Statistical Analysis of the Effects of Heavyweight and Lightweight Methodologies on the Six-Pointed Star Model

Muhammad Azeem Akbar, Jun Sang, Arif Ali Khan, Fazal E. Amin, Nasrullah, Shahid Hussain, Mohammad Khalid Sohail, Hong Xiang, Bin Cai

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

Traditionally, software development organizations relied on heavyweight development methodologies, such as waterfall, V-model, and others. Later, agile development methodologies known as lightweight methodologies were introduced. Many considered these to be more flexible and more effective than heavyweight methodologies. Both methodologies are equally important for a software development life cycle. The purpose of adopting software development methodologies is to optimize the process model to achieve milestones while concurrently and effectively managing time, budget, and quality. The literature review reveals that there is a lack of statistical evidence for determining the effect of both methodologies on the six-pointed star model (schedule, scope, budget, risk, resource, and quality). In this paper, statistical comparisons were performed for the effects of both methodologies on each factor of the six-pointed star model and the interdependency among factors. Numerical analyses were conducted based on survey responses collected from the experienced users of both methodologies. After examining the results of all the factors of both methodologies, it was determined that lightweight methodologies are suitable for small-scale projects and that heavyweight methodologies perform better for medium- and large-scale projects.

Original languageEnglish (US)
Pages (from-to)8066-8079
Number of pages14
JournalIEEE Access
Volume6
DOIs
StatePublished - Feb 12 2018

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering
  • Electrical and Electronic Engineering

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