Approach to Regression Test Automation
Software changes are the key reason for regression testing. Although regression testing is a resource-consuming process, automation makes it more efficient and reduces resource consumption. Regression test automation is a critical component in a software development cycle and ensures that any existing software tested earlier continues to perform as expected after modifications.
There are several steps to a well-planned regression testing automation strategy, including the selection of the right tools and frameworks, designing, and developing test scripts, test execution, and analyzing the results. The goal of the automation strategy is to increase efficiency, reduce manual effort, and ensure software quality through the development process.
This article focuses on the steps required for implementing an effective regression test automation strategy.
Key phases/steps to a regression test automation approach
Scope of automation: Defining the scope of automation is the first step towards regression testing automation. It is pivotal and gives direction to the automation strategy. The scope includes defining the timelines and milestones that are to be achieved during each part of the project and defining which test cases should be automated and which ones should be kept manually. The decision to automate a test or not is based on many factors such as the complexity of the test case, reusability, and the frequency of their execution. By defining the scope of the tests, there is a focused and effective approach to automation, which maximizes the benefits of regression testing without wasting resources.
Approach to automation: The second step is the approach to test automation, in which the automation process is defined, technology is selected, and roles are assigned. The process gives a direction in deciding how the automation is carried out and which practices and methodologies are to be followed to achieve the goal.
The process part of the approach strategy helps decide how the automation is to be carried out, and the methodologies and practices that are to be followed.
Generally, regression testing involves various application types such as web & mobile-based, mobile apps, SAP/Dynamics/Oracle, etc. Therefore, the technology approach is used to determine and choose the tools, frameworks and platforms required to take the project forward.
Assigning roles to teams and individuals is essential and responsibilities are assigned based on skills and expertise. A structured and defined approach provides a road map and ensures that the automation strategy aligns with the project objectives and maximizes the benefits of automation.
Analyzing risks: Risk analysis is a critical component of regression test automation strategy, and is used to identify the risks that can be linked to the changes in software. This is a time-consuming process, involving prediction issues, estimation of the impact, and devising strategies to mitigate the risks.
The risk-based approach also involves identifying the parts of the application that can be affected by changes in code and the selection of test cases. The purpose behind risk analysis is to prevent unforeseen issues, system failures, or performance breakdowns from happening and impacting business operations. Identification and mitigation of risks early on ensure that the quality and stability of the product is maintained. This approach also works when new features are added to a product.
Testing environment & data: The testing environment is a system where the software can be tested and can be made of more than one environment. To ensure that the automation strategy works effectively, it's necessary to ensure that the testing environment reflects the production environment to precisely assess software functionality and performance.
The testing data refers to the data inputs that are to be used during testing. The quality of testing data is crucial and can affect the effectiveness and outcome of the regression tests. Therefore it's essential to use authentic datasets that cover various scenarios of the working software.
The environment and data together can be particularly useful to identify any potential issues early on and ensure that the automation strategy works as intended.
Execution: The next step to automated testing is actually testing or executing the selected test cases. The test cases can be executed by using a scheduling tool or pipeline orchestrator such as Jenkins, Bamboo etc. The focus during the execution of test cases is to ensure that any recent modifications have not generated any bugs or issues or regression in the existing software. Executing a well planned strategy ensures quality and stability of the software.
Failure analysis: Failure analysis assesses failed test cases and the steps that have to be taken to correct this. It helps testing teams to grasp the reasons for both false and valid failures. It can also help identify the bottlenecks that can be the reason for delay in execution and release. A well defined failure analysis process saves time, effort and resources and plays a very important role in regression test automation strategy.
Release: Releasing the software is based on the results of the automated testing strategy and is an important step as it confirms that the software release is as per the required standards. The release process has to be well documented and systemic, and should account for multiple test versions. Essentially, release control ensures that the automation strategy is aligned with the objectives of the project and takes complete advantage of the automation strategy.
Feedback: The feedback received from team members, peers, and DevOps engineers, is used to review the strategy used for test automation. Reviews and feedback help provide a clear understanding of the application and enable the updation of test scripts as per requirement. The feedback and review loop helps in refining the regression test automation strategy and improving the quality of the software.
Final Words
The steps form a comprehensive strategy for regression test automation and are essential and ensure the quality and stability of the software product. You can work with a specialist software testing company and avail of their test automation services to execute the automation strategy to deliver high-quality products.
Similar Articles
E-learning has become a quintessential wave through which learners access education in today’s te
Are you tired of keeping up with regulatory requirements and managing risk, which can feel like navigating a labyrinth? Organizations across industries face mounting pressure to maintain compliance while simultaneously driving growth and innovation.
Anyone even vaguely familiar with today's fast-paced digital world would know that e-commerce businesses face intense pressure. Pressure to deliver exceptional customer experiences while also maximizing their profits. To achieve this delicate balance, companies operating in this space must now put the power of technology to work
Intelligent technology-driven solutions are now guiding industries across all sectors. Innovative and disruptive technologies like Artificial Intelligence (AI) and Machine Learning (ML) are driving these changes, which play a crucial role in designing and developing intelligent solutions.
The introduction of Artificial intelligence (AI) healthcare has caused a radical change in the way that medical care is provided. It gains paramount importance when it comes to customised treatment regimens.
Graphical presentation of data and information in visual formats like charts, maps, and graphs is termed data visualization. This method makes complex data more accessible and easily understandable bringing out the trends and patterns from raw data, which can be used to significantly enhance customer experience
Integrating AI into your business app isn't just a matter of staying current; it's about unlocking new dimensions of efficiency, personalization, and customer satisfaction. Among the most groundbreaking AI technologies is ChatGPT, a language model that simulates human conversation with incredible accuracy.
In the race to deliver high-quality software faster, automation isn’t just an option—it’s essential. Are you tired of slow, error-prone testing? It's time to let automation accelerate your software development and deliver top-notch quality more quickly.
The convergence of sports and technology has ignited a transformative era, where data-driven insights are reshaping the athletic landscape. Artificial intelligence (AI) and machine learning (ML) are at the heart of this, which have transcended mere buzzwords to become indispensable tools in sports app development