Knowledge based evaluation of software systems: a case study
Identifieur interne : 000264 ( France/Analysis ); précédent : 000263; suivant : 000265Knowledge based evaluation of software systems: a case study
Auteurs : I. Stamelos [Grèce] ; I. Vlahavas [Grèce] ; I. Refanidis [Grèce] ; A. Tsoukiàs [France]Source :
- Information and Software Technology [ 0950-5849 ] ; 1999.
English descriptors
Abstract
Solving software evaluation problems is a particularly difficult software engineering process and many contradictory criteria must be considered to reach a decision. Nowadays, the way that decision support techniques are applied suffers from a number of severe problems, such as naive interpretation of sophisticated methods and generation of counter-intuitive, and therefore most probably erroneous, results. In this paper we identify some common flaws in decision support for software evaluations. Subsequently, we discuss an integrated solution through which significant improvement may be achieved, based on the Multiple Criteria Decision Aid methodology and the exploitation of packaged software evaluation expertise in the form of an intelligent system. Both common mistakes and the way they are overcome are explained through a real world example.
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DOI: 10.1016/S0950-5849(99)00093-2
Affiliations:
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<front><div type="abstract" xml:lang="en">Solving software evaluation problems is a particularly difficult software engineering process and many contradictory criteria must be considered to reach a decision. Nowadays, the way that decision support techniques are applied suffers from a number of severe problems, such as naive interpretation of sophisticated methods and generation of counter-intuitive, and therefore most probably erroneous, results. In this paper we identify some common flaws in decision support for software evaluations. Subsequently, we discuss an integrated solution through which significant improvement may be achieved, based on the Multiple Criteria Decision Aid methodology and the exploitation of packaged software evaluation expertise in the form of an intelligent system. Both common mistakes and the way they are overcome are explained through a real world example.</div>
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