Empirical Performance Analysis of Computer-Supported Code-Reviews
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
Interval quality: relating customer-perceived quality to process quality
Proceedings of the 30th international conference on Software engineering
An analysis of developer metrics for fault prediction
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
A study of several metrics for programming effort
Journal of Systems and Software
| Hi-index | 0.00 |
The propensity to make programming errors and the rates of error detection and correction are dependent on program complexity. Knowledge of these relationships can be used to avoid errorprone structures in software design and to devise a testing strategy which is based on anticipated difficulty of error detection and correction. An experiment in software error data collection and analysis was conducted in order to study these relationships under conditions where the error data could be carefully defined and collected. Several complexity measures which can be defined in terms of the directed graph representation of a program, such as cyclomatic number, were analyzed with respect to the following error characteristics: errors found, time between error detections, and error correction time. Signifiant relationships were found between complexity measures and error charateristics. The meaning of directed grph structural properties in terms of the complexity of the programming and testing tasks was examined.