Empirical analysis of the relationship between CC and SLOC in a large corpus of Java methods and C functions

Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic complexity (CC) is an often used source code quality metric, next to source lines of code (SLOC). However, the use of the CC metric is challenged by...

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Vydáno v:	Journal of software : evolution and process Ročník 28; číslo 7; s. 589 - 618
Hlavní autoři:	Landman, Davy, Serebrenik, Alexander, Bouwers, Eric, Vinju, Jurgen J.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Chichester Blackwell Publishing Ltd 01.07.2016 Wiley Subscription Services, Inc
Témata:	empirical validation McCabe cyclomatic complexity metrics software maintenance
ISSN:	2047-7473, 2047-7481
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Abstract	Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic complexity (CC) is an often used source code quality metric, next to source lines of code (SLOC). However, the use of the CC metric is challenged by the repeated claim that CC is redundant with respect to SLOC because of strong linear correlation. We conducted an extensive literature study of the CC/SLOC correlation results. Next, we tested correlation on large Java (17.6 M methods) and C (6.3 M functions) corpora. Our results show that linear correlation between SLOC and CC is only moderate as a result of increasingly high variance. We further observe that aggregating CC and SLOC as well as performing a power transform improves the correlation. Our conclusion is that the observed linear correlation between CC and SLOC of Java methods or C functions is not strong enough to conclude that CC is redundant with SLOC. This conclusion contradicts earlier claims from literature but concurs with the widely accepted practice of measuring of CC next to SLOC. Copyright © 2015 John Wiley & Sons, Ltd. We analyzed the relationship between cyclomatic complexity (CC) and lines of code (SLOC) for two large corpora of Java and C software. Contradicting earlier claims from literature, we observed that the linear correlation between CC and SLOC is not strong enough to conclude that CC is redundant to SLOC. This is caused by increasingly high variance and concurs with the widely accepted practice of measuring of CC next to SLOC.
AbstractList	Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic complexity (CC) is an often used source code quality metric, next to source lines of code (SLOC). However, the use of the CC metric is challenged by the repeated claim that CC is redundant with respect to SLOC because of strong linear correlation. We conducted an extensive literature study of the CC/SLOC correlation results. Next, we tested correlation on large Java (17.6 M methods) and C (6.3 M functions) corpora. Our results show that linear correlation between SLOC and CC is only moderate as a result of increasingly high variance. We further observe that aggregating CC and SLOC as well as performing a power transform improves the correlation. Our conclusion is that the observed linear correlation between CC and SLOC of Java methods or C functions is not strong enough to conclude that CC is redundant with SLOC. This conclusion contradicts earlier claims from literature but concurs with the widely accepted practice of measuring of CC next to SLOC. Copyright © 2015 John Wiley & Sons, Ltd. We analyzed the relationship between cyclomatic complexity (CC) and lines of code (SLOC) for two large corpora of Java and C software. Contradicting earlier claims from literature, we observed that the linear correlation between CC and SLOC is not strong enough to conclude that CC is redundant to SLOC. This is caused by increasingly high variance and concurs with the widely accepted practice of measuring of CC next to SLOC. Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic complexity (CC) is an often used source code quality metric, next to source lines of code (SLOC). However, the use of the CC metric is challenged by the repeated claim that CC is redundant with respect to SLOC because of strong linear correlation. We conducted an extensive literature study of the CC/SLOC correlation results. Next, we tested correlation on large Java (17.6M methods) and C (6.3M functions) corpora. Our results show that linear correlation between SLOC and CC is only moderate as a result of increasingly high variance. We further observe that aggregating CC and SLOC as well as performing a power transform improves the correlation. Our conclusion is that the observed linear correlation between CC and SLOC of Java methods or C functions is not strong enough to conclude that CC is redundant with SLOC. This conclusion contradicts earlier claims from literature but concurs with the widely accepted practice of measuring of CC next to SLOC. Copyright © 2015 John Wiley & Sons, Ltd. Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic complexity (CC) is an often used source code quality metric, next to source lines of code (SLOC). However, the use of the CC metric is challenged by the repeated claim that CC is redundant with respect to SLOC because of strong linear correlation. We conducted an extensive literature study of the CC/SLOC correlation results. Next, we tested correlation on large Java (17.6 M methods) and C (6.3 M functions) corpora. Our results show that linear correlation between SLOC and CC is only moderate as a result of increasingly high variance. We further observe that aggregating CC and SLOC as well as performing a power transform improves the correlation. Our conclusion is that the observed linear correlation between CC and SLOC of Java methods or C functions is not strong enough to conclude that CC is redundant with SLOC. This conclusion contradicts earlier claims from literature but concurs with the widely accepted practice of measuring of CC next to SLOC. Copyright © 2015 John Wiley & Sons, Ltd.
Author	Bouwers, Eric Serebrenik, Alexander Landman, Davy Vinju, Jurgen J.
Author_xml	– sequence: 1 givenname: Davy surname: Landman fullname: Landman, Davy email: Correspondence to: Davy Landman, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands., davy.landman@cwi.nl organization: Centrum Wiskunde & Informatica, Amsterdam, The Netherlands – sequence: 2 givenname: Alexander surname: Serebrenik fullname: Serebrenik, Alexander organization: Eindhoven University of Technology, Eindhoven, The Netherlands – sequence: 3 givenname: Eric surname: Bouwers fullname: Bouwers, Eric organization: Software Improvement Group, Amsterdam, The Netherlands – sequence: 4 givenname: Jurgen J. surname: Vinju fullname: Vinju, Jurgen J. organization: Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
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Cites_doi	10.1002/9780470606834.ch6 10.1109/SCAM.2009.28 10.1098/rspl.1895.0041 10.1016/0164-1212(93)90065-6 10.1109/TSE.1979.226497 10.1214/ss/1009213004 10.1002/(SICI)1096-908X(199707/08)9:4<235::AID-SMR153>3.0.CO;2-3 10.1109/32.879815 10.1016/j.jss.2013.04.076 10.1111/1467-9884.00122 10.1016/S0164-1212(98)10042-0 10.1145/954627.954633 10.1145/162754.162867 10.2307/2289444 10.1109/32.295895 10.1109/ISSRE.2007.12 10.1145/1390630.1390648 10.1109/SCAM.2012.17 10.4236/jsea.2009.23020 10.1007/s10618-008-0118-x 10.1002/sim.5486 10.2307/1412159 10.1109/ICSM.1989.65191 10.1145/2491411.2491418 10.1109/32.922717 10.1109/2.402076 10.1109/METRIC.1994.344224 10.1049/sej.1987.0015 10.1109/ICSM.2011.6080798 10.1049/sej.1988.0003 10.1109/ICSM.2007.4362632 10.1145/69605.2085 10.1007/s10664-008-9060-1 10.1007/s11390-010-9398-x 10.1016/S0167-6296(98)00025-3 10.1109/32.24715 10.1007/s11334-006-0007-7 10.1007/s10664-014-9308-x 10.1109/MARK.1979.8817108 10.1007/BF02249047 10.1109/MSR.2007.31 10.1109/32.859533 10.1145/1985374.1985381 10.1007/s10664-013-9275-7 10.1109/ASE.2011.6100074 10.2307/1911963 10.1109/ICPC.2008.13 10.1109/TSE.1987.233475 10.2307/3565750 10.1109/QUATIC.2007.8 10.1037/0033-2909.95.3.576 10.1109/TSE.1976.233837 10.1109/52.50772 10.1145/2601248.2601268 10.1002/smr.1558 10.1109/SWAN.2015.7070485 10.1109/ENC.2005.47 10.1109/ICSME.2014.44 10.14569/IJACSA.2014.050721 10.1145/336512.336586 10.1109/32.935855 10.1145/1852786.1852801 10.1145/2635868.2635922 10.1007/s11219-011-9144-9 10.1109/32.44385 10.1109/ICSE.2015.24 10.1109/32.106988
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References	Pearson K. Note on regression and inheritance in the case of two parents. Proceedings of the Royal Society of London 1895; 58:240-242. Shull FJ, Carver JC, Vegas S, Juristo N. The role of replications in empirical software engineering. Empirical Software Engineering 2008; 13(2):211-218. DOI:10.1007/s10664-008-9060-1. Sheskin DJ. Handbook of Parametric and Nonparametric Statistical Procedures, 4 edn. Chapman & Hall/CRC, 2007. da Mota Silveira Neto PA, Engström E, de Carmo Machado I, de Almeida ES. On the reliability of mapping studies in software engineering. Journal of Systems and Software 2013; 86(10):2594-2610. DOI:10.1016/j.jss.2013.04.076. Kemerer CF, Slaughter SA. Determinants of software maintenance profiles: an empirical investigation. Journal of Software Maintenance Jul 1997; 9(4):235-251. Yu L, Mishra A. An empirical study of Lehman's law on software quality evolution. International Journal of Software & Informatics 2013; 7(3):469-481. Henry S, Selig C. Predicting source-code complexity at the design stage. Software, IEEE March 1990; 7(2):36-44. DOI:10.1109/52.50772. Myers GJ. An extension to the cyclomatic measure of program complexity. SIGPLAN Notices October 1977; 12(10):61-64. DOI:10.1145/954627.954633. Joanes DN, Gill CA. Comparing measures of sample skewness and kurtosis. Journal of the Royal Statistical Society: Series D (The Statistician) 1998; 47(1):183-189. DOI:10.1111/1467-9884.00122. El Emam K, Benlarbi S, Goel N, Rai SN. The confounding effect of class size on the validity of object-oriented metrics. IEEE Transactions on Software Engineering 2001; 27(7):630-650. Mordal K, Anquetil N, Laval J, Serebrenik A, Vasilescu B, Ducasse S. Software quality metrics aggregation in industry. Journal of Software: Evolution and Process 2013; 25(10):1117-1135. DOI:10.1002/smr.1558. Tashtoush Y, Al-Maolegi M, Arkok B. The correlation among software complexity metrics with case study. International Journal of Advanced Computer Research 2014; 4(2):414-419. Moores TT. Applying complexity measures to rule-based prolog programs. Journal of Systems and Software 1998; 44(1):45-52. DOI:10.1016/S0164-1212(98)10042-0. von Mayrhauser A, Vans AM. Program comprehension during software maintenance and evolution. IEEE Computer 1995; 28(8):44-55. McCabe TJ. A complexity measure. IEEE Transactions Software Engineering 1976; 2(4):308-320. Woodward MR, Hennell MA, Hedley D. A measure of control flow complexity in program text. IEEE Transactions on Software Engineering Jan 1979; 5(1):45-50. DOI:10.1109/TSE.1979.226497. Ma YT, He KQ, Li B, Liu J, Zhou XY. A hybrid set of complexity metrics for large-scale object-oriented software systems. Journal of Computer Science and Technology 2010; 25(6):1184-1201. DOI:10.1007/s11390-010-9398-x. Conte SD, Dunsmore HE, Shen VY. Software Engineering Metrics and Models. Benjamin-Cummings Publishing Co., Inc.: Redwood City, CA, USA, 1986. Schneidewind N. Software reliability engineering process. Innovations in Systems and Software Engineering 2006; 2(3-4):179-190. DOI:10.1007/s11334-006-0007-7. Chidamber SR, Kemerer CF. A metrics suite for object oriented design. IEEE Transactions on Software Engineering Jun 1994; 20(6):476-493. DOI:10.1109/32.295895. Kitchenham B, Pickard L. Towards a constructive quality model. part 2: Statistical techniques for modelling software quality in the esprit request project. Software Engineering Journal July 1987; 2(4):114-126. DOI:10.1049/sej.1987.0015. Linstead E, Bajracharya SK, Ngo TC, Rigor P, Lopes CV, Baldi P. Sourcerer: mining and searching internet-scale software repositories. Data Mining and Knowledge Discovery 2009; 18(2):300-336. DOI:10.1007/s10618-008-0118-x. Basili VR, Perricone BT. Software errors and complexity: an empirical investigation. Communications of the ACM 1984; 27(1):42-52. Troster J, Tian J. Measurement and defect modeling for a legacy software system. Annals of Software Engineering 1995; 1:95-118. DOI:10.1007/BF02249047. Spearman C. The proof and measurement of association between two things. The American Journal of Psychology 1904; 15(1):72-101. Malhotra R, Singh Y. On the applicability of machine learning techniques for object oriented software fault prediction. Software Engineering: An International Journal 2011; 1:24-37. Carr DB, Littlefield RJ, Nicholson WL, Littlefield JS. Scatterplot matrix techniques for large N. Journal of the American Statistical Association 1987; 82(398):424-436. Coleman R, Johnson MA. A study of Scala repositories on GitHub. International Journal of Advanced Computer Science and Applications 2014; 5(7):141-148. Khomh F, Adams B, Dhaliwal T, Zou Y. Understanding the impact of rapid releases on software quality. Empirical Software Engineering 2014; 20(2):336-373. DOI:10.1007/s10664-014-9308-x. Breusch T, Pagan A. A simple test for heteroscedasticity and random coefficient variation. Econometrica Sep 1979; 47(5):1287-1294. Lind RK, Vairavan K. An experimental investigation of software metrics and their relationship to software development effort. IEEE Transactions on Software Engineering May 1989; 15(5):649-653. DOI:10.1109/32.24715. Baggen R, Correia JP, Schill K, Visser J. Standardized code quality benchmarking for improving software maintainability. Software Quality Journal 2012; 20(2):287-307. DOI:10.1007/s11219-011-9144-9. Manning WG. The logged dependent variable, heteroscedasticity, and the retransformation problem. Journal of Health Economics 1998; 17(3):283-295. DOI:10.1016/S0167-6296(98)00025-3. Gill GK, Kemerer CF. Cyclomatic complexity density and software maintenance productivity. IEEE Transactions on Software Engineering Dec 1991; 17(12):1284-1288. DOI:10.1109/32.106988. Jay G, Hale JE, Smith RK, Hale DP, Kraft NA, Ward C. Cyclomatic complexity and lines of code: empirical evidence of a stable linear relationship. Journal of Software Engineering and Applications 2009; 2(3):137-143. Paige M. A metric for software test planning. Conference Proceedings of COMPSAC 1980; 80:499-504. Shepperd M. A critique of cyclomatic complexity as a software metric. Software Engineering Journal Mar 1988; 3(2):30-36. DOI:10.1049/sej.1988.0003. Kvålseth TO. Cautionary note about R2. The American Statistician 1985; 39(4):279-285. Gorla N, Benander A, Benander BA. Debugging effort estimation using software metrics. IEEE Transactions on Software Engineering 1990; 16(2):223-231. Li H, Cheung W. An empirical study of software metrics. IEEE Transactions on Software Engineering June 1987; SE-13(6):697-708. DOI:10.1109/TSE.1987.233475. Saltelli A, Tarantola S, Campolongo F. Sensitivity analysis as an ingredient of modeling. Statistical Science 2000; 15(4):377-395. Fenton N, Ohlsson N. Quantitative analysis of faults and failures in a complex software system. Software Engineering, IEEE Transactions on Aug 2000; 26(8):797-814. DOI:10.1109/32.879815. Succi G, Benedicenti L, Vernazza T. Analysis of the effects of software reuse on customer satisfaction in an RPG environment. IEEE Transactions on Software Engineering May 2001; 27(5):473-479. DOI:10.1109/32.922717. Feng C, Wang H, Lu N, Tu XM. Log transformation: application and interpretation in biomedical research. Statistics in Medicine 2013; 32(2):230-239. DOI:10.1002/sim.5486. Edgell SE, Noon SM. Effect of violation of normality on the t test of the correlation coefficient. Psychological Bulletin 1984; 95(3):576-583. Loehle C. Proper statistical treatment of species-area data. Oikos 1990; 57(1):143-145. Jbara A, Matan A, Feitelson DG. High-MCC functions in the Linux kernel. Empirical Software Engineering 2014; 19(5):1261-1298. DOI:10.1007/s10664-013-9275-7. Munson JC, Kohshgoftaar TM. Measurement of data structure complexity. Journal of Systems and Software 1993; 20(3):217-225. DOI:10.1016/0164-1212(93)90065-6. Graves T, Karr A, Marron J, Siy H. Predicting fault incidence using software change history. Software Engineering, IEEE Transactions on Jul 2000; 26(7):653-661. DOI:10.1109/32.859533. 1987; 2 2013; 25 1991; 17 1990; 57 1990; 16 1984; 27 1993; 20 2013; 7 1997; 9 1979 1998; 44 1998; 47 1994; 20 2014; 20 1984; 95 1998; 17 2014; 5 2014; 4 2010; 25 1995; 28 1987; 82 2000 2000; 15 1986 1979; 5 1983 2014; 19 1980; 80 1981 1987; SE‐13 2012; 20 2009; 18 1989 2011; 1 2012 2000; 26 2011 2010 2013; 86 1976; 2 2009 2008 2007 1995 2008; 13 1994 2005 1993 2001; 27 2006; 2 1995; 1 1985; 39 1988; 3 1979; 47 1904; 15 2013; 32 1895; 58 2015 2014 1977; 12 2013 1989; 15 2009; 2 1990; 7 e_1_2_7_5_1 e_1_2_7_3_1 e_1_2_7_9_1 e_1_2_7_7_1 e_1_2_7_19_1 e_1_2_7_60_1 e_1_2_7_83_1 e_1_2_7_17_1 Malhotra R (e_1_2_7_25_1) 2011; 1 e_1_2_7_81_1 e_1_2_7_41_1 e_1_2_7_64_1 e_1_2_7_13_1 e_1_2_7_43_1 e_1_2_7_66_1 e_1_2_7_85_1 e_1_2_7_11_1 e_1_2_7_45_1 e_1_2_7_68_1 e_1_2_7_47_1 e_1_2_7_49_1 e_1_2_7_28_1 Tashtoush Y (e_1_2_7_74_1) 2014; 4 Herraiz I (e_1_2_7_34_1) 2010 e_1_2_7_73_1 e_1_2_7_50_1 e_1_2_7_71_1 e_1_2_7_31_1 e_1_2_7_52_1 e_1_2_7_77_1 e_1_2_7_23_1 e_1_2_7_33_1 e_1_2_7_54_1 e_1_2_7_75_1 e_1_2_7_21_1 e_1_2_7_56_1 e_1_2_7_37_1 e_1_2_7_58_1 e_1_2_7_79_1 e_1_2_7_39_1 Paige M (e_1_2_7_62_1) 1980; 80 e_1_2_7_6_1 e_1_2_7_4_1 e_1_2_7_80_1 e_1_2_7_8_1 Chambers JM (e_1_2_7_53_1) 1983 e_1_2_7_18_1 e_1_2_7_84_1 e_1_2_7_16_1 e_1_2_7_40_1 e_1_2_7_61_1 e_1_2_7_82_1 e_1_2_7_2_1 e_1_2_7_14_1 e_1_2_7_42_1 e_1_2_7_63_1 e_1_2_7_12_1 e_1_2_7_44_1 e_1_2_7_65_1 e_1_2_7_86_1 e_1_2_7_10_1 e_1_2_7_46_1 e_1_2_7_67_1 e_1_2_7_48_1 e_1_2_7_69_1 e_1_2_7_27_1 e_1_2_7_29_1 Sheskin DJ (e_1_2_7_35_1) 2007 Yu L (e_1_2_7_26_1) 2013; 7 Kvålseth TO (e_1_2_7_36_1) 1985; 39 e_1_2_7_72_1 e_1_2_7_51_1 e_1_2_7_70_1 e_1_2_7_30_1 e_1_2_7_76_1 Conte SD (e_1_2_7_15_1) 1986 e_1_2_7_24_1 e_1_2_7_32_1 e_1_2_7_55_1 e_1_2_7_22_1 e_1_2_7_57_1 e_1_2_7_20_1 e_1_2_7_59_1 e_1_2_7_78_1 e_1_2_7_38_1
References_xml	– reference: Lind RK, Vairavan K. An experimental investigation of software metrics and their relationship to software development effort. IEEE Transactions on Software Engineering May 1989; 15(5):649-653. DOI:10.1109/32.24715. – reference: Fenton N, Ohlsson N. Quantitative analysis of faults and failures in a complex software system. Software Engineering, IEEE Transactions on Aug 2000; 26(8):797-814. DOI:10.1109/32.879815. – reference: Kitchenham B, Pickard L. Towards a constructive quality model. part 2: Statistical techniques for modelling software quality in the esprit request project. Software Engineering Journal July 1987; 2(4):114-126. DOI:10.1049/sej.1987.0015. – reference: Coleman R, Johnson MA. A study of Scala repositories on GitHub. International Journal of Advanced Computer Science and Applications 2014; 5(7):141-148. – reference: Pearson K. Note on regression and inheritance in the case of two parents. Proceedings of the Royal Society of London 1895; 58:240-242. – reference: Paige M. A metric for software test planning. Conference Proceedings of COMPSAC 1980; 80:499-504. – reference: Joanes DN, Gill CA. Comparing measures of sample skewness and kurtosis. Journal of the Royal Statistical Society: Series D (The Statistician) 1998; 47(1):183-189. DOI:10.1111/1467-9884.00122. – reference: Gill GK, Kemerer CF. Cyclomatic complexity density and software maintenance productivity. IEEE Transactions on Software Engineering Dec 1991; 17(12):1284-1288. DOI:10.1109/32.106988. – reference: Linstead E, Bajracharya SK, Ngo TC, Rigor P, Lopes CV, Baldi P. Sourcerer: mining and searching internet-scale software repositories. Data Mining and Knowledge Discovery 2009; 18(2):300-336. DOI:10.1007/s10618-008-0118-x. – reference: Mordal K, Anquetil N, Laval J, Serebrenik A, Vasilescu B, Ducasse S. Software quality metrics aggregation in industry. Journal of Software: Evolution and Process 2013; 25(10):1117-1135. DOI:10.1002/smr.1558. – reference: Graves T, Karr A, Marron J, Siy H. Predicting fault incidence using software change history. Software Engineering, IEEE Transactions on Jul 2000; 26(7):653-661. DOI:10.1109/32.859533. – reference: Carr DB, Littlefield RJ, Nicholson WL, Littlefield JS. Scatterplot matrix techniques for large N. Journal of the American Statistical Association 1987; 82(398):424-436. – reference: Jbara A, Matan A, Feitelson DG. High-MCC functions in the Linux kernel. Empirical Software Engineering 2014; 19(5):1261-1298. DOI:10.1007/s10664-013-9275-7. – reference: El Emam K, Benlarbi S, Goel N, Rai SN. The confounding effect of class size on the validity of object-oriented metrics. IEEE Transactions on Software Engineering 2001; 27(7):630-650. – reference: Khomh F, Adams B, Dhaliwal T, Zou Y. Understanding the impact of rapid releases on software quality. Empirical Software Engineering 2014; 20(2):336-373. DOI:10.1007/s10664-014-9308-x. – reference: Myers GJ. An extension to the cyclomatic measure of program complexity. SIGPLAN Notices October 1977; 12(10):61-64. DOI:10.1145/954627.954633. – reference: von Mayrhauser A, Vans AM. Program comprehension during software maintenance and evolution. IEEE Computer 1995; 28(8):44-55. – reference: Chidamber SR, Kemerer CF. A metrics suite for object oriented design. IEEE Transactions on Software Engineering Jun 1994; 20(6):476-493. DOI:10.1109/32.295895. – reference: Tashtoush Y, Al-Maolegi M, Arkok B. The correlation among software complexity metrics with case study. International Journal of Advanced Computer Research 2014; 4(2):414-419. – reference: Spearman C. The proof and measurement of association between two things. The American Journal of Psychology 1904; 15(1):72-101. – reference: Saltelli A, Tarantola S, Campolongo F. Sensitivity analysis as an ingredient of modeling. Statistical Science 2000; 15(4):377-395. – reference: Yu L, Mishra A. An empirical study of Lehman's law on software quality evolution. International Journal of Software & Informatics 2013; 7(3):469-481. – reference: Munson JC, Kohshgoftaar TM. Measurement of data structure complexity. Journal of Systems and Software 1993; 20(3):217-225. DOI:10.1016/0164-1212(93)90065-6. – reference: Shull FJ, Carver JC, Vegas S, Juristo N. The role of replications in empirical software engineering. Empirical Software Engineering 2008; 13(2):211-218. DOI:10.1007/s10664-008-9060-1. – reference: Loehle C. Proper statistical treatment of species-area data. Oikos 1990; 57(1):143-145. – reference: Shepperd M. A critique of cyclomatic complexity as a software metric. Software Engineering Journal Mar 1988; 3(2):30-36. DOI:10.1049/sej.1988.0003. – reference: Baggen R, Correia JP, Schill K, Visser J. Standardized code quality benchmarking for improving software maintainability. Software Quality Journal 2012; 20(2):287-307. DOI:10.1007/s11219-011-9144-9. – reference: Woodward MR, Hennell MA, Hedley D. A measure of control flow complexity in program text. IEEE Transactions on Software Engineering Jan 1979; 5(1):45-50. DOI:10.1109/TSE.1979.226497. – reference: McCabe TJ. A complexity measure. IEEE Transactions Software Engineering 1976; 2(4):308-320. – reference: Kemerer CF, Slaughter SA. Determinants of software maintenance profiles: an empirical investigation. Journal of Software Maintenance Jul 1997; 9(4):235-251. – reference: Conte SD, Dunsmore HE, Shen VY. Software Engineering Metrics and Models. Benjamin-Cummings Publishing Co., Inc.: Redwood City, CA, USA, 1986. – reference: Jay G, Hale JE, Smith RK, Hale DP, Kraft NA, Ward C. Cyclomatic complexity and lines of code: empirical evidence of a stable linear relationship. Journal of Software Engineering and Applications 2009; 2(3):137-143. – reference: Li H, Cheung W. An empirical study of software metrics. IEEE Transactions on Software Engineering June 1987; SE-13(6):697-708. DOI:10.1109/TSE.1987.233475. – reference: Sheskin DJ. Handbook of Parametric and Nonparametric Statistical Procedures, 4 edn. Chapman & Hall/CRC, 2007. – reference: da Mota Silveira Neto PA, Engström E, de Carmo Machado I, de Almeida ES. On the reliability of mapping studies in software engineering. Journal of Systems and Software 2013; 86(10):2594-2610. DOI:10.1016/j.jss.2013.04.076. – reference: Henry S, Selig C. Predicting source-code complexity at the design stage. Software, IEEE March 1990; 7(2):36-44. DOI:10.1109/52.50772. – reference: Schneidewind N. Software reliability engineering process. Innovations in Systems and Software Engineering 2006; 2(3-4):179-190. DOI:10.1007/s11334-006-0007-7. – reference: Feng C, Wang H, Lu N, Tu XM. Log transformation: application and interpretation in biomedical research. Statistics in Medicine 2013; 32(2):230-239. DOI:10.1002/sim.5486. – reference: Troster J, Tian J. Measurement and defect modeling for a legacy software system. Annals of Software Engineering 1995; 1:95-118. DOI:10.1007/BF02249047. – reference: Basili VR, Perricone BT. Software errors and complexity: an empirical investigation. Communications of the ACM 1984; 27(1):42-52. – reference: Kvålseth TO. Cautionary note about R2. The American Statistician 1985; 39(4):279-285. – reference: Succi G, Benedicenti L, Vernazza T. Analysis of the effects of software reuse on customer satisfaction in an RPG environment. IEEE Transactions on Software Engineering May 2001; 27(5):473-479. DOI:10.1109/32.922717. – reference: Breusch T, Pagan A. A simple test for heteroscedasticity and random coefficient variation. Econometrica Sep 1979; 47(5):1287-1294. – reference: Gorla N, Benander A, Benander BA. Debugging effort estimation using software metrics. IEEE Transactions on Software Engineering 1990; 16(2):223-231. – reference: Moores TT. Applying complexity measures to rule-based prolog programs. Journal of Systems and Software 1998; 44(1):45-52. DOI:10.1016/S0164-1212(98)10042-0. – reference: Manning WG. The logged dependent variable, heteroscedasticity, and the retransformation problem. Journal of Health Economics 1998; 17(3):283-295. DOI:10.1016/S0167-6296(98)00025-3. – reference: Edgell SE, Noon SM. Effect of violation of normality on the t test of the correlation coefficient. Psychological Bulletin 1984; 95(3):576-583. – reference: Ma YT, He KQ, Li B, Liu J, Zhou XY. A hybrid set of complexity metrics for large-scale object-oriented software systems. Journal of Computer Science and Technology 2010; 25(6):1184-1201. DOI:10.1007/s11390-010-9398-x. – reference: Malhotra R, Singh Y. On the applicability of machine learning techniques for object oriented software fault prediction. Software Engineering: An International Journal 2011; 1:24-37. – year: 2011 – year: 2009 – year: 1981 – volume: 20 start-page: 336 issue: 2 year: 2014 end-page: 373 article-title: Understanding the impact of rapid releases on software quality publication-title: Empirical Software Engineering – volume: 1 start-page: 24 year: 2011 end-page: 37 article-title: On the applicability of machine learning techniques for object oriented software fault prediction publication-title: Software Engineering: An International Journal – volume: 4 start-page: 414 issue: 2 year: 2014 end-page: 419 article-title: The correlation among software complexity metrics with case study publication-title: International Journal of Advanced Computer Research – year: 2005 – year: 1989 – volume: 16 start-page: 223 issue: 2 year: 1990 end-page: 231 article-title: Debugging effort estimation using software metrics publication-title: IEEE Transactions on Software Engineering – volume: 17 start-page: 283 issue: 3 year: 1998 end-page: 295 article-title: The logged dependent variable, heteroscedasticity, and the retransformation problem publication-title: Journal of Health Economics – volume: 1 start-page: 95 year: 1995 end-page: 118 article-title: Measurement and defect modeling for a legacy software system publication-title: Annals of Software Engineering – year: 1979 – year: 2014 – year: 1994 – volume: 25 start-page: 1184 issue: 6 year: 2010 end-page: 1201 article-title: A hybrid set of complexity metrics for large‐scale object‐oriented software systems publication-title: Journal of Computer Science and Technology – volume: 18 start-page: 300 issue: 2 year: 2009 end-page: 336 article-title: Sourcerer: mining and searching internet‐scale software repositories publication-title: Data Mining and Knowledge Discovery – year: 1986 – volume: 5 start-page: 45 issue: 1 year: 1979 end-page: 50 article-title: A measure of control flow complexity in program text publication-title: IEEE Transactions on Software Engineering Jan – volume: 2 start-page: 114 issue: 4 year: 1987 end-page: 126 article-title: Towards a constructive quality model. part 2: Statistical techniques for modelling software quality in the esprit request project publication-title: Software Engineering Journal July – volume: 26 start-page: 653 issue: 7 year: 2000 end-page: 661 article-title: Predicting fault incidence using software change history publication-title: Software Engineering, IEEE Transactions on Jul – volume: 32 start-page: 230 issue: 2 year: 2013 end-page: 239 article-title: Log transformation: application and interpretation in biomedical research publication-title: Statistics in Medicine – year: 2008 – volume: 20 start-page: 476 issue: 6 year: 1994 end-page: 493 article-title: A metrics suite for object oriented design publication-title: IEEE Transactions on Software Engineering Jun – volume: 95 start-page: 576 issue: 3 year: 1984 end-page: 583 article-title: Effect of violation of normality on the test of the correlation coefficient publication-title: Psychological Bulletin – volume: 9 start-page: 235 issue: 4 year: 1997 end-page: 251 article-title: Determinants of software maintenance profiles: an empirical investigation publication-title: Journal of Software Maintenance – volume: 13 start-page: 211 issue: 2 year: 2008 end-page: 218 article-title: The role of replications in empirical software engineering publication-title: Empirical Software Engineering – volume: 7 start-page: 469 issue: 3 year: 2013 end-page: 481 article-title: An empirical study of Lehman's law on software quality evolution publication-title: International Journal of Software & Informatics – volume: 27 start-page: 630 issue: 7 year: 2001 end-page: 650 article-title: The confounding effect of class size on the validity of object‐oriented metrics publication-title: IEEE Transactions on Software Engineering – volume: 2 start-page: 308 issue: 4 year: 1976 end-page: 320 article-title: A complexity measure publication-title: IEEE Transactions Software Engineering – year: 1993 – volume: 44 start-page: 45 issue: 1 year: 1998 end-page: 52 article-title: Applying complexity measures to rule‐based prolog programs publication-title: Journal of Systems and Software – volume: 17 start-page: 1284 issue: 12 year: 1991 end-page: 1288 article-title: Cyclomatic complexity density and software maintenance productivity publication-title: IEEE Transactions on Software Engineering Dec – year: 2015 – volume: 12 start-page: 61 issue: 10 year: 1977 end-page: 64 article-title: An extension to the cyclomatic measure of program complexity publication-title: SIGPLAN Notices October – start-page: 126 year: 2010 end-page: 141 – volume: 15 start-page: 72 issue: 1 year: 1904 end-page: 101 article-title: The proof and measurement of association between two things publication-title: The American Journal of Psychology – volume: 20 start-page: 217 issue: 3 year: 1993 end-page: 225 article-title: Measurement of data structure complexity publication-title: Journal of Systems and Software – year: 1983 – volume: 82 start-page: 424 issue: 398 year: 1987 end-page: 436 article-title: Scatterplot matrix techniques for large N publication-title: Journal of the American Statistical Association – volume: 39 start-page: 279 issue: 4 year: 1985 end-page: 285 article-title: Cautionary note about publication-title: The American Statistician – year: 2007 – volume: 27 start-page: 473 issue: 5 year: 2001 end-page: 479 article-title: Analysis of the effects of software reuse on customer satisfaction in an RPG environment publication-title: IEEE Transactions on Software Engineering May – volume: 80 start-page: 499 year: 1980 end-page: 504 article-title: A metric for software test planning publication-title: Conference Proceedings of COMPSAC – year: 2000 – volume: 15 start-page: 377 issue: 4 year: 2000 end-page: 395 article-title: Sensitivity analysis as an ingredient of modeling publication-title: Statistical Science – volume: 19 start-page: 1261 issue: 5 year: 2014 end-page: 1298 article-title: High‐MCC functions in the Linux kernel publication-title: Empirical Software Engineering – year: 2010 – year: 2012 – volume: 86 start-page: 2594 issue: 10 year: 2013 end-page: 2610 article-title: On the reliability of mapping studies in software engineering publication-title: Journal of Systems and Software – volume: 25 start-page: 1117 issue: 10 year: 2013 end-page: 1135 article-title: Software quality metrics aggregation in industry publication-title: Journal of Software: Evolution and Process – volume: 15 start-page: 649 issue: 5 year: 1989 end-page: 653 article-title: An experimental investigation of software metrics and their relationship to software development effort publication-title: IEEE Transactions on Software Engineering May – volume: 47 start-page: 1287 issue: 5 year: 1979 end-page: 1294 article-title: A simple test for heteroscedasticity and random coefficient variation publication-title: Econometrica – volume: 7 start-page: 36 issue: 2 year: 1990 end-page: 44 article-title: Predicting source‐code complexity at the design stage publication-title: Software, IEEE March – volume: 26 start-page: 797 issue: 8 year: 2000 end-page: 814 article-title: Quantitative analysis of faults and failures in a complex software system publication-title: Software Engineering, IEEE Transactions on Aug – year: 1995 – volume: 2 start-page: 137 issue: 3 year: 2009 end-page: 143 article-title: Cyclomatic complexity and lines of code: empirical evidence of a stable linear relationship publication-title: Journal of Software Engineering and Applications – volume: SE‐13 start-page: 697 issue: 6 year: 1987 end-page: 708 article-title: An empirical study of software metrics publication-title: IEEE Transactions on Software Engineering June – volume: 20 start-page: 287 issue: 2 year: 2012 end-page: 307 article-title: Standardized code quality benchmarking for improving software maintainability publication-title: Software Quality Journal – volume: 3 start-page: 30 issue: 2 year: 1988 end-page: 36 article-title: A critique of cyclomatic complexity as a software metric publication-title: Software Engineering Journal Mar – start-page: 131 year: 2010 end-page: 143 – volume: 58 start-page: 240 year: 1895 end-page: 242 article-title: Note on regression and inheritance in the case of two parents publication-title: Proceedings of the Royal Society of London – volume: 47 start-page: 183 issue: 1 year: 1998 end-page: 189 article-title: Comparing measures of sample skewness and kurtosis publication-title: Journal of the Royal Statistical Society: Series D (The Statistician) – volume: 57 start-page: 143 issue: 1 year: 1990 end-page: 145 article-title: Proper statistical treatment of species‐area data publication-title: Oikos – volume: 2 start-page: 179 issue: 3‐4 year: 2006 end-page: 190 article-title: Software reliability engineering process publication-title: Innovations in Systems and Software Engineering – volume: 28 start-page: 44 issue: 8 year: 1995 end-page: 55 article-title: Program comprehension during software maintenance and evolution publication-title: IEEE Computer – volume: 5 start-page: 141 issue: 7 year: 2014 end-page: 148 article-title: A study of Scala repositories on GitHub publication-title: International Journal of Advanced Computer Science and Applications – volume: 27 start-page: 42 issue: 1 year: 1984 end-page: 52 article-title: Software errors and complexity: an empirical investigation publication-title: Communications of the ACM – year: 2013 – ident: e_1_2_7_31_1 doi: 10.1002/9780470606834.ch6 – ident: e_1_2_7_45_1 doi: 10.1109/SCAM.2009.28 – ident: e_1_2_7_79_1 – ident: e_1_2_7_47_1 doi: 10.1098/rspl.1895.0041 – ident: e_1_2_7_52_1 doi: 10.1016/0164-1212(93)90065-6 – ident: e_1_2_7_56_1 doi: 10.1109/TSE.1979.226497 – ident: e_1_2_7_82_1 doi: 10.1214/ss/1009213004 – ident: e_1_2_7_61_1 doi: 10.1002/(SICI)1096-908X(199707/08)9:4<235::AID-SMR153>3.0.CO;2-3 – ident: e_1_2_7_10_1 doi: 10.1109/32.879815 – ident: e_1_2_7_20_1 doi: 10.1016/j.jss.2013.04.076 – ident: e_1_2_7_50_1 doi: 10.1111/1467-9884.00122 – ident: e_1_2_7_80_1 doi: 10.1016/S0164-1212(98)10042-0 – ident: e_1_2_7_18_1 doi: 10.1145/954627.954633 – ident: e_1_2_7_60_1 doi: 10.1145/162754.162867 – ident: e_1_2_7_46_1 doi: 10.2307/2289444 – ident: e_1_2_7_22_1 doi: 10.1109/32.295895 – ident: e_1_2_7_40_1 doi: 10.1109/ISSRE.2007.12 – ident: e_1_2_7_17_1 doi: 10.1145/1390630.1390648 – ident: e_1_2_7_2_1 doi: 10.1109/SCAM.2012.17 – ident: e_1_2_7_32_1 doi: 10.4236/jsea.2009.23020 – ident: e_1_2_7_12_1 doi: 10.1007/s10618-008-0118-x – ident: e_1_2_7_76_1 doi: 10.1002/sim.5486 – ident: e_1_2_7_49_1 doi: 10.2307/1412159 – ident: e_1_2_7_41_1 – ident: e_1_2_7_21_1 – ident: e_1_2_7_58_1 doi: 10.1109/ICSM.1989.65191 – ident: e_1_2_7_81_1 doi: 10.1145/2491411.2491418 – volume-title: Graphical Methods for Data Analysis year: 1983 ident: e_1_2_7_53_1 – ident: e_1_2_7_68_1 doi: 10.1109/32.922717 – ident: e_1_2_7_3_1 doi: 10.1109/2.402076 – ident: e_1_2_7_14_1 doi: 10.1109/METRIC.1994.344224 – ident: e_1_2_7_43_1 – ident: e_1_2_7_65_1 doi: 10.1049/sej.1987.0015 – volume: 39 start-page: 279 issue: 4 year: 1985 ident: e_1_2_7_36_1 article-title: Cautionary note about R2 publication-title: The American Statistician – ident: e_1_2_7_29_1 doi: 10.1109/ICSM.2011.6080798 – ident: e_1_2_7_13_1 doi: 10.1049/sej.1988.0003 – ident: e_1_2_7_24_1 doi: 10.1109/ICSM.2007.4362632 – ident: e_1_2_7_8_1 doi: 10.1145/69605.2085 – ident: e_1_2_7_83_1 doi: 10.1007/s10664-008-9060-1 – ident: e_1_2_7_73_1 doi: 10.1007/s11390-010-9398-x – ident: e_1_2_7_75_1 doi: 10.1016/S0167-6296(98)00025-3 – ident: e_1_2_7_57_1 doi: 10.1109/32.24715 – volume: 4 start-page: 414 issue: 2 year: 2014 ident: e_1_2_7_74_1 article-title: The correlation among software complexity metrics with case study publication-title: International Journal of Advanced Computer Research – volume-title: Handbook of Parametric and Nonparametric Statistical Procedures year: 2007 ident: e_1_2_7_35_1 – ident: e_1_2_7_71_1 doi: 10.1007/s11334-006-0007-7 – ident: e_1_2_7_84_1 doi: 10.1007/s10664-014-9308-x – ident: e_1_2_7_6_1 doi: 10.1109/MARK.1979.8817108 – ident: e_1_2_7_38_1 doi: 10.1007/BF02249047 – ident: e_1_2_7_33_1 doi: 10.1109/MSR.2007.31 – ident: e_1_2_7_67_1 doi: 10.1109/32.859533 – start-page: 126 volume-title: Making Software What Really Works, and Why We Believe It year: 2010 ident: e_1_2_7_34_1 – ident: e_1_2_7_28_1 doi: 10.1145/1985374.1985381 – ident: e_1_2_7_9_1 doi: 10.1007/s10664-013-9275-7 – ident: e_1_2_7_27_1 doi: 10.1109/ASE.2011.6100074 – ident: e_1_2_7_54_1 doi: 10.2307/1911963 – ident: e_1_2_7_23_1 doi: 10.1109/ICPC.2008.13 – ident: e_1_2_7_64_1 doi: 10.1109/TSE.1987.233475 – volume: 1 start-page: 24 year: 2011 ident: e_1_2_7_25_1 article-title: On the applicability of machine learning techniques for object oriented software fault prediction publication-title: Software Engineering: An International Journal – ident: e_1_2_7_7_1 – volume: 80 start-page: 499 year: 1980 ident: e_1_2_7_62_1 article-title: A metric for software test planning publication-title: Conference Proceedings of COMPSAC – ident: e_1_2_7_63_1 – ident: e_1_2_7_37_1 doi: 10.2307/3565750 – ident: e_1_2_7_5_1 doi: 10.1109/QUATIC.2007.8 – ident: e_1_2_7_55_1 – volume: 7 start-page: 469 issue: 3 year: 2013 ident: e_1_2_7_26_1 article-title: An empirical study of Lehman's law on software quality evolution publication-title: International Journal of Software & Informatics – ident: e_1_2_7_48_1 doi: 10.1037/0033-2909.95.3.576 – ident: e_1_2_7_16_1 doi: 10.1109/TSE.1976.233837 – ident: e_1_2_7_39_1 doi: 10.1109/52.50772 – ident: e_1_2_7_19_1 doi: 10.1145/2601248.2601268 – ident: e_1_2_7_30_1 doi: 10.1002/smr.1558 – ident: e_1_2_7_44_1 doi: 10.1109/SWAN.2015.7070485 – ident: e_1_2_7_70_1 doi: 10.1109/ENC.2005.47 – ident: e_1_2_7_11_1 doi: 10.1109/ICSME.2014.44 – volume-title: Software Engineering Metrics and Models year: 1986 ident: e_1_2_7_15_1 – ident: e_1_2_7_72_1 – ident: e_1_2_7_78_1 doi: 10.14569/IJACSA.2014.050721 – ident: e_1_2_7_77_1 doi: 10.1145/336512.336586 – ident: e_1_2_7_69_1 doi: 10.1109/32.935855 – ident: e_1_2_7_51_1 doi: 10.1145/1852786.1852801 – ident: e_1_2_7_85_1 doi: 10.1145/2635868.2635922 – ident: e_1_2_7_4_1 doi: 10.1007/s11219-011-9144-9 – ident: e_1_2_7_42_1 – ident: e_1_2_7_59_1 doi: 10.1109/32.44385 – ident: e_1_2_7_86_1 doi: 10.1109/ICSE.2015.24 – ident: e_1_2_7_66_1 doi: 10.1109/32.106988
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Snippet	Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic...
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SubjectTerms	empirical validation McCabe cyclomatic complexity metrics software maintenance
Title	Empirical analysis of the relationship between CC and SLOC in a large corpus of Java methods and C functions
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