Modeling the relationship between source code complexity and maintenance difficulty

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Abstract
Canonical correlation analysis can be a useful exploratory tool for software engineers who want to understand relationships that are not directly observable and who are interested in understanding influences affecting past development efforts. These influences could also affect current development efforts. In this paper, we restrict our findings to one particular development effort. We do not imply that either the weights or the loadings of the relations generalize to all software development efforts. Such generalization is untenable, since the model omitted many important influences on maintenance difficulty. Much work remains to specify subsets of indicators and development efforts for which the technique becomes useful as a predictive tool. Canonical correlation analysis is explained as a restricted form of soft modeling. We chose this approach not only because the terminology and graphical devices of soft modeling allow straightforward high-level explanations, but also because we are interested in the general method. The general method allows models involving many latent variables having interdependencies. It is intended for modeling complex interdisciplinary systems having many variables and little established theory. Further, it incorporates parameter estimation techniques relying on no distributional assumptions. Future research will focus on developing general soft models of the software development process for both exploratory analysis and prediction of future performance.

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