Reducing Quantization Error and Contextual Bias problems in Software Development Processes by Applying Fuzzy Logic

Francesco Marcelloni, Mehmet Aksit

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

    5 Citations (Scopus)
    102 Downloads (Pure)

    Abstract

    Object-oriented methods define a considerable number of rules, which are generally expressed using two-valued logic. For example, an entity in a requirement specification is either accepted or rejected as a class. There are two major problems how rules are defined and applied in current methods. Firstly, two-valued logic cannot effectively express the approximate and inexact nature of a typical software development process. Secondly, the influence of contextual factors on rules is generally not modeled explicitly. This paper terms these problems as quantization error and contextual bias problems, respectively. To reduce these problems, we adopt fuzzy logic-based methodological rules. This approach is method independent and is useful for evaluating and enhancing current methods. In addition, the use of fuzzy-logic increases the adaptability and reusability of design models.
    Original languageUndefined
    Title of host publicationNAFIPS'99
    Place of PublicationNew York, USA
    PublisherIEEE
    Pages268-272
    Number of pages5
    ISBN (Print)0780352114
    DOIs
    Publication statusPublished - Jul 1999
    EventNAFIPS'99 - New York, USA
    Duration: 10 Jun 199912 Jun 1999

    Publication series

    Name
    PublisherIEEE

    Conference

    ConferenceNAFIPS'99
    Period10/06/9912/06/99
    Other10 - 12 June 1999

    Keywords

    • IR-18374
    • METIS-118894
    • EWI-10143

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