Software errors and complexity: an empirical investigation0
Communications of the ACM
Monitoring Software Development Through Dynamic Variables
IEEE Transactions on Software Engineering - Special issue on COMPSAC 1982 and 1983
A formal model of diagnostic inference. I. Problem formulation and decomposition
Information Sciences: an International Journal - Special issue on expert systems
A comparative analysis of methods for expert systems
International Journal of Man-Machine Studies
Proceedings from the first international workshop on Expert database systems
IEEE Transactions on Systems, Man and Cybernetics - Special issue on artificial intelligence
Analyzing medium-scale software development
ICSE '78 Proceedings of the 3rd international conference on Software engineering
Recent advances in software measurement (abstract and references for talk)
ICSE '90 Proceedings of the 12th international conference on Software engineering
Function Points Analysis: An Empirical Study of Its Measurement Processes
IEEE Transactions on Software Engineering
AI Tools for Software Development Effort Estimation
SEEP '96 Proceedings of the 1996 International Conference on Software Engineering: Education and Practice (SE:EP '96)
On the Sufficiency of Limited Testing for Knowledge Based Systems
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Applying statistical methodology to optimize and simplify software metric models with missing data
Proceedings of the 2006 ACM symposium on Applied computing
Software project management with GAs
Information Sciences: an International Journal
Outlier elimination in construction of software metric models
Proceedings of the 2007 ACM symposium on Applied computing
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The development of four separate, prototype expert systems to aid in software engineering management is described. Given the values for certain metrics, these systems provide interpretations which explain any abnormal patterns of these values during the development of a software project. The four expert systems which solve the same problem, were built using two different approaches to knowledge acquisition, a bottom-up approach and a top-down approach and two different expert system methods, rule-based deduction and frame-based abduction. In a comparison to see which methods might better suit the needs of this field, it was found that the bottom-up approach led to better results that did the top-down approach, and the rule-based deduction systems using simple rules provided more complete and correct solutions than did the frame-based abduction systems.