Artificial Intelligence (AI) and software testing aren’t usually discussed in tandem, but this trend is changing. AI is poised to play a major role in how software is tested and evaluated for quality. AI bots that assist in testing is just the beginning of this change.
Today’s software has become more complex. An application usually interacts with multiple APIs that may or may not be working on legacy systems. The complexity keeps rising day by day and the experts are looking to leverage existing AI techniques and tools.
The World Quality Report 2017-18 states that intelligent test automation is the future. Here are a few statistics that illustrate how the software testing industry perceives these trends and how organizations plan to respond.
- 48% consider automated test case design as the next major step
- 47% believe test data automation is a major trend worth exploring
- 43% would favor virtualization of test environments
- 42%-38% consider intelligent, cognitive, and smart analytics trends as important
Of course, we don’t expect human software testing to lose value overnight. However, the progress of AI marches on and as tools become smarter and smarter, manual testing might soon be eliminated. AI implementations in software testing are following an AI-as-testing-assistant approach. The co-founders of Applitools, Moshe Milman, and Adam Carmi describe that automation will happen in stages. The first change that will happen is humans will have to do less of the mechanical work involved in implementing and executing tests. Nevertheless, they will still be an important part of the process because a human will need to approve and decide what actions to take based on the testing results.
Testers can look forward to AI-based testing bots working with them as the ideal assistant. These bots will help lighten their workload and make software development smoother. Here are five major ways that AI will alter the world of software testing.
1. Software testing will become simpler
AI algorithms are powerful analytical tools and when customized according to the needs of software testing needs, they can help make the process easier. Usually, testing involves writing detailed testing scripts, which then generate a large amount of data. This data needs to be analyzed and examined to gain insights and this task will become much simpler with AI-based tools. Developers will be able to program the AI to sort through extensive log files generated during testing. An algorithm will produce more accurate and faster results as compared to traditional methods.
This data and insights will remove much of the guesswork involved in the testing process and give developers a birds-eye view of what changes need to be implemented. AI checks the system and locates any flaws, which can be checked and fixed by human software testers. Another major innovation is that AI can make predictions about future complications, hence making the entire process more efficient.
2. AI will automate existing testing procedures
IT projects usually have strict time constraints. Developers are often under immense pressure to make the push for final deployment without fully testing the software. This ends up creating annoyance amongst users who encounter bugs while using the application. Companies can hire dedicated software testing teams, but this is an expensive option that doesn’t fit most budget constraints.
A majority of testing methods involve a set of repetitive steps that analyze the code, detect anomalies, and generates results. This manual testing is an integral part of every development phase and consumes a lot of time. AI can help increase efficiency by using algorithms that analyze a dataset. This dataset contains definitions of software functions and errors. Through this automated method eliminates almost 80% of the workload on human testers. This means workers don’t need to perform repetitive tasks and can focus on improving code quality.
3. AI will make humans more creative
The user interface of an application is the main basis for evaluating the intuitiveness of any front-end application. The developer has to be creative enough to think from the point of view of the customer while designing and coding the application. The use of AI gives developers more time to reflect on how the application functions. This eventually helps achieve the goal of a better product because developers aren’t bogged down in the intricacies of coding.
Software testers often spend a lot of time evaluating and analyzing the product from a technical perspective. These details often make them miss the forest for the trees when it comes to judging how the application looks to an average user. Since IT has always been a consumer-driven industry, better focus on customer perspectives will result in better products. Achieving this mindset means the company will create intuitive software and can move forward with innovative ideas.
4. More bugs will be eliminated
Bugs in software code end up ruining the overall application experience. Software testing can help identify and eliminate these bugs before the product is deployed. Whenever bugs are identified, testers often want to evaluate the origin of the bug and the reason why it went undetected so far. AI can help answer these important questions. AI-based tools will be able to test for bugs and keep track of how, where, and when they occurred. As the AI analyzes the code, it can also spot minor errors in code as well as possible improvements. Testers can decide if these suggested changes are worth implementing and can modify the code if needed.
5. Constant improvement in testing capabilities
Each stage of the testing process involves implementing multiple tests. Trying to accomplish this manually is an arduous task for software testers. Luckily, machine learning can help mitigate this problem. A machine learning algorithm analyzes a set of test data that has been specifically created for that purpose. This data is then fed into an AI machine to perform various tests automatically. These tests can be repeated at every stage to ensure the security and reliability of the software solution.
Everyone realizes that AI is no longer a buzzword, but a reality that will help disrupt existing processes as well as industries. The role of automated software testing and software testing is on the cusp of a dramatic change. Developers should get ready because Skynet might not be coming, but AI test bots definitely are.
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