PS2Way: An Efficient Pairwise Search Approach for Test Data Generation

Testing is a very important task to build error free software. Usually, the resources and time to market a software product is limited, hence, it is impossible to perform exhaustive test i.e., to test all combinations of input data. Pairwise (2way) test data generation approach supports higher reduction of exhaustive numbers as well as low cost and effective. In pairwise approach, most of the software faults are caused by unusual combination of input data. Hence, optimization in terms of number of generated test-cases and execution time is in demand. This paper proposes an enhanced pairwise search approach (PS2Way) of input values for optimum test data generation. This approach searches the most coverable pairs by pairing parameters and adopts one-test-at-a-time strategy to construct final test suites. PS2Way is effective in terms of number of generated test cases and execution time compared to other existing strategies.

[1]  Phil McMinn,et al.  Search‐based software test data generation: a survey , 2004, Softw. Test. Verification Reliab..

[2]  Michael L. Fredman,et al.  The AETG System: An Approach to Testing Based on Combinatiorial Design , 1997, IEEE Trans. Software Eng..

[3]  Tatsuhiro Tsuchiya,et al.  Using artificial life techniques to generate test cases for combinatorial testing , 2004, Proceedings of the 28th Annual International Computer Software and Applications Conference, 2004. COMPSAC 2004..

[4]  Yu Lei,et al.  In-parameter-order: a test generation strategy for pairwise testing , 1998, Proceedings Third IEEE International High-Assurance Systems Engineering Symposium (Cat. No.98EX231).

[5]  Mark Harman,et al.  A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search , 2010, IEEE Transactions on Software Engineering.

[6]  Nor Ashidi Mat Isa,et al.  IRPS - An Efficient Test Data Generation Strategy for Pairwise Testing , 2008, KES.

[7]  Rusli Abdullah,et al.  G2Way A Backtracking Strategy for Pairwise Test Data Generation , 2008, 2008 15th Asia-Pacific Software Engineering Conference.

[8]  Daniel Hoffman,et al.  White Box Pairwise Test Case Generation , 2007 .

[9]  Zainal Hisham Che Soh,et al.  A parallelization strategies of test suites generation for t-way combinatorial interaction testing , 2008, 2008 International Symposium on Information Technology.

[10]  D. Gong,et al.  Automatic detection of infeasible paths in software testing , 2010, IET Softw..

[11]  Jeff Yu Lei,et al.  IPOG: A General Strategy for T-Way Software Testing , 2007, 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'07).

[12]  Xiang Chen,et al.  Applying Particle Swarm Optimization to Pairwise Testing , 2010, 2010 IEEE 34th Annual Computer Software and Applications Conference.

[13]  K.Z. Zamli,et al.  Algebraic strategy to generate pairwise test set for prime number parameters and variables , 2008, 2008 International Symposium on Information Technology.

[14]  Roslina Mohd Sidek,et al.  A Tree Based Strategy for Test Data Generation and Cost Calculation for Uniform and Non-Uniform Parametric Values , 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

[15]  Dean Leffingwell,et al.  Managing Software Requirements: A Use Case Approach , 2003 .

[16]  Sheng Yao,et al.  A New Strategy for Pairwise Test Case Generation , 2009, 2009 Third International Symposium on Intelligent Information Technology Application.

[17]  James D. McCaffrey,et al.  Generation of pairwise test sets using a simulated bee colony algorithm , 2009, 2009 IEEE International Conference on Information Reuse & Integration.

[18]  Robert L. Glass,et al.  Facts and fallacies of software engineering , 2002 .

[19]  Xiang Chen,et al.  Building Prioritized Pairwise Interaction Test Suites with Ant Colony Optimization , 2009, 2009 Ninth International Conference on Quality Software.

[20]  Mark Harman,et al.  Search-based software engineering , 2001, Inf. Softw. Technol..