EsPreSSE - Estimation and Prediction in Software & Systems Engineering (Special Session)

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 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.

Topics of interest include, but are not restricted to:

  • Estimation and prediction approaches used for guiding quality assurance and/or process improvement initiatives
  • Estimation and prediction approaches for usage-, product- or process-related quality attributes
  • Approaches for risk estimation or prediction in systems and software development projects
  • 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 fuzzy real-world data sets (e.g., incomplete, inconsistent, and/or erroneous)
  • New ideas, methods and tools for estimation or prediction

To increase the visibility of published papers, EsPreSSE cooperates with the PROMISE repository of reproducible SE experiments. Authors of accepted papers are invited to submit the associated data to the PROMISE repository. Contributions based on proprietary data from commercial and industrial projects are also welcome. These contributions should encompass a detailed description of the project and organizational context.

Authors of the best papers will be invited to revise and submit extended versions of their papers for publication in the International Journal of Software Engineering and Knowledge Engineering (IJSEKE).

Accepted papers will be included in the proceedings, published by the Conference Publishing Services (CPS). The proceedings of the conference will be submitted to Xplore and CSDL. The Paper submission system and further instructions are available at the submission page.

 

Session Organizers

rr Rudolf Ramler, Software Competence Center Hagenberg, Austria
dw Dietmar Winkler, Vienna University of Technology, Austria

Program Committee

  • Maria Teresa Baldassarre, University of Bari, Italy
  • Ayse Basar Bener, Ryerson University, Canada
  • Christian Bird, Microsoft Research, United States
  • Michel Chaudron, Leiden University, Netherlands
  • Maya Daneva, Univeristy of Twente, Netherlands
  • Oscar Dieste, Universidad Politecnica de Madrid, Spain
  • Frank Elberzhager, Fraunhofer IESE, Germany
  • Robert Feldt, Chalmers Univ. of Technolog, Sweden
  • Christian Frühwirth, Aalto University, Finland
  • Harald Gall, University of Zurich, Switzerland
  • Michael Kläs, Fraunhofer IESE, Germany
  • Emilia Mendes, Zayed Univ., United Arab Emirates
  • Tim Menzies, West Virginia Univ., United States
  • Sandro Morasca, University of Insubria, Italy
  • Raimund Moser, Free University of Bolzano, Italy
  • Jürgen Münch, University of Helsinki, Finland
  • Haruka Nakao, Japan Manned Space Systems Corp., Japan
  • Thomas Natschläger, SCCH Hagenberg, Austria
  • Thomas J. Ostrand, AT&T Labs Research, United States
  • Andreas Rausch, TU Clausthal, Germany
  • Barbara Russo, Free University of Bolzano, Italy
  • Harry M. Sneed, Anecon GmbH, Austria
  • Ayse Tosun Misirli, Bogazici University, Turkey
  • Burak Turhan, University of Oulu, Finland
  • Stefan Wagner, University of Stuttgart, Germany