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On the Correlation between Testing Effort and Software Complexity Metrics

Fulltext:


Authors:

Adnan Muslija , Eduard Paul Enoiu

Note:

preprint version (2018-12-01)

Publication Type:

Manuscript


Abstract

Software complexity metrics, such as code size and cyclomatic complexity, have been used in the software engineering community for predicting quality metrics such as maintainability, bug proneness and robustness. However, not many studies have addressed the relationship between complexity metrics and software testing and there is little experimental evidence to support the use of these code metrics in the estimation of test effort. We have investigated and evaluated the relationship between test effort (i.e, number of test cases and test execution time) and software complexity metrics for industrial control software used in an embedded system. We show how to measure different software complexity metrics such as number of elements, cyclomatic complexity, and information flow for a popular programming language named FBD used in the safety critical domain. In addition, we use test data and test suites created by experienced test engineers working at Bombardier Transportation Sweden AB to evaluate the correlation between several complexity measures and the testing effort. We found that there is a moderate correlation between software complexity metrics and test effort. In addition, the results show that the software size (i.e., number of elements in the FBD program) provides the highest correlation level with the number of test cases created and test execution time. Our results suggest that software size and structure metrics, while useful for identifying parts of the system that are more complicated, should not be solely used for identifying parts of the system for which test engineers might need to create more test cases. A potential explanation of this result concerns the nature of testing, since other attributes such as the level of thorough testing required and the size of the specifications can influence the creation of test cases. In addition, we used a linear regression model to estimate the test effort using the software complexity measurement results.

Bibtex

@unpublished{Muslija5420,
author = {Adnan Muslija and Eduard Paul Enoiu},
title = {On the Correlation between Testing Effort and Software Complexity Metrics},
note = {preprint version (2018-12-01)},
month = {December},
year = {2018},
url = {http://www.es.mdh.se/publications/5420-}
}