Analyzing Test Case Selection using Proposed Hybrid Technique based on BCO and Genetic Algorithm and a Comparison with ACO

Regression Testing is primarily a maintenance activity that is performed to ensure the validity of modified software. But due to time and cost constraint entire test suite can't be executed. Thus, it becomes a necessity to reduce the test case suite and select a subset of test cases from test suite that can be executed in minimum time and has the ability to cover all the faults. A new hybrid approach based on bee colony optimization and genetic algorithm was proposed to reduce the test suite. This paper presents a tool named HBG_TCS that implements the proposed approach and the study is done to evaluate the correctness and efficiency of the proposed tool and a comparison of the proposed approach is made with the ant colony optimization.

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