11.REFERENCES confounding effect of class size on the validity of [1]C.Andersson and P.Runeson.A Replicated object-oriented metrics.IEEE Transactions on Quantitative Analysis of Fault Distributions in Software Engineering,27(7):630-650,July 2001. Complex Software Systems.IEEE Transactions on [15 N.Fenton and N.Ohlsson.Quantitative analysis of Software Engineering,33(5):273-286,May 2007. faults and failures in a complex software system.IEEE [2]E.Arisholm,L.C.Briand,and E.B.Johannessen.A Transactions on Software Engineering,26(8):797-814, systematic and comprehensive investigation of methods Aug.2000. to build and evaluate fault prediction models.Journal [16]H.Gall.K.Hajek,and M.Jazayeri.Detection of of Systems and Software,83(1):2-17.Jan.2010. Logical Coupling Based on Product Release History.In [3]V.Basili,L.Briand,and W.Melo.A validation of Proceedings of the International Conference on object-oriented design metrics as quality indicators. Software Maintenance.ICSM '98.pages 190-, IEEE Transactions on Software Engineering, Washington.DC,USA,1998.IEEE Computer Society. 22(10):751-761.0ct.1996 [17]R.E.Grinter,J.D.Herbsleb,and D.E.Perry.The [4]Y.Benjamini and Y.Hochberg.Controlling the False Geography of Coordination:Dealing with Distance in Discovery Rate:A Practical and Powerful Approach to R&D Work.In Proceedings of the International ACM Multiple Testing.Journal of the Royal Statistical SIGGROUP Conference on Supporting Group Work, Society.Series B (Methodological),57(1):289-300,Jan GROUP'99,pages 306-315,New York,NY,USA, 1995. 1999.ACM. [5]A.Beszedes,L.Schrettner,B.Csaba,T.Gergely, 18 M.Harman,D.Binkley,K.Gallagher,N.Gold,and J.Jasz,and T.Gyimothy.Empirical investigation of J.Krinke.Dependence Clusters in Source Code.ACM SEA-based dependence cluster properties.In Trans.Program.Lang.Syst.,32(1):1:1-1:33.Nov.2009 Proceedings of the 2013 IEEE International Working [19]J.D.Herbsleb and A.Mockus.An empirical study of Conference on Source Code Analysis and Manipulation, speed and communication in globally distributed SCAM '12,pages 1-10,Sept.2013. software development.IEEE Transactions on Software [6]A.Beszedes,L.Schrettner,B.Csaba,T.Gergely Engineering,29(6):481-494,June 2003. J.Jasz,and T.Gyimothy.Empirical Investigation of 20 S.Islam,J.Krinke,D.Binkley,and M.Harman. SEA-based Dependence Cluster Properties.Sci Coherent clusters in source code.Journal of Systems Comput.Program.,105(C):3-25,July 2015. and Software,88:1-24,Feb.2014. [7]D.Binkley,A.Beszedes,S.Islam,J.Jasz,and [21]S.S.Islam,J.Krinke,D.Binkley,and M.Harman B.Vancsics.Uncovering dependence clusters and Coherent Dependence Clusters.In Proceedings of the linchpin functions.In Proceedings of the 2015 IEEE 9th ACM SIGPLAN-SIGSOFT Workshop on Program International Conference on Software Maintenance and Analysis for Software Tools and Engineering,PASTE Evolution,(ICSME'15,pages 141-150,Sept.2015. '10,pages 53-60,New York,NY,USA,2010.ACM. [8]D.Binkley and M.Harman.Locating dependence 22 J.M.Juran.Quality control handbook.In Quality clusters and dependence pollution.In Proceedings of control handbook.McGraw-Hill.1962. the 21st IEEE International Conference on Software [23]W.Ma,L.Chen,Y.Yang,Y.Zhou,and B.Xu. Maintenance,2005.ICSM'05,pages 177-186,Sept. Empirical analysis of network measures for effort-aware 2005. fault-proneness prediction.Information and Software [9]D.Binkley and M.Harman.Identifying Linchpin Technology,69:50-70,Jan.2016. Vertices'That Cause Large Dependence Clusters.In [24]T.Mende and R.Koschke.Effort-Aware Defect Proceedings of the 2009 Ninth IEEE International Prediction Models.In Proceedings of the 2010 14th Working Conference on Source Code Analysis and European Conference on Software Maintenance and Manipulation,SCAM'09,pages 89-98,Washington, Reengineering,CSMR'10,pages 107-116,Washington, DC.USA,2009.IEEE Computer Society. DC.USA,2010.IEEE Computer Society. [10]D.Binkley,M.Harman,Y.Hassoun,S.Islam,and 25 T.Menzies,J.Greenwald,and A.Frank.Data Mining Z.Li.Assessing the impact of global variables on Static Code Attributes to Learn Defect Predictors program dependence and dependence clusters.Journal IEEE Transactions on Software Engineering, of Systems and Software,83(1):96-107.Jan.2010 33(1):2-13.Jan.2007. [11]L.C.Briand,J.Wtist,J.W.Daly,and [26]T.Menzies,Z.Milton,B.Turhan,B.Cukic,Y.Jiang, D.Victor Porter.Exploring the relationships between and A.Bener.Defect prediction from static code design measures and software quality in object-oriented features:current results,limitations,new approaches. systems.Journal of Systems and Software, Automated Software Engineering,17(4):375-407,May 51(3):245-273.May2000. 2010. 12 K.P.Burnham and D.R.Anderson.Multimodel [27]A.Mockus and D.M.Weiss.Predicting risk of software Inference Understanding AIC and BIC in Model changes.Bell Labs Technical Journal,5(2):169-180, Selection.Sociological Methods Research. Apr.2000. 33(2):261-304,Nov.2004. [28]N.Nagappan and T.Ball.Use of Relative Code Churn 13 M.Cataldo,A.Mockus,J.Roberts,and J.Herbsleb. Measures to Predict System Defect Density.In Software Dependencies,Work Dependencies,and Their Proceedings of the 27th International Conference on Impact on Failures.IEEE Transactions on Software Software Engineering,ICSE '05,pages 284-292,New Engineering,35(6):864-878,Nov.2009. York,NY,USA,2005.ACM. [14]K.El Emam,S.Benlarbi,N.Goel,and S.Rai.The [29]N.Nagappan,B.Murphy,and V.Basili.The Influence 30611. REFERENCES [1] C. Andersson and P. Runeson. A Replicated Quantitative Analysis of Fault Distributions in Complex Software Systems. IEEE Transactions on Software Engineering, 33(5):273–286, May 2007. [2] E. Arisholm, L. C. Briand, and E. B. Johannessen. A systematic and comprehensive investigation of methods to build and evaluate fault prediction models. Journal of Systems and Software, 83(1):2–17, Jan. 2010. [3] V. Basili, L. Briand, and W. Melo. A validation of object-oriented design metrics as quality indicators. IEEE Transactions on Software Engineering, 22(10):751–761, Oct. 1996. [4] Y. Benjamini and Y. Hochberg. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1):289–300, Jan. 1995. [5] A. Besz´edes, L. Schrettner, B. Csaba, T. Gergely, ´ J. J´asz, and T. Gyim´othy. Empirical investigation of SEA-based dependence cluster properties. In Proceedings of the 2013 IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM ’12, pages 1–10, Sept. 2013. [6] A. Besz´edes, L. Schrettner, B. Csaba, T. Gergely, ´ J. J´asz, and T. Gyim´othy. Empirical Investigation of SEA-based Dependence Cluster Properties. Sci. Comput. Program., 105(C):3–25, July 2015. [7] D. Binkley, A. Besz´edes, S. Islam, J. J´asz, and ´ B. Vancsics. Uncovering dependence clusters and linchpin functions. In Proceedings of the 2015 IEEE International Conference on Software Maintenance and Evolution, (ICSME’ 15, pages 141–150, Sept. 2015. [8] D. Binkley and M. Harman. Locating dependence clusters and dependence pollution. In Proceedings of the 21st IEEE International Conference on Software Maintenance, 2005. ICSM’05, pages 177–186, Sept. 2005. [9] D. Binkley and M. Harman. Identifying ‘Linchpin Vertices’ That Cause Large Dependence Clusters. In Proceedings of the 2009 Ninth IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM ’09, pages 89–98, Washington, DC, USA, 2009. IEEE Computer Society. [10] D. Binkley, M. Harman, Y. Hassoun, S. Islam, and Z. Li. Assessing the impact of global variables on program dependence and dependence clusters. Journal of Systems and Software, 83(1):96–107, Jan. 2010. [11] L. C. Briand, J. Wust, J. W. Daly, and ¨ D. Victor Porter. Exploring the relationships between design measures and software quality in object-oriented systems. Journal of Systems and Software, 51(3):245–273, May 2000. [12] K. P. Burnham and D. R. Anderson. Multimodel Inference Understanding AIC and BIC in Model Selection. Sociological Methods & Research, 33(2):261–304, Nov. 2004. [13] M. Cataldo, A. Mockus, J. Roberts, and J. Herbsleb. Software Dependencies, Work Dependencies, and Their Impact on Failures. IEEE Transactions on Software Engineering, 35(6):864–878, Nov. 2009. [14] K. El Emam, S. Benlarbi, N. Goel, and S. Rai. The confounding effect of class size on the validity of object-oriented metrics. IEEE Transactions on Software Engineering, 27(7):630–650, July 2001. [15] N. Fenton and N. Ohlsson. Quantitative analysis of faults and failures in a complex software system. IEEE Transactions on Software Engineering, 26(8):797–814, Aug. 2000. [16] H. Gall, K. Hajek, and M. Jazayeri. Detection of Logical Coupling Based on Product Release History. In Proceedings of the International Conference on Software Maintenance, ICSM ’98, pages 190–, Washington, DC, USA, 1998. IEEE Computer Society. [17] R. E. Grinter, J. D. Herbsleb, and D. E. Perry. The Geography of Coordination: Dealing with Distance in R&D Work. In Proceedings of the International ACM SIGGROUP Conference on Supporting Group Work, GROUP ’99, pages 306–315, New York, NY, USA, 1999. ACM. [18] M. Harman, D. Binkley, K. Gallagher, N. Gold, and J. Krinke. Dependence Clusters in Source Code. ACM Trans. Program. Lang. Syst., 32(1):1:1–1:33, Nov. 2009. [19] J. D. Herbsleb and A. Mockus. An empirical study of speed and communication in globally distributed software development. IEEE Transactions on Software Engineering, 29(6):481–494, June 2003. [20] S. Islam, J. Krinke, D. Binkley, and M. Harman. Coherent clusters in source code. Journal of Systems and Software, 88:1–24, Feb. 2014. [21] S. S. Islam, J. Krinke, D. Binkley, and M. Harman. Coherent Dependence Clusters. In Proceedings of the 9th ACM SIGPLAN-SIGSOFT Workshop on Program Analysis for Software Tools and Engineering, PASTE ’10, pages 53–60, New York, NY, USA, 2010. ACM. [22] J. M. Juran. Quality control handbook. In Quality control handbook. McGraw-Hill, 1962. [23] W. Ma, L. Chen, Y. Yang, Y. Zhou, and B. Xu. Empirical analysis of network measures for effort-aware fault-proneness prediction. Information and Software Technology, 69:50–70, Jan. 2016. [24] T. Mende and R. Koschke. Effort-Aware Defect Prediction Models. In Proceedings of the 2010 14th European Conference on Software Maintenance and Reengineering, CSMR ’10, pages 107–116, Washington, DC, USA, 2010. IEEE Computer Society. [25] 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, Jan. 2007. [26] T. Menzies, Z. Milton, B. Turhan, B. Cukic, Y. Jiang, and A. Bener. Defect prediction from static code features: current results, limitations, new approaches. Automated Software Engineering, 17(4):375–407, May 2010. [27] A. Mockus and D. M. Weiss. Predicting risk of software changes. Bell Labs Technical Journal, 5(2):169–180, Apr. 2000. [28] N. Nagappan and T. Ball. Use of Relative Code Churn Measures to Predict System Defect Density. In Proceedings of the 27th International Conference on Software Engineering, ICSE ’05, pages 284–292, New York, NY, USA, 2005. ACM. [29] N. Nagappan, B. Murphy, and V. Basili. The Influence 306