of testing the app on more than 5000 device browser combinations in parallel ensuring optimum device coverage.
Summing It Up
Test automation has many benefits like better test coverage, faster feedback, and accelerated results which reduces the time to market of any application. Using the practices mentioned above you can ensure coherent test automation and increased productivity. Apart from these points, there are many other things you can do like writing original code and not copying it as the code taken from other sources might not work in your test environment. But you will always find new roadblocks which you will have to deal with spontaneously.
