Volume 11 Number 7 (Jul. 2016)
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JSW 2016 Vol.11(7): 664-676 ISSN: 1796-217X
doi: 10.17706/jsw.11.7.664-676

Determination of the Optimal Allocation of Testing Resource for Modular Software Reliability Growth Using LINGO

N. Ahmad1*, M. G. M. Khan2
1University Department of Statistics and Computer Applications, T. M. Bhagalpur University, Bhagalpur, India.
2School of Computing Information and Mathematical Sciences, the University of the South pacific, Suva, Fiji Island.

Abstract—It is quite natural to produce reliable software systems since the breakdown of the computer systems, which is caused by software faults, results in a tremendous loss and damage for social life. Hence, software reliability is a key factor in software development process. Testing phase of software begins with module testing whereby, modules are tested independently to remove substantial amount of faults within a specified testing resource. Therefore, in this paper four optimization problems are discussed for optimal allocation of testing resources for a modular software system. These optimization problems are formulated as nonlinear programming problems (NLPP), which incorporates log-logistic testing-effort function into inflection S-shaped software reliability growth model based on a non-homogeneous Poisson process. The NLPPs are solved using LINGO, a user-friendly software package for optimization. Finally, numerical example is given to demonstrate and to validate the performance of proposed strategies. In addition, the results of the strategies proposed in this paper are compared with [1]. It is revealed that the proposed strategies yield a gain in efficiency.

Index Terms—Software reliability growth model, resource allocation problem, nonlinear programming problem, dynamic programming technique, inflection S-shaped models.


Cite: N. Ahmad, M. G. M. Khan, "Determination of the Optimal Allocation of Testing Resource for Modular Software Reliability Growth Using LINGO," Journal of Software vol. 11, no. 7, pp. 664-676, 2016.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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