DocumentCode :
1046304
Title :
Debugging effort estimation using software metrics
Author :
Gorla, Narasimhaiah ; Benander, Alan C. ; Benander, Barbara A.
Author_Institution :
Dept. of Comput. Sci., Cleveland State Univ., OH, USA
Volume :
16
Issue :
2
fYear :
1990
fDate :
2/1/1990 12:00:00 AM
Firstpage :
223
Lastpage :
231
Abstract :
Measurements of 23 style characteristics, and the program metrics LOC, V(g), VARS, and PARS were collected from student Cobol programs by a program analyzer. These measurements, together with debugging time (syntax and logic) data, were analyzed using several statistical procedures of SAS (statistical analysis system), including linear, quadratic, and multiple regressions. Some of the characteristics shown to correlate significantly with debug time are GOTO usage, structuring of the IF-ELSE construct, level 88 item usage, paragraph invocation pattern, and data name length. Among the observed characteristic measures which are associated with lowest debug times are: 17% blank lines in the data division, 12% blank lines in the procedure division, and 13-character-long data items. A debugging effort estimator, DEST, was developed to estimate debug times
Keywords :
program debugging; program testing; statistical analysis; Cobol programs; DEST; GOTO usage; IF-ELSE construct; LOC; PARS; SAS; V(g); VARS; data name length; debug times; debugging effort estimation; level 88 item usage; linear regressions; multiple regressions; paragraph invocation pattern; program analyzer; quadratic regressions; software metrics; statistical analysis system; statistical procedures; style characteristics; Computational Intelligence Society; Debugging; Lab-on-a-chip; Logic; Programming profession; Reactive power; Regression analysis; Software metrics; Statistical analysis; Synthetic aperture sonar;
fLanguage :
English
Journal_Title :
Software Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-5589
Type :
jour
DOI :
10.1109/32.44385
Filename :
44385
Link To Document :
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