Premium
Ranking of software engineering metrics by fuzzy‐based matrix methodology
Author(s) -
Garg R. K.,
Sharma Kapil,
Nagpal C. K.,
Garg Rakesh,
Garg Rajpal,
Kumar Rajive
Publication year - 2013
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/stvr.459
Subject(s) - ranking (information retrieval) , computer science , vagueness , software , data mining , expert elicitation , set (abstract data type) , fuzzy logic , function (biology) , rank (graph theory) , ambiguity , software engineering , machine learning , artificial intelligence , mathematics , statistics , combinatorics , evolutionary biology , biology , programming language
SUMMARY This research paper presents a framework for ranking of software engineering metrics based on expert opinion elicitation and fuzzy‐based matrix methodology. The proposed methodology is able to accommodate the imprecise and inexact data involved in the problem of ranking of software engineering metrics, vagueness and ambiguity occurring during expert (human) decision making and to depart from the complexity of formulation of the objective and the constraint function. The matrices lend themselves to mechanical manipulations and are useful for analyzing and deriving systems functions expeditiously to meet the objectives. The current research is based on software engineering metrics identified in an earlier study conducted by Lawrence Livermore National Laboratory. A set of ranking criteria were identified. Software engineering metrics are then ranked in ascending order using experts' opinion in accordance with the value of Permanent function on their criteria matrix. The proposed methodology has also been compared with other known methodologies. Copyright © 2011 John Wiley & Sons, Ltd.