Measuring the Psychological Complexity of Software Maintenance Tasks with the Halstead and McCabe Metrics

Three software complexity measures (Halstead's E, McCabe's u(G), and the length as measured by number of statements) were compared to programmer performance on two software maintenance tasks. In an experiment on understanding, length and u(G) correlated with the percent of statements corre...

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Bibliographic Details
Published in:IEEE transactions on software engineering Vol. SE-5; no. 2; pp. 96 - 104
Main Authors: Curtis, B., Sheppard, S.B., Milliman, P., Borst, M.A., Love, T.
Format: Journal Article
Language:English
Published: New York IEEE 01.03.1979
IEEE Computer Society
Subjects:
Codes
Commenting
Companies
complexity metrics
Computer programming
Computer science
Correlation analysis
Documentation
Experiments
FORTRAN
Halstead's E
Human factors
human factors in software engineering
Length measurement
McCabe's u(G)
Measurement
mnemonic variable names
modem programming practices modifica-tions
Programmers
Programming profession
Psychological aspects
Psychology
Resource management
Software
Software engineering
Software maintenance
Software measurement
Software performance
software science
structured programming
Variables
ISSN:0098-5589, 1939-3520
Online Access:Get full text
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Summary:Three software complexity measures (Halstead's E, McCabe's u(G), and the length as measured by number of statements) were compared to programmer performance on two software maintenance tasks. In an experiment on understanding, length and u(G) correlated with the percent of statements correctly recalled. In an experiment on modification, most significant correlations were obtained with metrics computed on modified rather than unmodified code. All three metrics correlated with both the accuracy of the modification and the time to completion. Relationships in both experiments occurred primarily in unstructured rather than structured code, and in code with no comments. The metrics were also most predictive of performance for less experienced programmers. Thus, these metrics appear to assess psychological complexity primarily where programming practices do not provide assistance in understanding the code.
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ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.1979.234165