Comparison of usage of crowdsourcing in traditional and agile software development methodologies on the basis of effectiveness

Himanshu Pandey

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The authors here try to forecast the Effort in Person Months for developing Agile and the traditional way of software development including Prototyping. The comparison is made on the basis of considering both Agile and traditional software development methodologies in addition to the crowdsourcing paradigm applied to both approaches. DNA Matcher (DNAM) has been developed using both prototyping and Agile software development with crowd sourcing. For Agile development, first of all COCOMO II Model is applied on it utilizing the crowdsourcing technique. The authors have determined that Agile development proves to be considerably economical when both techniques use crowdsourcing. The case study used here is DNAM. First DNAM was developed using traditional prototyping methods. During its analysis, costing is done. This is done in accordance with the crowdsoursing used in parallel to the Prototyping method. The time and effort in Person Months (PM) was known. Then AGILE development methodology is used in the development of DNAM. Agile is used along with the crowdsourcing paradigm. As soon as the analysis phase is completed, Simple Build-up Approach forecasts the time and effort in terms of Number of Iterations and Person Months and we compare the results of Effort and Cost of both the techniques. The Agile method is found to be both, less in cost and effort, thereby increasing the Effectiveness and Efficiency of the progression of Software development.

Original languageEnglish
Pages (from-to)32-44
Number of pages13
JournalReliability: Theory and Applications
Volume13
Issue number3
StatePublished - 1 Sep 2018
Externally publishedYes

Keywords

  • Agile software development
  • COCOMO
  • Crowdsourcing
  • Genomic information retrieval
  • Simple build-up method

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Safety Research
  • Statistics, Probability and Uncertainty

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