Applied multivariate statistical analysis
Applied multivariate statistical analysis
A mathematical perspective for software measures research
Software Engineering Journal
Methodology for Validating Software Metrics
IEEE Transactions on Software Engineering
An Entropy-Based Measure of Software Complexity
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
An analysis of SEI software process assessment results: 1987–1991
ICSE '93 Proceedings of the 15th international conference on Software Engineering
Software Metrics: A Rigorous Approach
Software Metrics: A Rigorous Approach
Evaluating Design Metrics on Large-Scale Software
IEEE Software
Report on the IEEE Standard for a Software Quality Memcs Methodology
ICSM '93 Proceedings of the Conference on Software Maintenance
Software Metrics Knowledge and Databases for Project Management
IEEE Transactions on Knowledge and Data Engineering
An Enhanced Neural Network Technique for Software Risk Analysis
IEEE Transactions on Software Engineering
Complexity and Performance in Parallel Programming Languages
HIPS '97 Proceedings of the 1997 Workshop on High-Level Programming Models and Supportive Environments (HIPS '97)
Detection of software modules with high debug code churn in a very large legacy system
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Modeling Design/Coding Factors That Drive Maintainability of Software Systems
Software Quality Control
Assessing maintainability change over multiple software releases
Journal of Software Maintenance and Evolution: Research and Practice
A priori implementation effort estimation for hardware design based on independent path analysis
EURASIP Journal on Embedded Systems - Operating System Support for Embedded Real-Time Applications
Modifiability measurement from a task complexity perspective: A feasibility study
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
Hi-index | 4.10 |
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.