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.

Accepted papers will be included in the proceedings published by the IEEE Computer Society in IEEE Xplore and CSDL. Extended versions of selected (best) papers will also be considered for publication in a special issue of a journal.

Session Organizers

Iv Rudolf Ramler, Software Competence Center Hagenberg, Austria
ra Dietmar Winkler, Vienna University of Technology, Austria

Program Committee

Maria Teresa Baldassarre, University of Bari, Italy
Ayse Bener, Ryerson University, Canada
Christian Bird, Microsoft Research, United States
Maya Daneva, University of Twente, Netherlands
Oscar Dieste, Universidad Politecnica de Madrid, Spain
Frank Elberzhager, Fraunhofer IESE, Germany
Robert Feldt, Chalmers University of Technology, Sweden
Christian Frühwirth, Aalto University, Finland
Harald Gall, University of Zurich, Switzerland
Marcela Genero, Universidad de Castilla-La Mancha, Spain
Jens Heidrich, Fraunhofer IESE, Germany
Michael Kläs, Fraunhofer IESE, Germany
Emilia Mendes, Zayed University, United Arab Emirates
Tim Menzies, West Virginia University, United States
Sandro Morasca, University of Insubria, Italy
Raimund Moser, Free University of Bolzano, Italy
Jürgen Münch, University of Helsinki, Finland
Thomas Natschläger, Software Competence Center Hagenberg, Austria
Thomas J. Ostrand, Rutgers University, United States
Andreas Rausch, TU Clausthal, Germany
Barbara Russo, Free University of Bolzano, Italy
Harry M. Sneed, Anecon GmbH, Austria
Burak Turhan, University of Oulu, Finland
Stefan Wagner, University of Stuttgart, Germany