Towards a Benchmark and a Comparison Framework for Combinatorial Interaction Testing of Software Product Lines

As Software Product Lines (SPLs) are becoming a more pervasive development practice, their effective testing is becoming a more important concern. In the past few years many SPL testing approaches have been proposed, among them, are those that support Combinatorial Interaction Testing (CIT) whose premise is to select a group of products where faults, due to feature interactions, are more likely to occur. Many CIT techniques for SPL testing have been put forward; however, no systematic and comprehensive comparison among them has been performed. To achieve such goal two items are important: a common benchmark of feature models, and an adequate comparison framework. In this research-in-progress paper, we propose 19 feature models as the base of a benchmark, which we apply to three different techniques in order to analyze the comparison framework proposed by Perrouin et al. We identify the shortcomings of this framework and elaborate alternatives for further study.

[1]  Kyo Chul Kang,et al.  Feature-Oriented Domain Analysis (FODA) Feasibility Study , 1990 .

[2]  Gregg Rothermel,et al.  A framework for evaluating regression test selection techniques , 1994, Proceedings of 16th International Conference on Software Engineering.

[3]  A. Vargha,et al.  A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong , 2000 .

[4]  Maliha S. Nash,et al.  Handbook of Parametric and Nonparametric Statistical Procedures , 2001, Technometrics.

[5]  Roberto Erick Lopez-Herrejon,et al.  A Standard Problem for Evaluating Product-Line Methodologies , 2001, GCSE.

[6]  Rami Bahsoon,et al.  Empirical comparison of regression test selection algorithms , 2001, J. Syst. Softw..

[7]  Jan Bosch,et al.  A taxonomy of variability realization techniques , 2005, Softw. Pract. Exp..

[8]  Klaus Pohl,et al.  Software Product Line Engineering - Foundations, Principles, and Techniques , 2005 .

[9]  A. Sima Etaner-Uyar,et al.  Pairwise sequence comparison for fitness evaluation in evolutionary structural software testing , 2006, GECCO '06.

[10]  Myra B. Cohen,et al.  Constructing Interaction Test Suites for Highly-Configurable Systems in the Presence of Constraints: A Greedy Approach , 2008, IEEE Transactions on Software Engineering.

[11]  Sebastian Oster,et al.  Automated Incremental Pairwise Testing of Software Product Lines , 2010, SPLC.

[12]  Myra B. Cohen,et al.  Evaluating improvements to a meta-heuristic search for constrained interaction testing , 2011, Empirical Software Engineering.

[13]  Sergio Segura,et al.  Automated analysis of feature models 20 years later: A literature review , 2010, Inf. Syst..

[14]  Jacques Klein,et al.  Automated and Scalable T-wise Test Case Generation Strategies for Software Product Lines , 2010, 2010 Third International Conference on Software Testing, Verification and Validation.

[15]  Andy Schürr,et al.  Model-based pairwise testing for feature interaction coverage in software product line engineering , 2011, Software Quality Journal.

[16]  Sven Apel,et al.  Scalable Prediction of Non-functional Properties in Software Product Lines , 2011, 2011 15th International Software Product Line Conference.

[17]  John D. McGregor,et al.  A systematic mapping study of software product lines testing , 2011, Inf. Softw. Technol..

[18]  Jacques Klein,et al.  Pairwise testing for software product lines: comparison of two approaches , 2012, Software Quality Journal.

[19]  Antonio J. Nebro,et al.  jMetal: A Java framework for multi-objective optimization , 2011, Adv. Eng. Softw..

[20]  Andy Schürr,et al.  Model-based coverage-driven test suite generation for software product lines , 2011, MODELS'11.

[21]  Per Runeson,et al.  Software product line testing - A systematic mapping study , 2011, Inf. Softw. Technol..

[22]  Arnaud Gotlieb,et al.  PACOGEN: Automatic Generation of Pairwise Test Configurations from Feature Models , 2011, 2011 IEEE 22nd International Symposium on Software Reliability Engineering.

[23]  Jerffeson Teixeira de Souza,et al.  Ten Years of Search Based Software Engineering: A Bibliometric Analysis , 2011, SSBSE.

[24]  Sungwon Kang,et al.  A survey on software product line testing , 2012, SPLC '12.

[25]  John D. McGregor,et al.  Strategies for testing products in software product lines , 2012, ACM SIGSOFT Softw. Eng. Notes.

[26]  Øystein Haugen,et al.  An algorithm for generating t-wise covering arrays from large feature models , 2012, SPLC '12.

[27]  Dragan Gasevic,et al.  Evolutionary Search-Based Test Generation for Software Product Line Feature Models , 2012, CAiSE.

[28]  Enrique Alba,et al.  Evolutionary algorithm for prioritized pairwise test data generation , 2012, GECCO '12.

[29]  Eduardo Santana de Almeida,et al.  16th International Software Product Line Conference, SPLC '12, Salvador, Brazil - September 2-7, 2012, Volume 1 , 2012, SPLC.

[30]  Yuanyuan Zhang,et al.  Search-based software engineering: Trends, techniques and applications , 2012, CSUR.

[31]  Laurie A. Williams,et al.  Validating software metrics: A spectrum of philosophies , 2012, TSEM.

[32]  Lionel C. Briand,et al.  A Hitchhiker's guide to statistical tests for assessing randomized algorithms in software engineering , 2014, Softw. Test. Verification Reliab..