Using Bayesian belief networks to model software project management antipatterns

Dimitrios Settas, Stamatia Bibi, Panagiotis Sfetsos, Ioannis Stamelos, Vassilis Gerogiannis

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    20 Citations (Scopus)

    Abstract

    In spite of numerous traditional and agile software project management models proposed, process and project modeling still remains an open issue. This paper proposes a Bayesian Network (BN) approach for modeling software project management antipatterns. This approach provides a framework for project managers, who would like to model the cause-effect relationships that underlie an antipattern, taking into account the inherent uncertainty of a software project. The approach is exemplified through a specific BN model of an antipattern. The antipattern is modeled using the empirical results of a controlled experiment on Extreme Programming (XP) that investigated the impact of developer personalities and temperaments on communication, collaboration-pair viability and effectiveness in pair programming. The resulting BN model provides the precise mathematical model of a project management antipattern and can be used to measure and handle uncertainty in mathematical terms.

    Original languageEnglish
    Title of host publicationProceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006
    Pages117-124
    Number of pages8
    DOIs
    Publication statusPublished - 2006
    Event4th International Conference on Software Engineering Research, Management and Applications, SERA 2006 - Seattle, WA, United States
    Duration: 9 Aug 200611 Aug 2006

    Other

    Other4th International Conference on Software Engineering Research, Management and Applications, SERA 2006
    Country/TerritoryUnited States
    CitySeattle, WA
    Period9/08/0611/08/06

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