Please note, we are currently updating the 2018 Journal Metrics. Empirical Software Engineering provides a forum for applied software engineering research with a strong empirical component, and a venue for publishing empirical results relevant to both researchers and practitioners. Empirical studies presented here usually involve the collection and analysis of data and experience that can be used to characterize, evaluate and reveal relationships between software development deliverables, practices, and technologies. Over time, it is expected that such empirical results will form a body of knowledge leading to widely accepted and well-formed theories. The journal also offers industrial experience reports detailing the application of software technologies - processes, methods, or tools - and their effectiveness in industrial settings. Empirical Software Engineering promotes the publication of industry-relevant research, to address the significant gap between research and practice.
Empirical Software Engineering
Description
Identifiers
ISSN | 1382-3256 |
e-ISSN | 1573-7616 |
DOI | 10.1007/10664.1573-7616 |
Publisher
Springer US
Additional information
Data set: Springer
Articles
Empirical Software Engineering > 2019 > 24 > 5 > 3153-3204
Software effort estimation is an online supervised learning problem, where new training projects may become available over time. In this scenario, the Cross-Company (CC) approach Dycom can drastically reduce the number of Within-Company (WC) projects needed for training, saving their collection cost. However, Dycom requires CC projects to be split into subsets. Both the number and composition of such...