A Bee Colony Optimization Algorithm for Fault Coverage Based Regression Test Suite Prioritization
Arvinder Kaur, Shivangi Goyal · International Journal of Advanced Science and Technology · 2011
The process of verifying the modified software in the maintenance phase is called Regression Testing. The size of the regression test suite and its selection process is a complex task for regression testers because of time and budget constraints. In this research paper, the Bee Colony Optimization (BCO) algorithm for the fault coverage regression test suite prioritization has been presented. In the natural bee colony, there are of two types of worker bees; Scout bees and forager bee, who are responsible for the development and maintenance of the colony. The BCO algorithm developed for the fault coverage regression test suite is based on the behavior of these two bees. The BCO algorithm has been formulated for fault coverage to attain maximum fault coverage in minimal units of execution time of each test case, using two examples whose results are comparable to optimal solution. Average Percentage of Fault Detection (APFD) metrics and charts has been used to show the effectiveness of proposed algorithm.