• DocumentCode
    2602910
  • Title

    A Multi-criteria Decision Making Approach for Resource Allocation in Software Engineering

  • Author

    Otero, Carlos E. ; Otero, Luis D. ; Weissberger, Ira ; Qureshi, Abrar

  • Author_Institution
    Dept. of Math. & Comput. Sci., Univ. of Virginia´´s Coll. at Wise, Wise, VA, USA
  • fYear
    2010
  • fDate
    24-26 March 2010
  • Firstpage
    137
  • Lastpage
    141
  • Abstract
    The completion of reliable software products within the expected time frame represents a major problem for companies that develop software applications. As the field grows, the software industry continues to struggle with delivering products in a timely manner. A major cause for increased cost and low quality in software products can be attributed to inadequate resource allocation. Therefore, it is important to develop systematic personnel assignment processes that consider the complete candidate skill set and provide the best fit to increase quality, reduce cost, and reduce training time. This paper presents a novel methodology that considers multiple project-specific skills to assign resources to software tasks. The methodology takes into account the existing capabilities of candidates to determine the best fit based on the required skills for the task. A sample case study is used to show the methodology´s capabilities.
  • Keywords
    resource allocation; software engineering; software houses; software reliability; multicriteria decision making approach; reliable software product; resource allocation; software engineering; software industry; Computational modeling; Costs; Decision making; Mathematical model; Personnel; Productivity; Programming; Resource management; Software engineering; Software quality; Desirability Functions; Multi-Critieria Resource Allocation; Resource Allocation; Software Engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modelling and Simulation (UKSim), 2010 12th International Conference on
  • Conference_Location
    Cambridge
  • Print_ISBN
    978-1-4244-6614-6
  • Type

    conf

  • DOI
    10.1109/UKSIM.2010.32
  • Filename
    5481062