Empirical evaluation of a fuzzy logic-based software quality predication model

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 560
  • Download : 0
Software inspection, due to its repeated success on industrial applications, has now become an industry standard practice. Recently, researchers began analyzing inspection data to obtain insights on how software processes can be improved. For example, project managers need to identify potentially error-prone software components so that limited project resource may be optimally allocated. This paper proposes an automated and fuzzy logic-based approach to satisfy such a need. Fuzzy logic offers significant advantages over other approaches due to its ability to naturally represent qualitative aspect of inspection data and apply flexible inference rules. In order to empirically evaluate the effectiveness of our approach, we have analyzed published inspection data and the ones collected from two separate inspection experiments which we had conducted. X 2 analysis is applied to statistically demonstrate validity of the proposed quality prediction model. (C) 2002 Elsevier Science B.V. All rights reserved.
Publisher
Elsevier Science Bv
Issue Date
2002-04
Language
English
Article Type
Article
Keywords

INSPECTION METHOD; CODE INSPECTIONS; EXPERIENCE

Citation

FUZZY SETS AND SYSTEMS, v.127, no.2, pp.199 - 208

ISSN
0165-0114
URI
http://hdl.handle.net/10203/79892
Appears in Collection
CS-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0