Towards better selection between moving windows and growing portfolio

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Abstract

BACKGROUND: Several studies in software effort estimation have shown that it can be effective to use a window of recent projects, rather than the growing portfolio of all past projects, as training data. Practitioners need a method for choosing between those approaches when estimating effort for a target project. OBJECTIVE: This study examined the usefulness of the fitted values for choosing between moving windows and the growing portfolio. METHOD: An empirical experiment was conducted with a single-company ISBSG dataset. RESULTS: The fitted values could be useful for the selection on average. CONCLUSIONS: This positive result contributes to understanding when windows may be appropriate.

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APA

Amasaki, S., & Lokan, C. (2016). Towards better selection between moving windows and growing portfolio. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10027 LNCS, pp. 627–630). Springer Verlag. https://doi.org/10.1007/978-3-319-49094-6_49

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