A Practical Approach for Evaluating and Prioritizing Situational Factors in Global Software Project Development
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 7
Abstract
There has been an enormous increase in globaliza-tion that has led to more cooperation and competition across boundaries. Software engineering, particularly distributed soft-ware development (DSD) and global software development (GSD), is evolving rapidly and presents several challenges, such as ge-ographical separations, temporal differences, cultural variations, and management strategies. As a result, a variety of situational factors (SFs) arise that causes challenging problems in software development. Both literature and real world software industry study revealed that the extent of the effect of SFs may vary subject to a certain software project. Project executives should need to concentrate on the right SFs for the successful development of a specific project. This work first examines the optimal and most well-balanced GSD-related SFs and then presents a mechanism for prioritizing the SFs to better understand the extent to which an SF generally affects the GSD. A set of 56 SFs in 11 categories is identified and analyzed in this research. A fuzzy set theory based, multi criteria decision making (MCDM) technique, fuzzy analytical hierarchy process (FAHP) was proposed to extract the SFs that have the strongest effects on GSD. The proposed technique is intelligent and automated and can be customized to suit specific conditions and environments. Thus, it can provide support for a much-needed variation that is the hallmark of such software development environments. A case study of a global company working in collaboration on a project JKL was selected to identify and prioritize the most challenging SFs. A sensitivity analysis is carried out to evaluate the extent of the impact for highly ranked SFs related to JKL project.
Authors and Affiliations
Kanza Gulzar, Jun Sang, Adeel Akbar Memon, Muhammad Ramzan, Xiaofeng Xia, Hong Xiang
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