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EsPRESSE@SEAA 2018 : SEAA 2018 - Special session on Estimation and Prediction in Software and Systems Engineering


When Aug 29, 2018 - Aug 31, 2018
Where Prague, Czech Republic
Abstract Registration Due Feb 22, 2018
Submission Deadline Mar 1, 2018
Notification Due May 15, 2018
Final Version Due Jun 15, 2018
Categories    software metrics   software engineering

Call For Papers

Special Session @ 44th EUROMICRO SEAA Conference

EsPreSSE – Estimation and Prediction in Software and Systems Engineering

Estimation and prediction approaches are a valuable foundation for planning activities and for making the right decisions at the right time in software and systems engineering. Over the last decade, research and practice in software estimation and prediction have advanced the ability to infer likely future results and implications for project and product development based on the present development stage, experiences gained in previous project phases, and data from past projects. The increasing availability of large sets of rich data fuels estimation and prediction approaches also in related areas and new application contexts, e.g., Internet of Things, Software Ecosystems, Estimation of value in business models, mobile systems or multi-disciplinary engineering projects. A tremendous trend is the application of mobile devices in several domains and the corresponding app development. New challenges arise, such as achieving a faster time to market, focusing on quality properties such as usability, security, and how to balance them, or deciding the point to release an app regarding faster feedback versus better quality. The objective of this special session is to provide a forum where researchers and practitioners discuss applications and results of software estimation and prediction approaches. In particular, the session encourages the exchange of experiences from applications in commercial, industrial and open source projects that indicate strengths and limitations of these approaches in a real-world setting. We encourage especially submissions in the area of mobile systems.

The EsPreSSE Session is an integral part of the Software Management track of the 44rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018.

Topics of interest include, but are not restricted to:
- Estimation and Prediction approaches to support of software engineering tasks and guidance for quality assurance.
- Estimation and prediction of usage behavior and applications to support development and maintenance activities.
- Risk estimation and prediction in software and systems development projects.
- Usage-, product- or process-related quality attributes.
- Machine learning for estimation and prediction.
- Case studies on the application of estimation or prediction in software and systems engineering.
- Experience reports about successful or unsuccessful estimation or prediction including a retrospective analysis and lessons learned.
- Practical approaches for constructing effort and prediction models from real-world data sets (e.g., incomplete, inconsistent, fuzzy, and/or erroneous).
- New ideas, methods and tools for estimation or prediction.

In particular, we encourage submissions demonstrating the benefits or limitations of EsPreSSE approaches through case studies, experiments, and quantitative data.

The conference proceedings will be published by the IEEE Computer Society. The format is the IEEE two-column proceedings format. Submission will be handled via EasyChair

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Please find general submission information for SEAA on the conference homepage. Please note that it is planned to select best papers among all tracks of SEAA and present them with an award.

A selection of best papers will be invited to submit extended versions for tentative publication in a requested Special Issue of the Journal of Systems and Software published by Elsevier

Special Session Organizers
- Frank Elberzhager, Fraunhofer Institute for Experimental Software Engineering, Germany.
- Miroslaw Staron, University of Göteborg, Sweden,
- Dietmar Winkler, Vienna University of Technology, Austria,

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