Agent based analysis of test case prioritization techniques for software operations

Abstract

Increased use of software applications by businesses, government and consumers to perform their daily operations has led to the need for reliable, well-tested software applications. A short time to market, large user community, demand for continuous availability, and frequent updates motivate automated cost-effective testing strategies. Software developers often save the test suites they develop for their software, so that they can reuse those suites later as the software evolves. Test case prioritization is an approach to optimize the execution of tests by ordering a set of test cases. Different prioritization techniques use different ordering criteria: execution time reduction, early discovery of defects, faster test coverage rate, exercises features in order of expected frequency of use, or exercises subsystems in an order that reflects their historical propensity to fail. This thesis presents an automated cost effective test case prioritization model using multi agents. The proposed agent based model performs test case prioritization of various operations like basic, database, web and web services present in the software under test. The proposed model will be applicable in the beta/maintenance testing phases of the lifecycle of the application. In phase-I, the proposed prioritization techniques for different operations present in the software under test are analyzed with the existing techniques, based on the Average Percentage of Fault Detection (APFD) and the best technique chosen for each operation. Phase-II automates the prioritization process for the complete software having different operations, using multi agents, where the best technique chosen from Phase-I is considered for implementation of the techniques in the agent based model. Finally, the proposed agent based model is compared with the existing general model, based on execution time. newline newline newline