Software engineering metrics and models
Software engineering metrics and models
Robust regression for developing software estimation models
Journal of Systems and Software
A replicated assessment and comparison of common software cost modeling techniques
Proceedings of the 22nd international conference on Software engineering
A Discipline for Software Engineering
A Discipline for Software Engineering
An empirical study of maintenance and development estimation accuracy
Journal of Systems and Software
ISESE '04 Proceedings of the 2004 International Symposium on Empirical Software Engineering
What Should You Optimize When Building an Estimation Model?
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
A Comparison of Software Project Overruns-Flexible versus Sequential Development Models
IEEE Transactions on Software Engineering
Analysis of attribute weighting heuristics for analogy-based software effort estimation method AQUA+
Empirical Software Engineering
Analogy-X: Providing Statistical Inference to Analogy-Based Software Cost Estimation
IEEE Transactions on Software Engineering
Why comparative effort prediction studies may be invalid
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models 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
Data accumulation and software effort prediction
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Handling categorical variables in effort estimation
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
IWSM-MENSURA '12 Proceedings of the 2012 Joint Conference of the 22nd International Workshop on Software Measurement and the 2012 Seventh International Conference on Software Process and Product Measurement
Investigating the Use of Duration-Based Moving Windows to Improve Software Effort Prediction
APSEC '12 Proceedings of the 2012 19th Asia-Pacific Software Engineering Conference - Volume 01
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Software development effort estimation is an essential aspect of software project management. An effort estimation model expresses relationships between effort and factors such as organizational and project features (e.g. software functional size, and the programming language used in a project). However, software development practices and tools change over time, to environmental changes. This can affect some relationships assumed in an effort estimation model. A moving windows method (a method for treating the timing information of projects), has thus been proposed for estimation models. The moving windows method uses data from a fixed number of the most recent projects data for model construction. However, it is not clear that moving windows is the best way to handle the timing information in an estimation model. The goal of our research is to determine how best to treat timing information in constructing effort estimation models. To achieve the goal, we compared six different methods (moving windows, dummy variable of moving windows, dummy variables of equal bins, dummy variables of year, year predictor, and serial number) for treating timing data, in terms of estimation accuracy. In the experiment, we use three software development project datasets. We found that moving windows is best when the number of projects included in the dataset is not small, and dummy variable of moving windows is the best when the number is small.