Data sets and data quality in software engineering
Proceedings of the 4th international workshop on Predictor models in software engineering
A comparative evaluation on the accuracies of software effort estimates from clustered data
Information and Software Technology
Software development productivity of Japanese enterprise applications
Information Technology and Management
Empirical Software Engineering
ACSC '09 Proceedings of the Thirty-Second Australasian Conference on Computer Science - Volume 91
Modeling the relationship between software effort and size using deming regression
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
State of the practice in software effort estimation: a survey and literature review
CEE-SET'08 Proceedings of the Third IFIP TC 2 Central and East European conference on Software engineering techniques
EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
EASE'08 Proceedings of the 12th international conference on Evaluation and Assessment in Software Engineering
Empirical analysis of the impact of requirements engineering on software quality
REFSQ'12 Proceedings of the 18th international conference on Requirements Engineering: foundation for software quality
Alternative methods using similarities in software effort estimation
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
PROFES'12 Proceedings of the 13th international conference on Product-Focused Software Process Improvement
Software Engineering Productivity: Concepts, Issues and Challenges
International Journal of Information Technology Project Management
On the value of outlier elimination on software effort estimation research
Empirical Software Engineering
Information and Software Technology
| Hi-index | 0.00 |
In 2001 the ISBSG database was used by Jeffery et al. (Using public domain metrics to estimate software development effort. Proceedings Metrics'01, London, pp 16---27, 2001; S1) to compare the effort prediction accuracy between cross- and single-company effort models. Given that more than 2,000 projects were later volunteered to this database, in 2005 Mendes et al. (A replicated comparison of cross-company and within-company effort estimation models using the ISBSG Database, in Proceedings of Metrics'05, Como, 2005; S2) replicated S1 but obtained different results. The difference in results could have occurred due to legitimate differences in data set patterns; however, they could also have occurred due to differences in experimental procedure given that S2 was unable to employ exactly the same experimental procedure used in S1 because S1's procedure was not fully documented. Recently, we applied S2's experimental procedure to the ISBSG database version used in S1 (release 6) to assess if differences in experimental procedure would have contributed towards different results (Lokan and Mendes, Cross-company and single-company effort models using the ISBSG Database: a further replicated study, Proceedings of the ISESE'06, pp 75---84, 2006; S3). Our results corroborated those from S1, suggesting that differences in the results obtained by S2 were likely caused by legitimate differences in data set patterns. We have since been able to reconstruct the experimental procedure of S1 and therefore in this paper we present both S3 and also another study (S4), which applied the experimental procedure of S1 to the data set used in S2. By applying the experimental procedure of S2 to the data set used in S1 (study S3), and the experimental procedure of S1 to the data set used in S2 (study S4), we investigate the effect of all the variations between S1 and S2. Our results for S4 support those of S3, suggesting that differences in data preparation and analysis procedures did not affect the outcome of the analysis. Thus, the different results of S1 and S2 are very likely due to fundamental differences in the data sets.