Lightweight Risk Management in Agile projects

Edzreena Odzaly, Desmond Greer, Darryl Stewart

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

8 Citations (Scopus)
709 Downloads (Pure)


Risk management in software engineering has become a recognized project management practice but it seems that not all companies are systematically applying it. At the same time, agile methods have become popular, partly because proponents claim that agile methods implicitly reduce risks due
to, for example, more frequent and earlier feedback, shorter periods of development time and easier prediction of cost. Therefore, there is a need to investigate how risk management can be usable in iterative and evolutionary software development processes. This paper investigates the gathering of empirical data on risk management from the project environment and presents
a novel approach to manage risk in agile projects. Our approach is based on a prototype tool, Agile Risk Tool (ART). This tool reduces human effort in risk management by using software agents to identify, assess and monitor risk, based on input and data collected from the project environment and by applying
some designated rules. As validation, groups of student project data were used to provide evidence of the efficacy of this approach. We demonstrate the approach and the feasibility of using a lightweight risk management tool to alert, assess and monitor risk with reduced human effort.
Original languageEnglish
Title of host publicationProceedings: 26th International Conference on Software Engineering & Knowledge Engineering (SEKE 2014)
Number of pages6
ISBN (Electronic)9781510841581
Publication statusPublished - 01 Jul 2014
Event26th Software Engineering Knowledge Engineering Conference - British Columbia, Vancouver, Canada
Duration: 01 Jul 201403 Jul 2014


Conference26th Software Engineering Knowledge Engineering Conference


  • software risk, risk management,
  • agile projects

ASJC Scopus subject areas

  • Software
  • Computer Science (miscellaneous)


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