COST-COGNIZANT TEST CASE PRIORITIZATION FOR SOFTWARE PRODUCT LINE USING GENETIC ALGORITHM

Abdulkarim Bello; Hauwa Muhammed Alhassan

doi:10.33003/fjs-2025-0909-2901

Authors

Abdulkarim Bello
kiyawa99@gmail.com

Department of Computer Science, Usmanu Danfodiyo University, Sokoto
Hauwa Muhammed Alhassan
Department of Computer Science, Federal Polytechnic Nasarawa

Keywords:

Test Case Prioritization, Test Suite, Software Product Line, Genetic Algorithm

Abstract

Software Product Line (SPL) is a family of related software systems with some commonalities and variabilities concerning features and relationships. SPL tends to reduce development and maintenance costs, increase quality, and decrease time to market. Due to its unique features, most software companies are moving from single software to SPL. A feature describes the behavior and capability of SPL displayed in a Feature Model. Moreover, testing of SPL is a difficult task as compared to a single system, based on this, a test case prioritization is needed to order test cases best on its importance. In this study, a cost-cognizant test case prioritization for software product line that uses path-based testing to identify the possible execution approaches was proposed. The path was extracted from a feature model of SPL obtained from FeatureIDE. Further, a Genetic Algorithm (GA) was used to prioritized test cases based on the rate of fault detection per unit test cost. The approach was evaluated using the Average Percentage of Fault Detection per Cost (APFDc) metric across four program objects (Video Store Versions VS1, VS2, VS3, and VS4). For the result, the proposed approach achieves higher performance compared to the existing methods namely CEC, RNDP and NOP. Specifically, APFDc scores reached 94.48% for VS1, 91.84% for VS2, 90.93% for VS3, and 71.81% for VS4, confirming the effectiveness and efficiency of the method in improving fault detection while reducing testing cost.

Dimensions

REFERENCES

Al-hajjaji, M., Lity, S., Lachmann, R., Th, T., Schaefer, I., & Saake, G. (2017). Delta-Oriented Product Prioritization for Similarity-Based Product-Line Testing. https://doi.org/10.1109/VACE.2017.8

Al-Hajjaji, M., Thüm, T., Meinicke, J., Lochau, M., & Saake, G. (2014). Similarity-based prioritization in software product-line testing. ACM International Conference Proceeding Series, 1(September), 197–206. https://doi.org/10.1145/2648511.2648532

Bello, A., Sultan, A. M., Ghani, A. A. A., & Zulzalil, H. (2018). Evolutionary cost cognizant regression test prioritization for object-oriented programs based on fault dependency. International Journal of Engineering and Technology(UAE), 7(4), 28–32. https://doi.org/10.14419/ijet.v7i4.1.19486

Bello abdulkarim. (2019). Evolutionary cost-cognizant regression test case prioritization for object-oriented programs abdulkarim bello fsktm 2019 6.

Devroey, X., Perrouin, G., Legay, A., Schobbens, P., & Heymans, P. (2016). Search-based Similarity-driven Behavioural SPL Testing.

Elbaum, S., Malishevsky, A. G., & Rothermel, G. (2002). Test case prioritization: A family of empirical studies. IEEE Transactions on Software Engineering, 28(2), 159–182. https://doi.org/10.1109/32.988497

Elbaum Sebastian; Rothermel, G. (2001). Incorporating Varying Test Costs and Fault Severities into Test Case Prioritization.

Elbeltagi, E., Hegazy, T., & Grierson, D. (2005). Comparison among five evolutionarElbeltagi, E., Hegazy, T., & Grierson, D. (2005). Comparison among five evolutionary-based optimization algorithms. 19, 43–53. https://doi.org/10.1016/j.aei.2005.01.004y-based optimization algorithms. 19, 43–53. https://doi.org/10.1016/j.aei.2005.01.004

Ensan, A., Bagheri, E., Asadi, M., Gasevic, D., & Biletskiy, Y. (2011). Goal-oriented test case selection and prioritization for product line feature models. Proceedings - 2011 8th International Conference on Information Technology: New Generations, ITNG 2011, 291–298. https://doi.org/10.1109/ITNG.2011.58

Ensan, F., Bagheri, E., & Gaˇ, D. (2012). Evolutionary Search-Based Test Generation for Software Product Line Feature Models. 613–628.

Fischer, S., Lopez-Herrejon, R. E., & Egyed, A. (2018). Towards a fault-detection benchmark for evaluating software product line testing approaches. Proceedings of the ACM Symposium on Applied Computing, 2034–2041. https://doi.org/10.1145/3167132.3167350

Kumar, S. (2017). cost-based test case prioritization technique for software product line. 40(115).

Kwon, J., Ko, I., Rothermel, G., & Staats, M. (2014). Test Case Prioritization Based on Information Retrieval Concepts. https://doi.org/10.1109/APSEC.2014.12

Li, S., Bian, N., Chen, Z., You, D., He, Y., & Prioritization, A. T. C. (2010). A Simulation Study on Some Search Algorithms for Regression Test Case Prioritization. 72–81. https://doi.org/10.1109/QSIC.2010.15

Ma, Y., & Offutt, J. (2016). Description of muJava ’ s Method-level Mutation Operators. 1–4.

Malhotra, R. (2015). Empirical research in software engineering : concepts, analysis, and applications. CRC press.

Malishevsky, A. G., Ruthruff, J. R., Rothermel, G., & Elbaum, S. (2006). Cost-cognizant Test Case Prioritization. Department of Computer Science and Engineering University of NebraskaLincoln Techical Report, TR-UNL-CSE-2006-0004, 1–41. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.131.6542&rep=rep1&type=pdf

Markiegi, U., Arrieta, A., Sagardui, G., & Etxeberria, L. (2017). Search-based product line fault detection allocating test cases iteratively. 123–132. https://doi.org/10.1145/3106195.3106210

MS. A. Askarunisa, MS. L. Shanmugapriya, D. N. R. (2010). Cost and Coverage Metrics for Measuring the Effectiveness of Test Case Prioritization Techniques.

Panigrahi, C. R., & Mall, R. (2014). A heuristic-based regression test case prioritization approach for object-oriented programs. Innovations in Systems and Software Engineering, 10(3), 155–163. https://doi.org/10.1007/s11334-013-0221-z

Qureshi, S. A. (2018). Test Case Prioritization for Software Product Line Testing. CAPITAL UNIVERSITY OF SCIENCE AND TECHNOLOGY, ISLAMABAD.

Raju, S. (2012). Factors Oriented Test Case Prioritization Technique in Regression Testing using Genetic Algorithm. 74(3), 389–402.

Ramasamy, K., Ieee, M., & A, S. A. S. A. M. S. (2008). Incorporating varying Requirement Priorities and Costs in Test Case Prioritization for New and Regression testing. 2.

Ritterman, J., & Klein, E. (2009). OOP Lab 3 Exercises : Instances , Arrays , and Encapsulation Exercises Exercise 1 : Looking at the Weather. 1–11.

Rothermel, G., Untcn, R. H., Chu, C., & Harrold, M. J. (2001). Prioritizing test cases for regression testing. IEEE Transactions on Software Engineering, 27(10), 929–948. https://doi.org/10.1109/32.962562

Sabharwal, S., Sibal, R., & Sharma, C. (2010). Prioritization of test case scenarios derived from activity diagram using genetic algorithm. 2010 International Conference on Computer and Communication Technology, ICCCT-2010, 481–485. https://doi.org/10.1109/ICCCT.2010.5640479

Sahak, M., Jawawi, D. N. A., & Halim, S. A. (2017). An Experiment of Different Similarity Measures on Test Case Prioritization for Software Product Lines. 9(3), 177–185.

Sanchez, A. B., Segura, S., & Ruiz-Cortes, A. (2014). A Comparison of test case prioritization criteria for software product lines. Proceedings - IEEE 7th International Conference on Software Testing, Verification and Validation, ICST 2014, 41–50. https://doi.org/10.1109/ICST.2014.15

Sulaiman, R. A., Jawawi, D. N. A., & Halim, S. A. (2021). A Dissimilarity with Dice-Jaro-Winkler Test Case Prioritization Approach for Model- Based Testing in Software Product Line. 15(3), 932–951.

Tulasiraman, M., & Kalimuthu, V. (2018). Cost Cognizant History Based Prioritization of Test Case for Regression Testing Using Immune Algorithm. Journal of Intelligent Engineering and Systems, 11(1), 221–228. https://doi.org/10.22266/ijies2018.0228.23

Wohlin, C., Runeson, P., H¨ost, M., Ohlsson, M. C., Regnell, B., & Wessl´en, A. (2012). Experimentation in SOftware Engineering. London: Springer Heidelberg New York Dordrecht. In Springer Heidelberg New York Dordrecht. london. https://doi.org/10.1007/978-3-642-29044-2

Yoo, S., & Harman, M. (2010). Regression testing minimization, selection and prioritization: a survey. Software Testing, Verification and Reliability, n/a-n/a. https://doi.org/10.1002/stvr.430

COST-COGNIZANT TEST CASE PRIORITIZATION FOR SOFTWARE PRODUCT LINE USING GENETIC ALGORITHM

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