Researching On Regression Test Selection Technique For Object-Oriented Software-Test Suite Minimization

One frequently executed but expensive maintenance activity is regression test.As the software is modified and new test cases are added to the test-suite,the size of the test-suite grows and the cost of regression testing increases.It is really necessary to decrease the cost and impove the effectiveness of regression test by using test-selection techniques.One of the most important regression-test reduction techniques is test-suite minimization techinique,which identifies a minimal set of test cases that provides the same coverage of the software,according to some criterion,as the original test-suite.For the purpose of this dissertation,a deep research of test minimization techniques appears below:1.The design and implementation of the object-oriented software-testing engine.As the kernel of the testing tool,the design of the testing engine took much consideration of the reusability of the component,and can be easily evolved to accommodate new testing requirements.There are three components in the test engine: a program analyzer,an instrumental tool and a media database.The media database can save all the structure information of the program and test history information,so it is convenient to extend the new function of the developed testing tools such as regression test,test selection and reduction for regression testing to promote the test efficiency,and so on.2.The mathematical model of test minimization problem.A general mathematical model for test minimization problem and its linear integer-programming form are presented in this thesis based on the block-based test data adequacy measurement criteria.This model can be easily changed to accommodate new test-selection requirement and other test data adequacy measurement criteria.3.A new greedy algorithm for test-suite minimization.Test-suite minimization is to find a minimal regression test-set which can satisfied test requirement.Based on present greedy algorithms for test-suite minimization,a new greedy algorithm is presented in this thesis.Unlike other algorithms,our algorithm uses a new criteria, which is a combination of a block based coverage criteria and a test-execution cost criteria.The studies showed that our algorithm can significantly reduce the size and decrease the cost of the test-suite for regression testing,and the test-execution cost is one of the most important features that must be taken into consideration for test-suite reduction.4.A genetic algorithm for test-suite minimization.In order to improve the effectiveness of test-suite minimization,this dissertation is to investigate the use of genetic algorithms.The algorithm builds the initial population based on test history, calculates the fitness value using coverage and cost information,and then selectively breeds the successive generations using three genetic operations.The results of studies showed that,genetic algorithms can achieve better minimization effectiveness than the greedy algorithms.The studies also demonstrated that taking the test-execution-cost criteria into consideration can promote the effectiveness of the test minimization techniques. 5.A framework for evaluating the test-minimization techniques.Finally, several issues relevant to regression test minimization techniques are outlined,and these issues,including adequacy,precision,cost-effectiveness and generality,are used as the basis for a framework within which to evaluate the minimization techniques.