Abstract
Software testing is a very important and crucial phase of software development life cycle. In order to develop good quality software, the effectiveness of the software has been tested. Test cases and test suites are prepared for testing, and it should be done in minimum time for which test case prioritization and optimization techniques are required. The main aim of test case prioritization is to test software in minimum time and with maximum efficiency, so for this there are many techniques, and to develop a new or better technique, existing techniques should be known. This paper presents a review on the techniques of test case prioritization and optimization. This paper also provides analysis of the literature available for the same.
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References
Qu, B., Nie, C., Xu, B.: Test case prioritization for multiple processing queues. In: ISISE’08 International Symposium on Information Science and Engineering, vol. 2, pp. 646–649. IEEE (2008)
Hla, K.H.S., Choi, Y. Park, J.S. Applying particle swarm optimization to prioritizing test cases for embedded real time software retesting. In: 8th International Conference on Computer and Information Technology Workshops, pp. 527–532. IEEE (2008)
Tyagi, M., Malhotra, S.: Test case prioritization using multi objective particle swarm optimizer. In: International Conference on Signal Propagation and Computer Technology (ICSPCT), pp. 390–395. IEEE (2014)
Simons, C., Paraiso, E.C.: Regression test cases prioritization using failure pursuit sampling. In: 10th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 923–928. IEEE (2010)
Nagar, R., Kumar, A., Kumar, S., Baghel, A.S.: Implementing test case selection and reduction techniques using meta-heuristics. In: Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference, pp. 837–842. IEEE (2014)
Ansari, A.S., Devadkar, K.K., Gharpure, P.: Optimization of test suite-test case in regression test. In: IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp. 1–4. IEEE (2013)
Elanthiraiyan, N., Arumugam, C.: Parallelized ACO algorithm for regression testing prioritization in hadoop framework. In: International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), pp. 1568–1571. IEEE (2014)
Sharma, N., Purohit, G.N.: Test case prioritization techniques-an empirical study. In: International Conference on High Performance Computing and Applications (ICHPCA), vol. 28(2), pp. 159–182. IEEE (2014)
Kruse, P.M., Schieferdecker, I. Comparison of approaches to prioritized test generation for combinatorial interaction testing. In: Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 1357–1364. IEEE (2012)
Stochel, M.G., Sztando, R.: Testing optimization for mission-critical, complex, distributed systems. In: 32nd Annual IEEE International Conference on Computer Software and Applications, 2008. COMPSAC’08, pp. 847–852. IEEE (2008)
Islam, M.M., Scanniello, G.: MOTCP: a tool for the prioritization of test cases based on a sorting genetic algorithm and latent semantic indexing. In: 28th IEEE International Conference on Software Maintenance (ICSM), pp. 654–657. IEEE (2012)
Sabharwal, S., Sibal, R., Sharma, C.: A genetic algorithm based approach for prioritization of test case scenarios in static testing. In: 2nd International Conference on Computer and Communication Technology (ICCCT), pp. 304–309. IEEE (2011)
Khan, S.U.R., Parizi, R.M., Elahi, M.: A code coverage-based test suite reduction and prioritization framework.In: Fourth World Congress on Information and Communication Technologies (WICT), pp. 229–234. IEEE (2014)
Harman, M.: Making the case for MORTO: multi objective regression test optimization. In: Fourth International Conference on Software Testing, Verification and Validation Workshops, pp. 111–114. IEEE (2011)
Noguchi, T., Sato, A.: History-based test case prioritization for black box testing using ant colony optimization. In: IEEE 8th International Conference on Software Testing, Verification and Validation (ICST), pp. 1–2. IEEE (2015)
Ma, Z., Zhao, J.: Test case prioritization based on analysis of program structure. In: Software Engineering Conference, 2008. APSEC’08. 15th Asia-Pacific, pp. 471–478. IEEE (2008)
Wu, K., Fang, C., Chen, Z., Zhao, Z.: Test case prioritization incorporating ordered sequence of program elements. In: Proceedings of the 7th International Workshop on Automation of Software Test, pp. 124–130. IEEE Press (2012)
Prakash, N., Rangaswamy, T.R.: Modular based multiple test case prioritization. In: IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp. 1–7. IEEE (2012)
Rugthaicharoencheep, N., Thongkeaw, S., Auchariyamet, S.: Economic load dispatch with daily load patterns using particle swarm optimization. In: Proceedings of 46th International Universities Power Engineering Conference (UPEC), pp. 1–5. VDE (2011)
Chauhan, N., Kumar, H.: A hierarchical test case prioritization technique for object oriented software. In: International Conference on Contemporary Computing and Informatics (IC3I), pp. 249–254. IEEE (2014)
Baudry, B., Fleurey, F., Jezequel, J.M., Le Traon, Y.: Automatic test case optimization using a bacteriological adaptation model: application to. net components. In: Proceedings of the ASE 2002. 17th IEEE International Conference on Automated Software Engineering, pp. 253–256. IEEE (2002)
Malhotra, R., Tiwari, D.: Development of a framework for test case prioritization using genetic algorithm. ACM SIGSOFT Softw. Eng. Notes 38(3), 1–6 (2013)
Mayan, J.A., Ravi, T.: Test case optimization using hybrid search technique. In: Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing. ACM (2014)
Arcuri, A., Briand, L.: Adaptive random testing: an illusion of effectiveness? In: Proceedings of the 2011 International Symposium on Software Testing and Analysis, pp. 265–275. ACM (2011)
Pastore, F., Mariani, L., Hyvärinen, A.E.J., Fedyukovich, G., Sharygina, N., Sehestedt, S., Muhammad, A.: Verification-aided regression testing. In: Proceedings of the 2014 International Symposium on Software Testing and Analysis, pp. 37–48. ACM (2014)
Gligoric, M., Negara, S. Legunsen, O., Marinov, D.: An empirical evaluation and comparison of manual and automated test selection. In: Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering, pp. 361–372. ACM (2014)
Baudry, B., Fleurey, F., Jézéquel, J.M., Le Traon, Y.: Automatic test case optimization: a bacteriologic algorithm. IEEE Softw. 22(2), 76–82 (2005)
Baudry, B., Fleurey, F., Jézéquel, J.M., Le Traon, Y.: Genes and bacteria for automatic test cases optimization in the. net environment. In: Proceedings of the 13th International Symposium on Software Reliability Engineering, ISSR, pp. 195–206. IEEE (2002)
Liu, W., Dasiewicz, P.: The event-flow technique for selecting test cases for object-oriented programs. In: Canadian Conference on Engineering Innovation: Voyage of Discovery, vol. 1, pp. 257–260. IEEE (1997)
Hoseini, B., Jalili, S.: Automatic test path generation from sequence diagram using genetic algorithm. In: 7th International Symposium on Telecommunications (IST), pp. 106–111. IEEE (2014)
Mahajan, S., Joshi, S.D., Khanaa, V.: Component-based software system test case prioritization with genetic algorithm decoding technique using java platform. In: International Conference on Computing Communication Control and Automation, pp. 847–851. IEEE (2015)
Panichella, A., Oliveto, R., Di Penta, M., De Lucia, A.: Improving multi-objective test case selection by injecting diversity in genetic algorithms. IEEE Trans. Softw. Eng. 41(4), 358–383 (2015)
Valdez, F., Melin, P., Mendoza, O.: A new evolutionary method with fuzzy logic for combining particle swarm optimization and genetic algorithms: the case of neural networks optimization. In: International Joint Conference on Neural Networks, IJCNN, (IEEE World Congress on Computational Intelligence), pp. 1536–1543. IEEE (2008)
Karnavel, K., Santhosh Kumar, J.: Automated software testing for application maintenance by using bee colony optimization algorithms (BCO). In: International Conference on Information Communication and Embedded Systems (ICICES), pp. 327–330. IEEE (2013)
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Saraswat, P., Singhal, A., Bansal, A. (2019). A Review of Test Case Prioritization and Optimization Techniques. In: Hoda, M., Chauhan, N., Quadri, S., Srivastava, P. (eds) Software Engineering. Advances in Intelligent Systems and Computing, vol 731. Springer, Singapore. https://doi.org/10.1007/978-981-10-8848-3_48
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DOI: https://doi.org/10.1007/978-981-10-8848-3_48
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