• DocumentCode
    3170171
  • Title

    Estimating and improving the probability of success of a software project by analysing the factors involved using data mining

  • Author

    Prasad, Athul ; Arsiwala, Juzer ; Singh, Praval Pratap

  • Author_Institution
    Comput. Sci. & Eng., Nat. Inst. of Technol., Warangal, India
  • fYear
    2010
  • fDate
    29-30 Oct. 2010
  • Firstpage
    391
  • Lastpage
    394
  • Abstract
    Software project management is the art and science of planning and leading software projects. It is a subdiscipline of project management in which software projects are planned, monitored and controlled. To ensure that a certain software project is successful is the main responsibility of the project manager. From the point of view of a project manager, a success is defined as: Did the system come in “up to specifications”, in time and on budget? Many factors come into play in deciding the success of the project such as project management, customer involvement etc. In this paper, online survey is used to collect project data about a number of factors upon which the outcome of the project depends. Data mining tools such as Association Rule Mining, Naive Bayes, Decision Tree and Neural networks are used to determine whether a project will be successful or not. In addition to that, it also finds out the most important factors guiding the project to success and determine the changes required to turn an unsuccessful project into a successful one.
  • Keywords
    Bayes methods; data mining; decision trees; neural nets; project management; software development management; Naive Bayes; association rule mining; data mining; decision tree; neural network; project data; software project management; software project success; Chaos; Databases; data mining; factor; software project management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Education (ICAIE), 2010 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-6935-2
  • Type

    conf

  • DOI
    10.1109/ICAIE.2010.5641159
  • Filename
    5641159