Debugging effort estimation using software metrics

• Published in: IEEE transactions on software engineering Vol. 16; no. 2; pp. 223 - 231
• Main Authors: Gorla, N., Benander, A.C., Benander, B.A.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.1990; IEEE Computer Society
• Subjects: Characteristics; Computational Intelligence Society; Computer programming; Debugging; Estimating techniques; Experiments; Lab-on-a-chip; Linear algebra; Logic; Names; Programming profession; Reactive power; Regression analysis; Software; Software engineering; Software metrics; Statistical analysis; Students; Syntax; Synthetic aperture sonar
• ISSN: 0098-5589; 1939-3520
• DOI: 10.1109/32.44385

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.< >