Cyclomatic complexity: Difference between revisions

Revision as of 17:38, 11 May 2020

Revision as of 06:22, 6 June 2020

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url=http://www.eecs.qmul.ac.uk/~norman/papers/defects_prediction_preprint105579.pdf|

title=A Critique of Software Defect Prediction Models|

year=1999|volume=25|issue=3|pages=675–689|issn=|doi=10.1109/32.815326|citeseerx=10.1.1.548.2998 }}</ref> Some studies<ref name="schroeder99">{{cite articlejournal| title=A Practical guide to object-oriented metrics|author=Schroeder, Mark|s2cid=14945518|year=1999|volume=1|issue=6|pages=30-3630–36|journal=IT Professional | url=https://pdfs.semanticscholar.org/e3d6/6c47ee0ddb37868c51ca30840084263ee1f1.pdf|doi=10.1109/6294.806902}}</ref> find a positive correlation between cyclomatic complexity and defects: functions and methods that have the highest complexity tend to also contain the most defects. However, the correlation between cyclomatic complexity and program size (typically measured in [[lines of code]]) has been demonstrated many times. [[Les Hatton]] has claimed<ref name="taic">

{{cite web |url=http://www.leshatton.org/TAIC2008-29-08-2008.html |title=The role of empiricism in improving the reliability of future software |author=Les Hatton |year=2008 |at=version 1.1}}</ref> that complexity has the same predictive ability as lines of code.

Studies that controlled for program size (i.e., comparing modules that have different complexities but similar size) are generally less conclusive, with many finding no significant correlation, while others do find correlation. Some researchers who have studied the area question the validity of the methods used by the studies finding no correlation.<ref name="kan">