Application of Machine Learning in Software Testing of Healthcare Domain

Software testing stage plays an important role in the software development life cycle. Structural testing is a popular method of software testing among other sorts. By traveling through all potential software code paths, structural testing can be greatly enhanced. The most popular search method for automating path testing and test case generation is the genetic algorithm. In this research, an algorithm based on ant colony optimization (ACO) has been suggested, which will produce a set of best paths and rank them. In order to produce test data for structural testing, the basic ACO algorithm is transformed into discrete version in this study. The technical road map for integrating the modified ACO algorithm and test procedure is presented first. The method also creates test data sequences within the domain for the produced pathways to use as inputs. The suggested method ensures complete software coverage with the least amount of redundancy. This paper also applies the suggested strategy by way of a program module.