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One of the major chronic problems in software development is the fact that application requirements are almost never stable and fixed. Creeping user requirements have been troublesome since the software industry began. Several empirical studies have reported that volatile requirements are a challenging factor in most information systems development projects. Software process simulation modeling has increasingly been used for a variety of issues during software development. The management of software development risks is one of them. This study presents an approach for simulating and analyzing the effect of Requirements Creep on certain software development risk management activities. The proposed algorithm is based on stochastic simulation and has been implemented using C.
Shilpa Rani. 2014. \u201cStochastically Simulating the Effects of Requirements Creep on Software Development Risk Management\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 102
Country: India
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: P.K. Suri, Shilpa Rani (PhD/Dr. count: 0)
View Count (all-time): 236
Total Views (Real + Logic): 8999
Total Downloads (simulated): 2295
Publish Date: 2014 05, Thu
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One of the major chronic problems in software development is the fact that application requirements are almost never stable and fixed. Creeping user requirements have been troublesome since the software industry began. Several empirical studies have reported that volatile requirements are a challenging factor in most information systems development projects. Software process simulation modeling has increasingly been used for a variety of issues during software development. The management of software development risks is one of them. This study presents an approach for simulating and analyzing the effect of Requirements Creep on certain software development risk management activities. The proposed algorithm is based on stochastic simulation and has been implemented using C.
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