AIQA Technologies is a company formed around the AIQA project, an intelligent automated application test selector.
The problem with application testing
We noticed that one of the problems in developers’ daily work is that the tests of the whole application take a very long time, and only after their completion we know how effective are the introduced changes in the code, and whether they do not cause other errors in other modules of the created project. If such tests last all night, the programmer will see the effects of his work only the next day and if something did not go as planned, he will have to return to the problem solved the day before and correct it further. Sometimes this will require going back to an earlier task and re-examining the entire problem.
Additionally, in large development teams, it is common to test all of the changes made by the entire team on a given day simultaneously, and it is often difficult to pinpoint whose bugs are resulting in application performance issues. This creates an additional problem with identifying badly written code and pinpointing the person responsible for correcting it.
A way to streamline such work is to perform only selected tests, which check only the modules that depend on the modifications introduced by the programmer. Such a scenario allows the programmer to check his work faster and possibly catch errors before they affect the whole program.
In our solution, we used artificial intelligence and machine learning algorithms to determine the relationship between source code and tests. Based on the history of application development and testing we are able to suggest to the developer which tests he should perform in order to quickly check the impact of modified code on the entire project.
We believe that our project will allow others to develop applications more efficiently and save time needed to fix bugs.