A study of the applicability of complexity measures
- 1 September 1988
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Software Engineering
- Vol. 14 (9) , 1366-1372
- https://doi.org/10.1109/32.6179
Abstract
A study of the predictive value of a variety of syntax-based problem complexity measures is reported. Experimentation with variants of chunk-oriented measures showed that one should judiciously select measurable software attributes as proper indicators of what one wishes to predict, rather than hoping for a single, all-purpose complexity measure. The authors have shown that it is possible for particular complexity measures or other factors to serve as good predictors of some properties of program but not for others. For example, a good predictor of construction time will not necessarily correlate well with the number of error occurrences. M.H. Halstead's (1977) efforts measure (E) was found to be a better predictor that the two nonchunk measures evaluated, namely, T.J. McCabe's (1976) V(G) and lines of code, but at least one chunk measure predicted better than E in every case.Keywords
This publication has 23 references indexed in Scilit:
- Program SlicingIEEE Transactions on Software Engineering, 1984
- Control flow and data structure documentationCommunications of the ACM, 1982
- A complexity measure based on nesting levelACM SIGPLAN Notices, 1981
- Modern Coding Practices and Programmer PerformanceComputer, 1979
- Computer programming and the human thought processSoftware: Practice and Experience, 1979
- Measuring computer program quality and comprehensionInternational Journal of Man-Machine Studies, 1977
- A method of programming measurement and estimationIBM Systems Journal, 1977
- Exploratory experiments in programmer behaviorInternational Journal of Parallel Programming, 1976
- Some psychological evidence on how people debug computer programsInternational Journal of Man-Machine Studies, 1975
- An Exploratory Study of Computer Program DebuggingHuman Factors: The Journal of the Human Factors and Ergonomics Society, 1974