{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:53:40Z","timestamp":1778255620704,"version":"3.51.4"},"reference-count":11,"publisher":"World Scientific Pub Co Pte Lt","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Soft. Eng. Knowl. Eng."],"published-print":{"date-parts":[[1999,10]]},"abstract":"<jats:p> In this paper we present the results of an empirical study in which we have investigated Machine Learning (ML) algorithms with regard to their capabilities to accurately assess the correctability of faulty software components. Three different families algorithms have been analyzed: divide and conquer (top down induction decision tree), covering, and inductive logic programming (ILP). We have used (1) fault data collected on corrective maintenance activities for the Generalized Support Software reuse asset library located at the Flight Dynamics Division of NASA's GSFC and (2) product measures extracted directly from the faulty components of this library. In our data set, the software quality models generated by both C4.5-rules (a divide and conquer algorithm) and FOIL (an inductive logic programming one) presented the best results from the point of view of model accuracy. <\/jats:p>","DOI":"10.1142\/s0218194099000310","type":"journal-article","created":{"date-parts":[[2003,2,24]],"date-time":"2003-02-24T10:42:33Z","timestamp":1046083353000},"page":"565-593","source":"Crossref","is-referenced-by-count":14,"title":["AN INVESTIGATION ON THE USE OF MACHINE LEARNED MODELS FOR ESTIMATING SOFTWARE CORRECTABILITY"],"prefix":"10.1142","volume":"09","author":[{"given":"MAURICIO A.","family":"DE ALMEIDA","sequence":"first","affiliation":[{"name":"Laboratory of Integrated Systems, Av.  Prof. Luciano Gualberto, 158 S\u00e3o Paulo, SP Brazil 05508-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"HAKIM","family":"LOUNIS","sequence":"additional","affiliation":[{"name":"Centre de Recherche Informatique de Montr\u00e9al, 550, Sherbrooke O., #100 Montr\u00e9al, H3A 1B9, Qc, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"WALCELIO L.","family":"MELO","sequence":"additional","affiliation":[{"name":"Oracle Brazil and Catholic University of Brasilia, SCN Qd. 02 \u2013 Bl. A-Salas 604 Brasilia, DF Brazil 70712-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"p_4","first-page":"2","volume":"7","author":"Selby A. P","year":"1990","journal-title":"IEEE Software"},{"key":"p_8","first-page":"1","volume":"18","author":"Briand L.","year":"1992","journal-title":"IEEE TSE"},{"key":"p_12","first-page":"84","author":"Mao Y.","year":"1998","journal-title":"Automated Software Engineering Conference"},{"key":"p_14","first-page":"4","volume":"3","author":"Clark P.","year":"1989","journal-title":"Machine Learning Journal"},{"key":"p_15","first-page":"3","volume":"5","author":"Quinlan J. R.","year":"1990","journal-title":"Machine Learning Journal"},{"key":"p_17","first-page":"1","volume":"1","author":"Quinlan J. R.","year":"1986","journal-title":"Machine Learning Journal"},{"key":"p_21","first-page":"463","author":"Lounis H.","year":"1991","journal-title":"Lecture Notes in Artificial Intelligence"},{"key":"p_27","first-page":"3301","volume":"20742","author":"Briand L.","year":"1994","journal-title":"Technical Report, University of Maryland, Department of Computer Science, College Park, MD"},{"key":"p_29","doi-asserted-by":"publisher","DOI":"10.1016\/S0164-1212(96)00153-7"},{"key":"p_30","first-page":"1","volume":"27","author":"Basili V.","year":"1984","journal-title":"CA CM"},{"key":"p_32","first-page":"423","volume":"5","author":"Munson J.","year":"1992","journal-title":"IEEE TSE SE-18"}],"container-title":["International Journal of Software Engineering and Knowledge Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218194099000310","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T16:13:34Z","timestamp":1565194414000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218194099000310"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1999,10]]},"references-count":11,"journal-issue":{"issue":"05","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1999,10]]}},"alternative-id":["10.1142\/S0218194099000310"],"URL":"https:\/\/doi.org\/10.1142\/s0218194099000310","relation":{},"ISSN":["0218-1940","1793-6403"],"issn-type":[{"value":"0218-1940","type":"print"},{"value":"1793-6403","type":"electronic"}],"subject":[],"published":{"date-parts":[[1999,10]]}}}