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