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Home»Articles»A Technique for Regression Testing of Object Oriented Software

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Asian Journal of Computer Science and Technology (AJCST)

Editor Dr. K. Ganesh
Print ISSN : 2249-0701
Frequency : Quarterly

A Technique for Regression Testing of Object Oriented Software

Author : Vedpal and Naresh Chauhan
Volume 7 No.1 January-June 2018 pp 87-92

Abstract

The main challenge in testing an OOS is that there are large number of test cases which are not feasible to execute all of them within constrained time and budget. This paper proposes some factors which can be used to prioritize the test cases in order to have an effective testing. The considered factors are based on the testing history and structured analysis of the software. These factors may be nature of bug, capability of a test case, execution time, business impact, coverage of code in terms of classes(old and new classes), etc. Every factor has been assigned a positive weight which shows the criticality of the factor and ability to introduce the errors in the software. The prioritized set of test cases thus obtained is helpful to discover maximum bugs as early as possible.

Keywords

Regression testing, test case prioritization, history based regression testing

Full Text:

References

[1] N. Chauhan, “Software Testing Principles and Practices”, Oxford University Press, 2010.
[2] Y. Tak Yu, M. Fai Lau, “Fault-based test suite prioritization for specification-based testing”, Information and Software Technology, Vol. 54, pp. 179–202, 2012.
[3] M. Abdollahi Khalilian and Y. Fazlalizadeh Azgomi, “An improved method for test case prioritization by incorporatinghistorical test case data”, Science of Computer Programming, Vol. 78, pp. 93–116, 2012.
[4] Y.Chi Huangc, K.Li Penga, C.Yu Huang, “A history-based cost-cognizant test case prioritization technique in regression Testing”, The Journal of Systems and Software, Vol. 85, pp. 626– 637, 2012.
[5] E. Rogstad, L. Briand and R. Torkar, “Test case selection for black-box regression testing of databaseApplications”, Information and Software Technology, 2013.
[6] S. Malhotra and S. Chaudhary, “Programming in Java”, Oxford University Press, 2014.
[7] P G Sapna and A. Balakrishnan, “An Approach for Generating Minimal Test Cases for RegressionTesting”, Procedia Computer Science, Vol. 47, pp. 188 – 196, 2015.
[8] W.K. Jianga Chan, “Input-based adaptive randomized test case prioritization: A local beam search approach”, Journal of Systems and Software, Vol. 105, pp. 91-106, July 2015.
[9] S. Jafrin, D. Nandi and S. Mahmood, “Test Case Prioritization based on Fault Dependency” I.J. Modern Education and Computer Science, Vol. 4, pp. 33-45, 2016. [Online] Available: http://www.mecs-press.org/DOI:10.5815/ijmecs.2016.04.05
[10] Ansari, A. Khan and K. Mukadam, “Optimized Regression Test using Test Case Prioritization” 7th International Conference on Communication, Computing and Virtualization 2016, Procedia Computer Science, Vol. 79, pp. 152 – 160, 2016.
[11] A. Bertolino Miranda, “ Scope-aided test prioritization, selection and minimization for software reuse”, The Journal of Systems and Software, pp. 1–22, 2016.
[12] S. Ghai and S. Kaur, “A Hill-Climbing Approach for Test Case Prioritization”, International Journal of Software Engineering and Its Applications, Vol. 11, No. 3, pp. 13-20, 2017. [Online] Available: http://dx.doi.org/10.14257/ijseia.2017.11.3.02
[13] W. FU, H. YU, G. FAN, and X. JI, “Coverage-Based Clustering and Scheduling Approach for Test CasePrioritization”, IEICE TRANS. INF. & SYST., Vol. E100–D, No.6, June 2017.
[14] W. Rhmann and V. Saxena, “ Fuzzy Expert System Based Test Cases Prioritization from UML State Machine Diagram using Risk Information”, I.J. Mathematical Sciences and Computing, Vol. 1, pp. 17-27, 2017. [Online] Available: http://www.mecs-press.net DOI: 10.5815/ijmsc.2017.01.02
[15] S. Nayak, C. Kumar and S. Tripathi, “Enhancing Efficiency of the Test Case Prioritization Techniqueby Improving the Rate of Fault Detection”, Arab J Sci Eng, DOI 10.1007/s13369-017-2466-6
[16] H. Do Schwartz, “Cost-effective Regression Testingthrough Adaptive Test Prioritization Strategies”, The Journal of Systems & Software, S0164-1212(16)00016-9DOI: 10.1016/j.jss.2016.01.018 Reference: JSS 9661. AJCST

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The main challenge in testing an OOS is that there are large number of test cases which are not feasible to execute all of them within constrained time and budget. This paper proposes some factors which can be used to prioritize the test cases in order to have an effective testing. The considered factors are based on the testing history and structured analysis of the software. These factors may be nature of bug, capability of a test case, execution time, business impact, coverage of code in terms of classes(old and new classes), etc. Every factor has been assigned a positive weight which shows the criticality of the factor and ability to introduce the errors in the software. The prioritized set of test cases thus obtained is helpful to discover maximum bugs as early as possible.

Editor-in-Chief
Dr. K. Ganesh
Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
Expert at McKinsey and Company, India
[email protected]
Editorial Advisory Board
Dr. Eng. Hamid Ali Abed AL-Asadi
Department of Computer Science, Basra University, Iraq
[email protected]
Dr. Norjihan Binti Abdul Ghani
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Christos Bouras
Department of Computer Engineering & Informatics, University of Patras, Greece
[email protected]
Dr. Maizatul Akmar Binti Ismail
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Harold Castro
Department of Systems Engineering and Computing, University of the Andes, Colombia
[email protected]
Dr. Busyairah Binti Syd Ali
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. Sri Devi Ravana
Department of Information system, University of Malaya, Malaysia
[email protected]
Dr. Karpaga Selvi Subramanian
Department of Computer Engineering, Mekelle University, Ethiopia
[email protected]
Dr. Mazliza Binti Othman
Department of Computer System & Technology, University of Malaya, Malaysia
[email protected]
Dr. Chiam Yin Kia
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. OUH Eng Lieh
Department of Information Systems, Singapore Management University, Singapore
[email protected]

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    Editorial Note

    Editorial Dr. K. Ganesh

    Editor-in-Chief
    Dr. K. Ganesh
    Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
    Expert at McKinsey and Company, India
    [email protected]
    Editorial Advisory Board
    Dr. Eng. Hamid Ali Abed AL-Asadi
    Department of Computer Science, Basra University, Iraq
    [email protected]
    Dr. Norjihan Binti Abdul Ghani
    Department of Information System, University of Malaya, Malaysia
    [email protected]edu.my
    Dr. Christos Bouras
    Department of Computer Engineering & Informatics, University of Patras, Greece
    [email protected]
    Dr. Maizatul Akmar Binti Ismail
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Harold Castro
    Department of Systems Engineering and Computing, University of the Andes, Colombia
    [email protected]
    Dr. Busyairah Binti Syd Ali
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. Sri Devi Ravana
    Department of Information system, University of Malaya, Malaysia
    [email protected]
    Dr. Karpaga Selvi Subramanian
    Department of Computer Engineering, Mekelle University, Ethiopia
    [email protected]
    Dr. Mazliza Binti Othman
    Department of Computer System & Technology, University of Malaya, Malaysia
    [email protected]
    Dr. Chiam Yin Kia
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. OUH Eng Lieh
    Department of Information Systems, Singapore Management University, Singapore
    [email protected]

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