Smart Test Execution and Analysis of Results
Smart test execution and efficient analysis of results apply powers of artificial intelligence and machine learning to categorically target specific codes as per changes in the application. Organizations save time and effort with faster feedback. There is no need to execute a complete automation test suite and run software testing for everything whenever programmers develop changes. Four Steps for Smart Test Execution Assessment of Scope for Automation Test Start with a run-through of your organization & automation test state, the quantity of data for the test, and the node of the execution platform. A deep analysis of the internal team will help to assess the general area for software testing.
The walkthrough should include
- Technical suitability of the team
- The complexity level of automation test cases
- Significant functions and features to be performed
- The expanse of test elements to be reprocessed Choosing a Reliable Software Testing Tool A reliable and efficient automation tool is crucial for a successful automation testing project. You must conduct a detailed study to finalize a testing platform. You should consider the following things before selecting a testing tool:
- Web and mobile applications and required technology stack which is to be tested
- Automation testing specifications
- Skill sets in terms of QA teams, developers, and programmers
- The license cost of the tool (if any) Test automation does not work similarly on all platforms and projects. Save time, money, and effort by choosing the right tool for automation testing. Though it might take time in selecting a reliable tool, it is worth it for the sake of successful application testing. Plan, Design, and Develop Next, it & time to plan a software testing strategy. You need to ponder the goals of the automation testing procedure, framework designs, features, and timeline to conduct scripting for the implementation of test cases. Smart Test Cases Execution and Report Making
The final step is the implementation of test automation scripts
Platforms like algoQA offers machine-generated faster scripts with accuracy. The platform runs with AI and ML-based technologies. It facilitates smart test execution. We will explain the benefits of choosing algoQA in the concluding section. After smart test execution concludes, the system generates a consolidated report of the testing implemented during the project. Systematic Analysis of Test Results Efficient and systematic results analysis is equally important as smart test execution. It is crucial for correct data finding and uses the outcome for application launch in the public domain. Productive analysis of results needs the correct method and the right bunch of tools. Automated tests increase efficiency, minimizes the risk of failures, and lower costs.
However, automation also increases speed, which means a higher number of tests. A greater quantity of tests poses a challenge to managing and analyzing thousands of test outcomes.
How to conduct automation test results analysis for smart testing?
Aspects to cover during the analysis of test results are the following:
- There is a need to review the correct build of automated tests and their planned purpose to attain. It is essential to set the tone into the right perspective for results analysis and smart testing.
- Setting up automated monitoring to ensure software testers invest their time efficiently. Testers spend lots of time observing and analyzing individual test results, making it automated saves time and increase productivity.
- Explore and utilize features of your test automation platform to find out the reasons for test failures. Features include a video recording of the tools running the test script, replay, debugging, logging functionalities, exception reporting, and more.
- Use release platforms like Jira, TFS, etc., for handling and managing bugs in the test. Organizations can integrate test automation platforms with these release tools for keeping track of bugs, test case descriptions, test strategies, and more.
- You can integrate either through pulling test results from the software testing platform with an API or pushing outcomes to the test management mechanism.
- Use shared dashboards for transparent and fast feedback for real-time automation test results. It is a crucial aspect of results analysis for DevOps teams. The feedback loop helps the development team at your organization to resolve issues faster and prevent bugs before releasing them for production.
- Last but not least by any means aspect of result analysis is a comprehensive review of the tests conducted, not individual test sets. A deep understanding of test failures and bugs will prepare your team to ensure bug-free and glitch-free applications for public consumption. Smart Test Execution and Analysis of Results with algoQA Platform.
- The amount of time test execution takes should be optimal, and the scripts should run consistently multiple times.
- Access results faster with algoQA. Run smart tests, and attain the automation testing requirements of compressed cycles supervised by agile development procedure.
- Smart test execution with algoQA observes the application for any changes and runs the remedial measures to authenticate the transformed part or entire code.
- It saves additional time invested in implementing thousands of automation tests for every build that develops obstacles in the process.
- ML-based tools of algoQA analyze and model the relationships between automation tests and the code beneath. After smart test execution, the model is used for test impact analysis on altered or new code.
- It helps to generate targeted and intelligent automation tests. The platform provides smart test execution and effective analysis of outcomes.
- QA, DevOps, and Developers can execute tests uninterrupted and seamlessly integrates with CI/CD pipelines. It allows real-time access to code breaks, and you can fix bugs in-time.
- Therefore, it gives stable codes for an effective automation test. Explore more about smart test execution and analysis with algoQA from AlgoShack at https://www.algoshack.com/algoqa/.