T-Way testing with seeding support

Abstract

Software testing is one of the important parts of software development life cycle in software engineering, but this process is still very labour- intensive and expensive . Around 50% of project money goes under software testing. Hence, the focus is to find automatic and cost-effective software testing and debugging techniques to ensure high quality of released product. Nowdays, research on software testing focuses on test coverage criterion design, test-data generation problem, test oracle problem, regression testing problem and fault localization problem. Among these problems test-data generation problem is an important issue in producing error free software. To solve this problem, Pairwise strategy (i.e. two-way interaction) has been known as an effective test data reduction strategy and able to detect from 60 to 80% of the faults. For a typical software product, it is desired to test all possible combinations of input data in various configurations, Exhaustive testing is impossible to execute prior to release in the market. The lack of resources, cost factors and tight deadlines to market are some of the main factors that prevent this consideration. Another than that, the lack of testing can lead to disastrous consequences including loss of data, fortunes and even lives if human resources are not planned and managed effectively. In current practice, usually the testdata are selected and executed randomly. Many useful strategies (2-Way and T- Way sampling) were developed to generate test-data and facilitate smooth testing process. Comprehensive test data generation is nondeterministic polynomial hard problem (NPcomplete). Hence, optimization in terms of number of generated test-data and execution time is in demand. However, as t-way test suite generation is NP hard problem, no single existing strategy can claim dominance as far as optimality of test size is concerned. Motivated by the aforementioned challenges, this Final Year Project design and evaluate t-way strategy called TSWS that supports seeding possibilities.