Research Question Unacceptable Files:FS GQM 1 2 GQM s r 2.1 GQM Goal-Question-Metric GQM [2] GQM 3 Qustions GQM 3 GQM 2.2 UFs AFs Acceptable Fi
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1 1,a) 1 1,b) 1,c) Unacceptable Files:FS (Acceptable Files:Fs) UFs UFs GQM GQM C [1] Goal-Question-Metric GQM [2] GQM 1 2 a) @toki.waseda.jp b) washizaki@waseda.jp c) fukazawa@waseda.jp 1 s GQM GQM 2 1
2 Research Question Unacceptable Files:FS GQM 1 2 GQM s r 2.1 GQM Goal-Question-Metric GQM [2] GQM 3 Qustions GQM 3 GQM 2.2 UFs AFs Acceptable Files Accuracy Precision Recall F1 F1-measure Cohen s kappa 1 4 true positive TP false positive FP true negative TN negative FN F1 FN FN Landis [3] (kappa < 0.00) ( ) ( ) ( ) ( ) ( ). (ACC - RA)/(1 - RA) RA 1 RA = NP A T OT AL NP P T OT AL + NNA T OT AL NNP T OT AL (1) AnswerPredicted Answer/Predicted Positive(Prd) Negative(Prd) Sum Positive(Ans) TP FN NPA Negative(Ans) FP TN NNA Sum NPP NNP TOTAL 2
3 3. GQM UFs GQM Interpretation [1] Interpretation 4 Interpretation 4 GQM+Interpretation 3.1 UFs AND OR AND OR TRUE AFs FALSE UFs AND OR -1 bool i = (M i T i ) (2) AND : (bool and1 bool and2...) (3) OR : (bool or1 bool or2...) (4) 2 M i T i M i TRUE AND 3 bool and FALSE AND FALSE OR 4 bool or TRUE OR TRUE AFs UFs AND-FALSE-Files F F s AND OR-FALSE-Files F F s OR F F s AND F F s OR UFs AND F F s OR AFs OR TRUE AFs 3.2 GQM Question Question 3
4 QuestionX M1 M2 M3 AND (M1 T and1 )(M2 T and2 ) OR (M1 T or1 ) (M3 T or3 ) AND OR UFs 3.3 UFs or AFs UFs UFs or AFs 2.2 M M1-1. M 1,AF 2,AF20,UF25,UF (M T and1 ) T 3 10 UFs F F s AND F F s OR AFs AND F F s AND AND OR F F s OR OR OR (M1 T or1 )... < OR AND GQM UFs GQM GQM Adqua GQM Adqua[4] Adqua 100 GQM Adqua QAC/QAC++ csv *1 3 MFl004 MFl732 Adqua cppfile metrics value1.csv MFl004K MFl007K func metrics value1.csv MFn066 MFn CE Q *1 C++ 4
5 2 UFs Q Description Related Metrics Q01 Q02 Q03 Q04 Private-Public MFl097, MFl732 MFl004, MFl477 MFl497 MFl002K MFl019, Q05 MFl004K, MFl005K, Q06 MFl006K, MFl007K MFl232 Q07 MFl062 Q08 Q09 Q10 3 MFl061, MFl316, MFl317 MFl590, MFl599 MFl026, MFl589 MFl152, MFl591, MFl588, UFs Metrics Description MFl004 MFl019 MFl026 MFl061 MFl062 MFl097 MFl152 MFl232 MFl316 MFl317 MFl477 MFl497 MFl588 MFl589 MFl590 MFl591 MFl599 MFl732 MFl002K MFl004K MFl005K MFl006K MFl007K public CE 4 UFs ( : MFl004 >M004, MFl005K >05K) CE Q AND OR CE01 Q01 M097<Ta1 01 M732<Ta2 01 CE02 Q02 M004<Ta1 02 M019<Ta2 02 M477<Ta3 02 CE03 Q03 M497<Ta1 03 CE04 Q04 002K<Ta1 04 CE05 Q05 04K<Ta K<Ta K<Ta K<Ta4 05 CE06 Q06 M232<Ta1 06 CE07 Q07 M062<Ta1 07 M004<To1 02 M019<To2 02 M477<To K<To K<To K<To K<To4 05 CE08 Q08 M152<Ta1 08 M61<Ta2 08 M316<To1 08 M317<To2 08 CE09 Q09 M599<Ta1 09 M590<Ta2 09 M591<Ta3 09 CE10 Q10 M026<Ta1 10 M588<Ta2 10 M589<Ta3 10 M599<To1 09 M590<To2 09 M591<To2 09 M026<To1 10 M588<To2 10 M589<To C C++ C++ sub C++ - FiN subsys FiN SLOC LLOC Sum Med Sum Med Sum Med sub sub sub Question
6 75 UFs UF 2 sub01 sub02 sub03 55 Q sub02 sub03 Q02 Q Q02 Q AFs (UFs) Q sub01 sub02 sub03 AF UFs AFs UFs AFs UFs Q Q Q Q Q Q Q Q Q Q Research Question UFs 1 CE01-10 CE sub01 55 CE CE02 CE05 UFs sub02 sub03 sub01 sub02 sub sub CE02 CE05 CE09 6 Q01 Q03 Q04 Q06 Q08 55 UFs CE Q08 Q10 sub01 sub01 sub01 Q08 Q sub01 UFs Q Pre Rec F1 Kap Q Q Q NaN NaN 0.00 Q04 NaN 0.00 NaN 0.00 Q Q06 NaN 0.00 NaN 0.00 Q Q08 NaN 0.00 NaN 0.00 Q Q CE02 CE05 CE09 CE02:(MF l004 25)(MF l019 12)(MF l477 37) CE05:((MF l004k 2.33)(MF l005k 4)(MF l006k 3.40)(MF l007k 11))((MF l004k < 1.00) (MF l005k < 3) (MF l006k < 2.17) (MF l007k < 7)) CE09:(MF l599 20)(MF l590 == 0)(MF l591 == 0) CE02 CE09 OR CE include using
7 sub02 sub sub02 sub03 CE05 sub02 sub CE CE sub01 sub02 sub03 UFs subsys&q Acc Pre Rec F1 Kap sub02:q sub02:q sub03:q sub03:q Alves [5] Alves %quantile UFs Alves GQM [6] EPM[7] Interpretation Jacek [8] UFs Rahman [9] UFs 6. Unacceptable Files UFs UFs [1] Zhang, F. and et al.: How Does Context Affect the Distribution of Software Maintainability Metrics?, Proc. of the 2013 IEEE Int. Conf. on Soft. Maintenance, ICSM 13, Washington, DC, USA, IEEE Computer Society, pp (online), DOI: /ICSM (2013). [2] Basili, V. R. and et al.: A Methodology for Collecting Valid Software Engineering Data, IEEE Trans. Softw. Eng., Vol. 10, No. 6, pp (online), DOI: /TSE (1984). [3] Landis, R. and et al.: The measurement of observer agreement for categorical data, Biometrics, Vol. 33, No. 1, pp (1977). [4] Hironori, W. and et al.: A Framework for Measuring and Evaluating Program Source Code Quality, Proc. of the 8th Int. Conf. on PROFES, PROFES 07, Berlin, Heidelberg, Springer-Verlag, pp (2007). [5] Alves, T. and et al.: Deriving Metric Thresholds from Benchmark Data, Proc. of the 2010 IEEE Int. Conf. on Soft. Maintenance, ICSM 10, Washington, DC, USA, IEEE Computer Society, pp (2010). [6] MONDEN, A. and et al.: Customizing GQM Models for Software Project Monitoring, IEICE Trans. on Informa- 7
8 tion and Systems, Vol. 95, No. 9, pp (2012). [7] Masao, O. and et al.: Empirical project monitor: A tool for mining multiple project data, Project Data, Proc. Int. Wksp. on Mining Soft. Repositories, pp (2004). [8] Ratzinger, J. and et al.: Mining Software Evolution to Predict Refactoring, Proc. of the First Int. Symp. on Empirical Soft. Eng. and Measurement, ESEM 07, Washington, DC, USA, IEEE Computer Society, pp (2007). [9] Rahman, F. and et al.: Recalling the Imprecision of Cross-project Defect Prediction, Proc. of the ACM SIG- SOFT 20th Int. Symp. on the Foundations of Soft. Eng., FSE 12, New York, NY, USA, ACM, pp. 61:1 61:11 (2012). 8
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