Software project development cost estimation
Journal of Systems and Software
Statistical analysis with missing data
Statistical analysis with missing data
Software engineering metrics and models
Software engineering metrics and models
An Evaluation of Expert Systems for Software Engineering Management
IEEE Transactions on Software Engineering
Robust regression for developing software estimation models
Journal of Systems and Software
Rule-based approach to computing module cohesion
ICSE '93 Proceedings of the 15th international conference on Software Engineering
Explaining the cost of European space and military projects
Proceedings of the 21st international conference on Software engineering
Software Cost Estimation with Incomplete Data
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Software Development Cost Estimation Using Function Points
IEEE Transactions on Software Engineering
Assessing the Benefits of Imputing ERP Projects with Missing Data
METRICS '01 Proceedings of the 7th International Symposium on Software Metrics
Using Public Domain Metrics To Estimate Software Development Effort
METRICS '01 Proceedings of the 7th International Symposium on Software Metrics
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Optimizing and Simplifying Software Metric Models Constructed Using Maximum Likelihood Methods
COMPSAC '05 Proceedings of the 29th Annual International Computer Software and Applications Conference - Volume 01
An empirical analysis of software effort estimation with outlier elimination
Proceedings of the 4th international workshop on Predictor models in software engineering
An empirical evaluation of outlier deletion methods for analogy-based cost estimation
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Automated trendline generation for accurate software effort estimation
Proceedings of the 3rd annual conference on Systems, programming, and applications: software for humanity
International Journal of Intelligent Information Technologies
On the value of outlier elimination on software effort estimation research
Empirical Software Engineering
Information and Software Technology
Hi-index | 0.00 |
Software metric models are models relating various software metrics of software projects. Such models' purpose is to predict some of these metrics for certain future projects given the other metrics for those projects. The construction of software metric models derives such relationships and is usually based on data samples of concerned software metrics for past software projects. Often, in such a data sample, there are inevitably a few very extreme projects which have relationships among their metrics deviating substantially from those among the metrics for the remaining "mainstream" bulk of projects in the data sample. Such "outlier" projects exert considerable undue influence on the derivation of the said relationships during model construction in that the relationships so derived cannot candidly reflect the true "mainstream" relationships. The direct consequence is degraded prediction accuracy of the constructed models for future projects. To overcome this problem, we proposed a methodology to identify and thus eliminate such outliers prior to model construction. Our methodology makes use of the least of median squares (LMS) regression to uncover such outliers and is applicable irrespective of any subsequent model construction approaches. We also did a case study to apply our methodology, and the results prove our methodology being able to improve the prediction accuracy of most models experimented with in the study. Thus, our methodology is recommended for any further software metric model construction. This paper documents such a methodology and the successful case study.