An application of Genetic Programming to Software Quality Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "T. M. Khoshgoftaar and M. P. Evett and E. B. Allen and 
                 P.-D. Chien",
  title =        "An application of Genetic Programming to Software
                 Quality Prediction",
  booktitle =    "Computational Intelligence in Software Engineering",
  publisher =    "World Scientific Publishing Co.",
  year =         "1998",
  editor =       "W. Pedrycz and J. F. Peters",
  volume =       "16",
  series =       "Advances in Fuzzy Systems-Applications and Theory",
  pages =        "175--195",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 evolutionary computation, software quality, software
                 reliability, fault-prone modules, software metrics,
                 software engineering",
  eisbn =        "9789812816153",
  URL =          "",
  DOI =          "doi:10.1142/9789812816153_0007",
  abstract =     "Because highly reliable software is becoming an
                 essential ingredient in many systems, software
                 developers apply various techniques to discover faults
                 early in development, such as more rigorous reviews,
                 more extensive testing, and strategic assignment of key
                 personnel. Our goal is to target reliability
                 enhancement activities to those modules that are most
                 likely to have problems. This paper presents a
                 methodology that incorporates genetic programming for
                 predicting the order of software modules based on the
                 expected number of faults. This is the first
                 application of genetic programming to software
                 engineering that we know of. We found that genetic
                 programming can be used to generate software quality
                 models whose inputs are software metrics collected
                 earlier in development, and whose output is a
                 prediction of the number of faults that will be
                 discovered later in development or during operations.
                 We established ordinal evaluation criteria for models,
                 and conducted an industrial case study of software from
                 a military communications system. Case study results
                 were sufficiently good to be useful to a project for
                 choosing modules for extra reliability enhancement
  notes =        "See also: An Application of Genetic Programming to
                 Software Quality Prediction, Technical report,
                 TR-CSE-97-60, Florida Atlantic Univ, September 1997

                 Empirical Software Engineering Laboratory, Department
                 of Computer Science and Engineering, Florida Atlantic
                 University, 777 W. Glades Road, Boca Raton, FL 333431,

Genetic Programming entries for Taghi M Khoshgoftaar Matthew P Evett Edward B Allen Pei-der Chien