Artificial Intelligence (AI) has been one of the trendiest terms in world for the last decade or so, as it is not just a concept now but also an actual reality. AI has been in use in various fields but it reached the world of software testing just in the last couple of years. Ever since Software Testing has incorporated automation testing, the importance of AI has increased even more. With clients wanting faster results or on short notice, AI has played a crucial role in meeting these demands with ease. However, the question arises that were not the automation tools doing the same. AI improves the output of these automation tools and thus saving a lot more time and money. In this article, we will tell you how AI is providing the all-important extra impetus in the field of Software Testing.
What is the role of AI in testing?
Automation tools have made it easier to produce faster results as it runs all the tests using different automation tools and thereby reducing the possibility of human errors. However, there is scope for even more improvement. To take an example, what happens with automation testing is that it runs all the available tests, even if it is not required, on a product and then comes up results. This transpires as the automation tools do not have the knowledge of which tests to run and what to avoid. This is where AI has changed the game of Software Testing in a huge way. The major role of AI is reducing the time of development cycles and enhancing the efficiency of automation tools. AI determines the tests required for a particular product and help the tools to run just those tests, thus saving a lot of time.
How does AI fit into the scheme of testing?
Artificial Intelligence means the study of intelligent agents working according to its environment and thus coming up with solutions to increase the success rate of achieving certain goals. This is exactly what AI does in Software Testing as well. It helps reduce the test cycle turnaround time. It replaces the developer or tester in the process of decision-making in the most mundane or routine cases and hence comes up with faster and accurate results. It does so by using the application of problem solving, reasoning and machine learning in some cases.
Machine learning is something that aids AI in the improvement of the tool by coming up with information on previous data and cases and thus helping the AI in decision-making based on experiences. Machine learning helps in continuous data collection and modifying it from time to time. Machine learning helps AI by giving information on static analysis results, test results and other software metrics to come up with faster solutions and decisions. However, one does not require the use of machine learning all the time as in some cases human fine-tuning is the best solution. Humans create codes and instructions that are to be repeated routinely in certain conditions and thus help AI continue taking such decisions on it.
What are the advantages of AI in Software Testing?
• Fewer errors
In Software testing, the chances of experiencing errors can be high, especially in monotonous tests. It is natural for humans to cause errors while doing the same thing for a long time. This is where AI comes into rescue as it reduces the possibility of an error drastically. AI can deal with such mundane processes at length without losing focus and it frees up the humans to indulge in processes that are more sophisticated.
• Improved test coverage
AI can help make quick decisions and ensure smooth functioning of the whole process by looking into data files, internal program states and data points in tables. It can help the automation tools to churn out faster results by simultaneously testing the products with different tests.
• Saves time and money
Every time a source code is modified, the testing cycle repeats itself from the start and thus can be time consuming. AI integrated automation tools help by repeating such processes repeatedly without the use of manual developers or testers. It saves you a lot of time and work force, thus saving you money.
There will soon be a time when AI would replace the testers and developers for the writing and execution of codes even during the run time to eradicate any chances of human error. It might not replace some of the fundamentals of testing and quality assurance, which only humans are capable of doing. However, since testing is an ever-evolving process, we can hope for some exciting innovations involving the integration of AI in testing techniques in our near future.