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Volumn , Issue , 2008, Pages 197-206

Cost curve evaluation of fault prediction models

Author keywords

[No Author keywords available]

Indexed keywords

BEST MODEL; COST CURVES; DEVELOPMENT COSTS; FAULT PREDICTION; FAULT-PRONE; FAULT-PRONE COMPONENTS; MISCLASSIFICATION; MISCLASSIFICATION COSTS; MODEL EVALUATION; PUBLIC REPOSITORIES; SOFTWARE COMPONENT; SOFTWARE MODULES; SOFTWARE QUALITY; SOFTWARE QUALITY MODELS; SPECIFIC COST; STANDARD METHOD; STATISTICAL TECHNIQUES; SYSTEM FAILURES; VERIFICATION ACTIVITIES;

EID: 67249086374     PISSN: 10719458     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISSRE.2008.54     Document Type: Conference Paper
Times cited : (47)

References (18)
  • 5
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • DOI 10.1023/A:1010933404324
    • L. Breiman. Random forests. Machine Learning, 45:5-32, 2001. (Pubitemid 32933532)
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 6
    • 67249116357 scopus 로고    scopus 로고
    • Return on investment for iv&v
    • Results available from
    • J. Dabney. Return on investment for iv&v. 2002- 2004,NASA funded study. Results available from http://sarpresults.ivv.nasa.gov/ViewResearch/24. jsp.
    • (2002) NASA Funded Study
    • Dabney, J.1
  • 7
    • 33748991193 scopus 로고    scopus 로고
    • Cost curves: An improved method for visualizing classifier performance
    • DOI 10.1007/s10994-006-8199-5
    • C. Drummond and R. C. Holte. Cost curves: An improved method for visualizing classifier performance. Machine Learning, 65(1):95-130, 2006. (Pubitemid 44451195)
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 95-130
    • Drummond, C.1    Holte, R.C.2
  • 8
    • 0035017874 scopus 로고    scopus 로고
    • Incorporating varying test costs and fault severities into test case prioritization
    • 00:0329
    • S. Elbaum, A. Malishevsky, and G. Rothermel. Incorporating varying test costs and fault severities into test case prioritization. icse, 00:0329, 2001.
    • (2001) Icse
    • Elbaum, S.1    Malishevsky, A.2    Rothermel, G.3
  • 9
  • 10
    • 47349102648 scopus 로고    scopus 로고
    • Fault prediction using early lifecycle data
    • Software Reliability, 2007. ISSRE '07
    • Y. Jiang, B. Cukic, and T. Menzies. Fault prediction using early lifecycle data. pages 237-246. Software Reliability, 2007. ISSRE '07. The 18th IEEE International Symposium on, Nov. 2007.
    • (2007) The 18th IEEE International Symposium , pp. 237-246
    • Jiang, Y.1    Cukic, B.2    Menzies, T.3
  • 12
    • 0032156744 scopus 로고    scopus 로고
    • Classification of faultprone software modules: Prior probabilities,costs, and model evaluation
    • T. M. Khoshgoftaar and E. B. Allen. Classification of faultprone software modules: Prior probabilities,costs, and model evaluation. Empirical Softw. Engg., 3(3):275-298, 1998.
    • (1998) Empirical Softw. Engg. , vol.3 , Issue.3 , pp. 275-298
    • Khoshgoftaar, T.M.1    Allen, E.B.2
  • 14
    • 33845782503 scopus 로고    scopus 로고
    • Data mining static code attributes to learn defect predictors
    • DOI 10.1109/TSE.2007.256941
    • T. Menzies, J. Greenwald, and A. Frank. Data mining static code attributes to learn defect predictors. IEEE Transactions on Software Engineering, 33(1):2-13, January 2007. Available from http://menzies.us/pdf/ 06learnPredict.pdf. (Pubitemid 46002165)
    • (2007) IEEE Transactions on Software Engineering , vol.33 , Issue.1 , pp. 2-13
    • Menzies, T.1    Greenwald, J.2    Frank, A.3
  • 15
    • 33646161505 scopus 로고    scopus 로고
    • Predicting Fault-Prone Software Modules in Telephone Switches
    • N. Ohlsson and H. Alberg. Predicting fault-prone software modules in telephone switches. IEEE Transactions on Software Engineering, 22(12):886-894, 1996. (Pubitemid 126771695)
    • (1996) IEEE Transactions on Software Engineering , vol.22 , Issue.12 , pp. 886-894
    • Ohlsson, N.1    Alberg, H.2
  • 16
    • 22944473604 scopus 로고    scopus 로고
    • Predicting the location and number of faults in large software systems
    • DOI 10.1109/TSE.2005.49
    • T. J. Ostrand, E. J. Weyuker, and R. M. Bell. Predicting the location and number of faults in large software systems. IEEE Transactions on Software Engineering, 31(4):340-355, 2005. (Pubitemid 41046924)
    • (2005) IEEE Transactions on Software Engineering , vol.31 , Issue.4 , pp. 340-355
    • Ostrand, T.J.1    Weyuker, E.J.2    Bell, R.M.3
  • 18
    • 34548253429 scopus 로고    scopus 로고
    • Data mining static code attributes to learn defect predictors
    • Comments on
    • H. Zhang and Z. X. Comments on 'data mining static code attributes to learn defect predictors'. IEEE Transactions on Software Engineering, 33(9):635-637, Sept. 2007.
    • (2007) IEEE Transactions on Software Engineering , vol.33 , Issue.9 , pp. 635-637
    • Zhang, H.1    X., Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.