Keywords
Automated Test Case Generation
How to Cite
Abstract
Test case generation is the most intellectually demanding and labor-intensive activity in software testing. It plays the most important role in the quality of software products and reduces testing costs. Among all these automated test case generation is the most emerging and challenging area in today’s research. Currently, several test case designing/generation tools exist but they are disorganized and unstructured since they are implementing various sets of parameters which is hard to categorize that’s why they are still misaligned with the current requirement of the software industry. There exists a real need to have such a Test Case generation framework that aligns functions of Automated Test Case Generation tools with the current requirements of the software industry. Thus aim of this research is to provide guidelines for the development of automated test case designing/generation tools. To do so we have performed a literature survey which identified six common referred tools and existing proposed frameworks. After that, an international questionnaire-based survey had been conducted in software industries to identify their challenges related to test case generation tools and desired parameters. The results indicated that industries are not satisfied with the current tools and need more sophisticated tools. After analysis, it is concluded that software test case generation is a long process that starts from the identification of parameter sets and ends with the test procedures. It is evident from the results that all assembling test sets activities are highly supported (by all variables) by large and medium scale organizations, highly experienced quality engineers, and organizations that are certified by CMMI (at levels 4 and 5) and ISO(9001 and 90003).
References
Lee, J., S. Kang, and D. Lee. "Survey on software testing practices." IET Software 6, no. 3 (2012): 275-282.
Nguyen, Bao N., Bryan Robbins, Ishan Banerjee, and AtifMemon. "GUITAR: an innovative tool for automated testing of GUI-driven software." Automated Software Engineering 21, no. 1 (2014): 65-105.
Vos, Tanja EJ, Beatriz Marin, Maria Jose Escalona, and Alessandro Marchetto. "A methodological framework for evaluating software testing techniques and tools." In Quality Software (QSIC), 2012 12th International Conference on, pp. 230-239. IEEE, 2012.
Stoyanova, Vera, DessislavaPetrova-Antonova, and Sylvia Ilieva. "Automation of Test Case Generation and Execution for Testing Web Service Orchestrations." In Service-Oriented System Engineering (SOSE), 2013 IEEE 7th International Symposium on, pp. 274-279. IEEE, 2013.
Tung, Yuan-Hsin, Shian-Shyong Tseng, Tsung-Ju Lee, and Jui-FengWeng. "A novel approach to automatic test case generation for web applications." In Quality Software (QSIC), 2010 10th International Conference on, pp. 399-404. IEEE, 2010.
Bertolini, Cristiano, and AlexandreMota. "A framework for GUI testing based on use case design." In Software Testing, Verification, and Validation Workshops (ICSTW), 2010 Third International Conference on, pp. 252-259. IEEE, 2010.
Hu, Yi-Tin, and Nai-Wei Lin. "Automatic black-box method-level test case generation based on constraint logic programming." In Computer Symposium (ICS), 2010 International, pp. 977-982. IEEE, 2010.
Sofokleous, Anastasis A., and Andreas S. Andreou. "Automatic, evolutionary test data generation for dynamic software testing." Journal of Systems and Software 81, no. 11 (2008): 1883-1898.
Abdou, Tamer, Peter Grogono, and PankajKamthan. "A Conceptual Framework for Open Source Software Test Process." In Computer Software and Applications Conference Workshops (COMPSACW), 2012 IEEE 36th Annual, pp. 458-463. IEEE, 2012.
Kasurinen, Jussi, OssiTaipale, and Kari Smolander. "Analysis of problems in testing practices." In Software Engineering Conference, 2009. APSEC'09. Asia-Pacific, pp. 309-315. IEEE, 2009.
Anand, Saswat, Edmund K. Burke, TsongYueh Chen, John Clark, Myra B. Cohen, Wolfgang Grieskamp, Mark Harman, Mary Jean Harrold, and Phil McMinn. "An orchestrated survey of methodologies for automated software test case generation." Journal of Systems and Software 86, no. 8 (2013): 1978-2001.
Vos, Tanja EJ, Arthur I. Baars, Felix F. Lindlar, Peter M. Kruse, Andreas Windisch, and Joachim Wegener. "Industrial scaled automated structural testing with the evolutionary testing tool." In Software Testing, Verification and Validation (ICST), 2010 Third International Conference on, pp. 175-184. IEEE, 2010.
Ng, S.P., Murnane, T., Reed, K., Grant, D., Chen, T.Y.: ‘A preliminary survey on software testing practices in Australia’. Proc. Conf. Australian Software Engineering, 2004, pp. 116–125
Garousi, Vahid, and JunjiZhi. "A survey of software testing practices in Canada." Journal of Systems and Software 86, no. 5 (2013): 1354-1376.
Wohlin, Claes, Per Runeson, Martin Höst, Magnus C. Ohlsson, BjörnRegnell, and Anders Wesslén. Experimentation in software engineering. Springer Science & Business Media, 2012.
Kasurinen, Jussi, OssiTaipale, and Kari Smolander. "Software test automation in practice: empirical observations." Advances in Software Engineering 2010 (2010).
Pfleeger, Shari Lawrence, and Barbara A. Kitchenham. "Principles of survey research part 2:
designing a survey." Software Engineering Notes 27, no. 1 (2002): 18-20.
Kitchenham, Barbara A., and Shari Lawrence Pfleeger. "Principles of survey research: part 3: constructing a survey instrument." ACM SIGSOFT Software Engineering Notes 27, no. 2 (2002): 20-24.
Pfleeger, Shari Lawrence, and Barbara A. Kitchenham. "Principles of survey research: part 1: turning lemons into lemonade." ACM SIGSOFT Software Engineering Notes 26, no. 6 (2001): 16-18.
Kitchenham, Barbara, and Shari Lawrence Pfleeger. "Principles of survey research part 4:
questionnaire evaluation." ACM SIGSOFT Software Engineering Notes 27, no. 3 (2002): 20-23.
Kitchenham, Barbara, and Shari Lawrence Pfleeger. "Principles of survey research: part 5:
populations and samples." ACM SIGSOFT Software Engineering Notes 27, no. 5 (2002): 17-20.
Kitchenham, Barbara, and Shari Lawrence Pfleeger. "Principles of survey research part 6: data
analysis." ACM SIGSOFT Software Engineering Notes 28, no. 2 (2003): 24-27.
Galler, Stefan J., and Bernhard K. Aichernig. "Survey on test data generation tools." International Journal on Software Tools for Technology Transfer 16, no. 6 (2014): 727-751.
Rafi, Dudekula Mohammad, Katam Reddy Kiran Moses, Kai Petersen, and Mika V. Mäntylä. "Benefits and limitations of automated software testing: Systematic literature review and practitioner survey." In Proceedings of the 7th International Workshop on Automation of Software Test, pp. 36-42. IEEE Press, 2012.
Abran, Alain, James W. Moore, Pierre Bourque, Robert Dupuis, and L. Tripp. "Guide to the software engineering body of knowledge, 2004 version." IEEE Computer Society 1 (2004).
Csallner, Christoph, and YannisSmaragdakis. "JCrasher: an automatic robustness tester for Java."
Software: Practice and Experience 34, no. 11 (2004): 1025-1050.
Wahid, M., and A. Almalaise. "JUnit framework: An interactive approach for basic unit testing learning in Software Engineering." In Engineering Education (ICEED), 2011 3rd International Congress on, pp. 159-164. IEEE, 2011.
Fraser, Gordon, and Andrea Arcuri. "Whole test suite generation." Software Engineering, IEEE Transactions on 39, no. 2 (2013): 276-291.
Fraser, Gordon, and Andrea Arcuri. "EvoSuite at the SBST 2013 Tool Competition." In ICST
Workshops, pp. 406-409. 2013.
De Castro, Andreza MFV, Gisele A. Macedo, Eliane F. Collins, and Arilo C. Dias-Neto. "Extension of Selenium RC tool to perform automated testing with databases in web applications." In Proceedings of the 8th International Workshop on Automation of Software Test, pp. 125-131. IEEE Press, 2013.
Alim, Affan, et al. "The most discriminant subbands for face recognition: A novel information- theoretic framework." International Journal of Wavelets, Multiresolution, and Information Processing 16.05 (2018): 1850040.
Bork, D., Roelens, B. A technique for evaluating and improving the semantic transparency of modeling language notations. Softw Syst Model 20, 939–963 (2021).
Cognitive Impairment and Dementia Data Model: Quality Evaluation and Improvements Dessislava Petrova-Antonova * and Sophia Lazarova GATE Institute, Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgari Received: 15 November 2022 / Revised: 6 January 2023 / Accepted: 27 January 2023 / Published: 30 January 2023.
Brady SS, Brubaker L, Fok CS, et al. Development of Conceptual Models to Guide Public Health Research, Practice, and Policy: Synthesizing Traditional and Contemporary Paradigms. Health Promotion Practice. 2020;21(4):510-524.