Software engineering metrics and models
Software engineering metrics and models
A Procedure for Analyzing Unbalanced Datasets
IEEE Transactions on Software Engineering
Using Prior-Phase Effort Records for Re-estimation During Software Projects
METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
ISESE '04 Proceedings of the 2004 International Symposium on Empirical Software Engineering
An Empirical Analysis of Software Productivity over Time
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
Optimal Project Feature Weights in Analogy-Based Cost Estimation: Improvement and Limitations
IEEE Transactions on Software Engineering
Cross-company and single-company effort models using the ISBSG database: a further replicated study
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Cross versus Within-Company Cost Estimation Studies: A Systematic Review
IEEE Transactions on Software Engineering
ESEM '07 Proceedings of the First International Symposium on Empirical Software Engineering and Measurement
Building Software Cost Estimation Models using Homogenous Data
ESEM '07 Proceedings of the First International Symposium on Empirical Software Engineering and Measurement
Replicating studies on cross- vs single-company effort models using the ISBSG Database
Empirical Software Engineering
Cross-company vs. single-company web effort models using the Tukutuku database: An extended study
Journal of Systems and Software
Using genetic programming to improve software effort estimation based on general data sets
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
EASE'08 Proceedings of the 12th international conference on Evaluation and Assessment in Software Engineering
Applying moving windows to software effort estimation
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
Can cross-company data improve performance in software effort estimation?
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
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Numerous studies have used historical datasets to build and validate models for estimating software development effort. Very few used a chronological split (where projects' end dates are used so that training sets only contain projects that were completed before the start date of each project in the validation set), and only one compared chronological split to random split. Therefore the aim of this study is to investigate further and compare the use of chronological and random splitting. We do so in the context of comparing cross-company and singlecompany models for effort estimation. We used 450 single-company projects and 741 cross-company projects from the ISBSG Release 10 repository, and estimates were obtained using manual stepwise regression. We found that with these data the use of chronological splitting, and different splitting dates, did not affect prediction accuracy. We were not able to obtain a converging set of findings when comparing cross- to single-company predictions given that different accuracy measures presented contradictory results.