The core objective of agile methodology is to develop and deliver products faster. As businesses embrace test automation in agile software development, the overall productivity and deployment of software development activities accelerate to deliver high-quality software. Businesses get a fully functional, bug-free, and flawless product as a final product.

However, implementing the right automation testing tools plays a vital role in enhancing the effectiveness of the agile and DevOps implementations.

Content

1. What are Agile software development methodologies?
2. Where does test automation fit into agile development?
3. Four key factors that depict the importance of test automation in agile ?
4. Benefits of implementing test automation in an agile environment
5. How to implement test automation in agile?
6. What tests can be automated in agile?
7. Five major automation testing tools businesses can leverage
8. Conclusion

Agile software development methodologies

Agile software development methodologies include Scrum, Kanban, Extreme programming, Lean development, and Crystal development.The scrum method is an important agile methodology wherein the development and testing activities are run parallelly within sprints.

A set of features are released in each sprint during the agile process, and continuous development and testing are performed to ensure faster releases. But, to ensure faster and quality releases, manual testing does not suffice in the latest agile and DevOps scenarios. Thus, businesses should embrace test automation using the latest automation tools to carry out the testing in an agile environment.

Where does test automation fit into agile development?

The product is developed in iterations during the agile development, and testing is done within sprints. Each time a new feature is added to the software, the software needs to be tested again to ensure there are no bugs. Testing each feature manually becomes almost impossible for the QA team with so many new features added. Hence, automation testing should be leveraged for faster testing outcomes in agile development. Businesses should leverage various automation testing tools, such as Selenium, TestNG, Appium, Tricentis TOSCA, etc.

During automation testing, testers need to develop test cases according to the needs of the software to be tested. These test cases can be executed multiple times while performing continuous integration or continuous builds. This form of automation testing ensures that the software remains bug-free, and even if a bug is introduced, it can be easily identified in the early stages and can be fixed early.

This form of automation testing ensures that the software remains bug-free, and even if a bug is introduced, it can be easily identified in the early stages and can be fixed early.

Four key factors depicting importance of test automation in agile

Test scripts reusability

Automated test cases can be reused, which means these test scripts can be re-run several times in different ways. This test reusability will reduce the maintenance costs to a great extent. The application of reusability eliminates human errors and saves cost.

Optimal test coverage

Test coverage plays a vital role in improving the efficiency of software testing activities. The depth and scope of tests are increased through automation testing activities. This is because testers need not run all the tasks manually. Instead, the testers can create a test suite for every feature of the application, such as internal programs, data tables, and memory contents.

By leveraging automation testing, complex test cases can be automatically run, ensuring better and faster test coverage. The manual testers’ work is reduced, and they can be used for other important tasks.

Faster test execution

The efficiency of the development process is significantly improved by the test automation process. Testing is done parallel to development to ensure all the bugs and issues identified are resolved at the earliest. Further, this sort of testing is also known as the ‘Fail Fast’ method, wherein as the defects are found early in the SDLC, they can be fixed early, and it also saves a lot of time.

Typically, if the automated testing is performed from the initial unit testing phase, then the defects can be found early and fixed, rather than fixing them at a later stage. Moreover, the time-to-market of a software product is also drastically reduced through the application of continuous testing. Developers and testers can save time and ensure to deliver a high-quality product at a quicker pace.

Cost-effectiveness

At the initial stage, the cost of test automation will be more as the required training, tool cost, and tool setup needs to be taken up to ensure effective test automation. However, with the test automation once set up, the cost factor will be reduced as the automation activity goes on for a longer time.

Further, without investing any additional costs, test cases can be run several times as and when required, thereby improving the overall speed and efficiency of the software testing activities.

Benefits of implementing test automation in an agile environment

•Parallel testing can be performed wherein the same scripts are run on different devices

•When the testing is done using test scripts, the reliability factor is scaled up to an all-new level

•Agile software development can be carried out at a faster pace through the strategic application of test automation

•Initially, the costs are high for implementing test automation in agile, but, eventually, the ROI is more

•If a specific test script is developed, it can be used several times to test the software for bugs.

•Test automation is an innovative way for carrying out agile methodologies cost-effectively and efficiently. Thus, it helps to improve the overall software testing activities by enabling a high-quality product in a shorter time with faster releases.

How to implement test automation in agile?

Develop an effective plan for agile automation

For the success of an agile project, it is essential to prepare an automation testing plan that must cover the automation framework and. Also, ensure a proper collaboration between QA and the development teams.

Determine the test cases that can be automated

Not all test cases can be automated; therefore, identify the test cases that can be automated beforehand.

Conduct parallel testing

With automation in place, QA teams can execute several tests on different devices, browsers, and operating systems simultaneously. Specifically, parallel testing saves a good amount of time for the teams.

Adopt DevOps Integration

DevOps ensures proper collaboration between developers and operation teams. Also, testers can integrate the automation tool into CI/CD pipelines for effective testing.

Select the right automation tool

Testers should select the right test automation tool (open source or commercial tools). Test automation tools reduce regression testing time and ensure faster testing outcomes with high-quality software. However, while selecting the test automation tool, testers should ensure that the tool matches their technical skills, software testing needs, current IT infrastructure, etc.

What tests can be automated in agile?

•Unit tests

•Smoke tests

•Integration tests

•Regression tests

•API tests

•Security tests

•Accessibility tests

•Performance tests

Automation testing tools to leverage

•Selenium

•Tricentis TOSCA

•Appium

•TestNG

•Katalon Studio

Conclusion

Automation testing helps QA teams create test cases that run automatically when new code is pushed to the code repository. Automation testing also scales up the agile development activities if combined with the right tools, expertise, and an effective automation testing roadmap.

Leverage the test automation services from a next-gen testing services provider to get high-quality products with a faster time-to-market and quicker ROI.

The post Importance of Test Automation in Agile first appeared on TestingXperts.

Software testing industry is becoming extensive with each passing day. Applications these days have started interacting seamlessly with other applications through APIs. With the sudden increase in the technology challenges, applications are growing in complexity, which creates an incessant need for effective software testing.

Contents 1. Importance of Artificial Intelligence 2. Why do we need Artificial Intelligence in Software Testing? 3. How Artificial Intelligence benefits software testers? 4. What are the AI tools for software testing? 5. In Conclusion

Software testing is the only premeditated way where an application can be observed under certain conditions and where testers can recognize the risks involved in the software implementation. Testing, on the other hand, is gradually transitioning to greater automation to ensure maximum precision and accuracy in the journey towards digital transformation. In an attempt to make the application foolproof, the world is turning towards Artificial Intelligence (AI). This implies that instead of manual testing and human intervention, we are moving towards a situation where machines will be slowly taking over.

Importance of Artificial Intelligence

Simply put, Artificial intelligence (AI)is the science behind computers performing tasks that are traditionally performed by humans. AI provides machines with the skill to process information about its conditions and learns to adapt to the transformations with problem solving techniques. Machines are learning faster than ever given the technology advancements. The computer is fed with a huge amount of data to adapt as per a set of inputs so that it can identify patterns and logic and as a result make an effective connection between similar input and output pairs. It is through machine learning that websites like Amazon and Netflix are able to deliver targeted ads to their customers by using huge amounts of data based on the web pages the customer searches. Personal assistants like Google Assistant, Alex, and others use AI technology extensively to deliver results.

Machine Learning has come a long way with people using it to drive cars without a human. Artificial Intelligence (AI) has become quite famous in the field of healthcare also as it is used to identify cancerous tumors. As Artificial Intelligence begins to progress, technology experts across the globe are finding ways to leverage its potential in the software testing field as well. It is only a matter of sometimes when training applications to be familiar with problems for agile and more efficient testing becomes a reality.

Why do we need Artificial Intelligence in Software Testing?

Software testing is usually a time-consuming process. Artificial Intelligence ai is the best choice for developers looking for faster deployments with insufficient infrastructure. It is best to leave the arduous work to the Artificial Intelligence-powered automation which leaves only 20% of the testing work to human ingenious and cognitive ability. It would ensure more fail-safe results as hand-crafted testing does not only require extensive human hours but is also susceptible to imprecisions and discrepancies.

How Artificial Intelligence benefits software testers?

Reduces the test-cycle time:

With the AI methodology, it is easier for a tester to understand which test cases are required to be executed in each test cycle. AI is efficient in gathering data from the previous test executions made for the application. This helps AI to easily identify when any changes are made in the code. Also, it automatically states the test suites as per the application risk. The application risks are defined by considering several factors such as the most used parts of the application, tests having the risk of failure or complexity, etc. This way of finding defects at earliest and running the test cases that can get affected at the start of a test cycle helps to receive faster feedback from delivery teams and ensures to find solutions when any defects are identified.

Helps to find bugs faster:

Unlike the traditional test methods, the AI methodology is an expert to find the defects faster in applications. In the previous methods, error detection was at the later period and this resulted in several drawbacks for the app before its launch. AI helps in automating the processes, it automatically corrects the code and assigns bug tracking to the QA teams. This effectively benefits the teams to track the errors at the earliest and achieve a bug-free app before production.

Encourages Script Execution:

There is no need to perform a test script automation when using AI because test scripts are executed automatically by the AI. Also, it enhances test cases to be more stable so that there won’t be any change experienced when the locators get changed.

Improves the speed of Test Coverage:

AI is efficient for increasing the scope and depth of the test cases. AI monitors the memory, file contents, internal programs, and data tables of the app to verify the functionality is as needed or not. Also, with the use of the AI-powered test automation tools, thousands of test cases can be executed in one test run. This ability of AI effectively helps in speeding up the test coverage.

Reduces Costs Requirements:

Bugs or the errors in the application can become expensive when they are not resolved at the earliest. With the help of AI, instant feedback can help to find and resolve the errors at the earliest and this significantly helps in cost savings. In addition to this, AI is even more efficient to sort files, detect errors and scan code at a lesser time. This reduces the effort of manual work and human errors and thus, yields more accurate results at a lesser cost. 

Improves Accuracy:

A well-experienced tester can even make mistakes while carrying out repetitive tasks in manual testing. This is the reason automation came into effect to reduce the scope of repetitive tasks. When automation is powered with AI, the repetitive tasks are performed by the AI and the testing teams are provided with the scope to perform exploratory activities and find automation solutions. Thus, the time consumption is reduced and the accuracy for achieving quality results increases. 

What are the AI tools for software testing?

– Functionize

– EggPlant AI

– AppVance

– Testim

– Applitools

– TestCraft

– Test.ai

In Conclusion

Digital Transformation is becoming impossible without the implementation of new and emerging technologies. The consumer market has become dynamic, organizations that do not leverage these technologies will end up way behind in the race. Businesses need to experiment and innovate to make their product success with the end-user. This can only be possible when these technologies are tested extensively against the odds and under all conditions.

TestingXperts brings machine learning together with analytics to unleash the power of software testing and drive automation and innovation, consequently improving QA efficiencies. Our intelligent frameworks are based on industry best practices and standards, to efficiently evaluate clients’ testing maturity. Connect with our experts to understand and improve all QA focus areas across the delivery lifecycle.

The post Artificial Intelligence and its Impact on the Software Testing Industry first appeared on TestingXperts.

The advent of Agile and DevOps as a practice over the few years has helped enhance the quality of software immensely. The highly collaborative nature of both the methodologies has led to rapid deployment cycles, and in some cases, it has also helped in achieving the speed of Continuous Integration. The best way to ensure the quality of the software is by implementing the right amount of QA. In fact, implementing an integrated DevOps and continuous testing quality approach has become relevant for all the organizations now.

Contents 1. DevOps QA Best Practices 1.1 Disentangle from the traditional roles and responsibilities of QA 1.2 Communication and Collaboration are Imperative 1.3 Include QA in the Requirements Gathering Process 1.4 Detecting Software Defects Early 1.5 Multiple Virtual Testing Environment is Essential 1.6 Conclusion

A highly iterative DevOps process lays more pressure on the QA role to properly evaluate software while working closely with developers, network professionals, and business stakeholders. In this article, we will explore how DevOps is the best way to strengthen the project and be absolutely sure of what you are shipping to the customer. With high-quality software as the main aim, here are some DevOps QA best practices that will help accelerate the software delivery and also maintain the quality of the software.

DevOps QA Best Practices

1. Disentangle from the traditional roles and responsibilities of QA:

2. Communication and Collaboration are Imperative:

3. Include QA in the Requirements Gathering Process:

4. Detecting Software Defects Early:

5. Multiple Virtual Testing Environment is Essential:

The post Accelerate Software Delivery with DevOps Best Practices first appeared on TestingXperts.

The world is becoming more interconnected and intelligent with each passing day. CIOs are motivated by moving from waterfall projects to continuous delivery of working software. To facilitate continuous delivery, DevOps has become a priority.

Fundamentals for a Successful DevOps Implementation

DevOps is a methodology and a culture shift that emphasizes collaboration across the entire lifecycle of a product. In this infographic, we will discuss the four fundamentals that are important for a successful DevOps implementation.

The post 4 Fundamentals for a Successful DevOps Implementation first appeared on TestingXperts.

1. What is Digital Transformation 2. DevOps and Digital Transformation 3. Steps to Accelerate DevOps with Digital Transformation 4. DevOps and Digital Transformation: Key to Business Success

What is Digital Transformation

Digital transformation is revolutionizing the way organizations are managing internal processes as well as delivering services to customers. Organizations in this digital age are more agile in adapting to change in order to innovate at the speed of business. As cloud-native enterprises use software to build new business models, disrupt, and digitally transform their respective industries, DevOps is becoming the culture to enable this change.

DevOps and Digital Transformation

DevOps has helped minimize barrier between developers and operations and made it easier for the applications to be built and deployed quickly for use. While developers focus on building modern solutions with better user experience, operations fixate on providing stability for site availability. Due to the difference in the focus of work, a gap can exist in both the departments. By adopting DevOps methodology, the conflict between developers and operations can be reduced. However, it requires a cultural shift to address the application behavior proactively rather than at the time of deployment.

The need for speed has been the key driver for DevOps adoption. In the era of digitalization, software is the source of variation, and DevOps is the key to accelerate development and delivery of software. However, not many companies have fully realized the direct connection between speeding up the DevOps implementation and accelerating the whole journey of digital transformation. If you are not able to accelerate the software testing, development, release cycles, and change management, the entire transformation schedule will hit a roadblock.

So, the question arises – How to accelerate DevOps in order to expedite the business outcomes of digital transformation. Given below are three key suggestions as an early point.

Steps to Accelerate DevOps with Digital Transformation

DevOps and Digital Transformation: Key to Business Success

In a business environment, DevOps is the key to superior business results. If you want to expedite your journey to DevOps, you need to get proper guidance from a technology-agnostic partner with DevOps expertise on a global scale. TestingXperts’ with its matured DevOps QA practices and global experience in software testing, can help you create a QA strategy for your DevOps journey to accelerate your digital transformation.

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