Regression Test Suite Reduction Research Articles

Regression Test Suite Reduction using an Hybrid Technique Based on BCO And Genetic Algorithm

Regression testing is a maintenance activity that is performed to ensure the validity of modified software. The activity takes a lot of time to run the entire test suite and is very expensive. Thus it becomes a necessity to choose the minimum set of test cases with the ability to cover all the faults in minimum time. The paper presents a new test case reduction hybrid technique based on Genetic algorithms(GA) and bee colony optimization (BCO) .GA is an evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. BCO is a swarm intelligence algorithm. The proposed approach adopts the behavior of bees to solve the given problem. It proves to be optimistic approach which provides optimum results in minimum time.

Regression test suite reduction based on SDL models of system requirements

AbstractThis paper proposes a model‐based regression test suite reduction method. The proposed method considers an SDL model representing the requirements of a system under test and a set of modifications on this model, applies dependence analysis to identify interaction patterns related to each type of modifications, i.e., adding, deleting, and changing transitions in the SDL model, and reduces the size of a given regression test suite by examining interaction patterns covered by each test case in the test suite. Results of empirical studies are reported. Copyright © 2009 John Wiley & Sons, Ltd.