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Volumn , Issue , 2011, Pages 69-74

How many software metrics should be selected for defect prediction?

Author keywords

[No Author keywords available]

Indexed keywords

BUILDING DEFECTS; DEFECT PREDICTION; DEFECT PREDICTION MODELS; EMPIRICAL CASE STUDIES; FEATURE SUBSET; MODEL PERFORMANCE; REAL WORLD PROJECTS; SELECTION OF SOFTWARE; SOFTWARE MEASUREMENT DATA; SOFTWARE METRICS; SOFTWARE PRACTITIONERS;

EID: 80052408958     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (55)

References (10)
  • 1
    • 28244470710 scopus 로고    scopus 로고
    • Finding the right data for software cost modeling
    • DOI 10.1109/MS.2005.151
    • Chen, Z.; Menzies, T.; Port, D.; and Boehm, B. 2005. Finding the right data for software cost modeling. IEEE Software (22):38-46. (Pubitemid 41709723)
    • (2005) IEEE Software , vol.22 , Issue.6 , pp. 38-46
    • Chen, Z.1    Menzies, T.2    Port, D.3    Boehm, B.4
  • 2
    • 33646023117 scopus 로고    scopus 로고
    • An introduction to ROC analysis
    • Fawcett, T. 2006. An introduction to ROC analysis. Pattern Recognition Letters 27(8):861-874.
    • (2006) Pattern Recognition Letters , vol.27 , Issue.8 , pp. 861-874
    • Fawcett, T.1
  • 6
    • 17044405923 scopus 로고    scopus 로고
    • Toward integrating feature selection algorithms for classification and clustering
    • DOI 10.1109/TKDE.2005.66
    • Liu, H., and Yu, L. 2005. Toward integrating feature selection algorithms for classification and clustering. IEEE Transactions on Knowledge and Data Engineering 17(4):491-502. (Pubitemid 40495592)
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.4 , pp. 491-502
    • Liu, H.1    Yu, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.