Software engineering in an effective collaborative environment: An evaluative study on crowdsourcing platforms

Hani Al-Bloush, Badariah Solemon

Research output: Contribution to journalArticle

Abstract

Crowdsourcing gathers the world’s software engineering experts on a specific subject matter, and allows organisations and individuals to employ the combined effort of these ‘experts’ to accomplish the software task at hand. However, leveraging the knowledge of experts will not be achieved without online crowdsourcing platforms, which makes communication possible. This study intends to evaluate the performance of four Crowdsourced Software Engineering(CSE) platforms (TopCoder, InnoCentive, AMT and Upwork) based on the criteria of the Web of System Performance (WOSP) model. The WOSP criteria include functionality, usability, security, extendibility, reliability, flexibility, connectivity and privacy. Findings from the analyses showed that the four CSE platforms vary in all of their features, and at the same time, they all lack the requirements of flexibility. The results provide insight into the current status of CSE platforms and highlight the gaps inherent in these platforms while offering a more complete picture. This study contributes to work on enhancing the design of current and future platforms.

Original languageEnglish
Pages (from-to)27-38
Number of pages12
JournalPertanika Journal of Science and Technology
Volume25
Issue numberS10
Publication statusPublished - 01 Oct 2017

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Crowdsourcing
Software engineering
engineering
Software
software
expert opinion
communication (human)
Privacy
connectivity
Organizations
communication
Communication

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Chemical Engineering(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Cite this

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Software engineering in an effective collaborative environment : An evaluative study on crowdsourcing platforms. / Al-Bloush, Hani; Solemon, Badariah.

In: Pertanika Journal of Science and Technology, Vol. 25, No. S10, 01.10.2017, p. 27-38.

Research output: Contribution to journalArticle

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