How AI Is Transforming The Future Of Software Testing?
July 08, 2020
How AI is transforming the future of Software testing?
Artificial Intelligence is not just a technical concept anymore. It’s the hottest topic of the town, transforming enterprises by providing smart and actionable insights. At the same time software testing is now undergoing a major shift from manual to automation as more and more organizations are recognizing the need to adopt DevOps and digital transformation. Needless to say, AI has a huge role to play in this change.
These days applications interact with other kinds of applications with the help of API, utilizing traditional systems. This eventually results in complexities growing in a non-linear manner. So how does this affect testers? The major challenge for them here is to make sure the new code does not break the existing codebase. Every time a new code is written by the developer, new testing methods should be applied to ensure code quality. This in turn increases the workload of tester due to the rising complexity of code.
AI is considered to mitigate all these roadblocks related to QA and testing. Let’s discuss some of the ways AI bring about major changes in testing.
Simple and Error free
The latest AI offers so many features which has the capability to save the time of testers by sorting through log files. This improves accuracy and the developers will be free of writing long scripts and checking huge amounts of data. The AI driven data results helps testers to locate the exact bug in the system without tedious work of going through thousands of lines of code and even predict future errors and complications in the code. Major benefit here is that it accelerates the timeline and efficiency of the QA team.
Like we discussed above, the major time share of QA team is consumed by making sure the new code does not break the existing functional code. With more features added to the system, more testing works need to be undertaken, which further burdens the testers' overall productivity
AI can make a big difference here. AI bots can evolve predetermining the changes in the code. Being highly efficient and adaptable, these bots can identify new modifications in the code and understand if it’s really a change in the code or an error to be removed.
Optimized test suite
One of the major challenges faced by software testers is backlogs, which results due to over-engineering and speedy release due to hectic schedules. Bots can help here by identifying repetitive test cases and removing the duplicates. This will help in clearing the backlogs and achieve end to end traceability.
Prescriptive and Predictive Analytics
AI is taking predictive analytics to the next level. AI bots helps organizations to detect vulnerabilities earlier and thus helps them to prioritize their QA efforts effectively without compromising on quality. It can help solve the most complicated problems by predicting certain scenarios and behavioural patterns and take the best decision possible. From analysing test results to identifying bugs and predicting the quality, AI can be used in every area of QA process. You can utilize it to predict flaws earlier, optimize test processes and hence accelerate overall timeline.