UML Generated Test Case Mining Using ISA

Our paper focuses on the generation of optimal test cases from Unified Modeling Language (UML) diagrams using Intelligent Software Agents (ISA) for highly reliable systems. Knowledge Discovery in Databases (KDD) is a process of finding new, interesting, previously unknown, potentially useful, and ultimately understandable patterns from very large volumes of data. The ultimate goal of data mining is in revealing pattern that is easy to perceive, interpret, and manipulate. Software testing is the most common practice of software quality assurance which needs test cases. In order to improve the efficiency of software testing we go for mining of test cases. One of the most important and challenging problems in data mining is the definition of prior knowledge. This can be originated from the process or the domain. Prior knowledge is helpful for selecting suitable data and mining techniques, pruning the space of hypothesis, representing the output in comprehensible way, and improving the overall method.