• DocumentCode
    257629
  • Title

    Decisively: Application of Quantitative Analysis and Decision Science in Agile Requirements Engineering

  • Author

    Saxena, S.K. ; Chakraborty, Rupak

  • Author_Institution
    GrayPE Syst. (P) Ltd., Noida, India
  • fYear
    2014
  • fDate
    25-29 Aug. 2014
  • Firstpage
    323
  • Lastpage
    324
  • Abstract
    While many mature Requirements Engineering (RE) tools for Agile exist, RE professionals at large have not been able to benefit from Quantitative Analysis and Decision Science (QUADS) techniques in this context. In this paper we present an Agile RE tool, Decisively, which brings a new perspective to automation in the RE process through application of QUADS to address Requirement Discovery, Analysis, Estimation and Prioritization. Techniques explored in Decisively include Analytical Hierarchical Process (AHP) for prioritization and estimation, Lorenz function to shortlist user stories by analyzing the distribution of votes, Box Plot Analysis to predict velocity, and Text Mining to discover implied requirements from documents.
  • Keywords
    analytic hierarchy process; formal specification; software prototyping; software tools; Agile RE tool; Agile requirements engineering; Decisively; Lorenz function; analytical hierarchical process; automation; box plot analysis; quantitative analysis and decision science techniques; requirement analysis; requirement discovery; requirement estimation; requirement prioritization; text mining; user story shortlisting; velocity prediction; vote distribution analysis; Context; Decision making; Educational institutions; Estimation; Real-time systems; Statistical analysis; Text mining; AHP; Agile; Box Plot; Quantitative Analysis & Decision Science; Requirements Prioritization; SPAN; Story Points Estimation; Text Mining; Velocity Prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Requirements Engineering Conference (RE), 2014 IEEE 22nd International
  • Conference_Location
    Karlskrona
  • Print_ISBN
    978-1-4799-3031-9
  • Type

    conf

  • DOI
    10.1109/RE.2014.6912278
  • Filename
    6912278