EsPreSSE Special Session

Estimation and Prediction in Software & Systems Engineering (ESPreSSE)
Special Session inside the SM Track

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.

Estimation and prediction for mobile systems: The increasing availability of large sets of rich data fuels estimation and prediction approaches also in related areas and new application contexts. 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. Topics of interest include, but are not restricted to:

  • Estimation and prediction approaches used for supporting software engineering tasks and guiding quality assurance
  • Estimation and prediction approaches for usage-, product- or process-related quality attributes
  • Approaches for risk estimation or prediction in mobile systems and software development projects
  • Case studies on the application of estimation or prediction in mobile 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)
  • Estimation and prediction based on big data in the area of pervasive and mobile computing
  • Predicting usage behavior, mobility patterns, and application contexts to support development and maintenance activities
  • Approaches based on app store mining and user feedback
  • New ideas, methods and tools for estimation or prediction

SEAA 2015 – EsPreSSE – Call for Papers in PDF format (updated).

Submission of Papers:

Special Session Organizers:

espresse_frankFrank Elberzhager, Fraunhofer IESE, Germany.
espresse_rudolfRudolf Ramler, Software Competence Center Hagenberg, Austria

Program Commitee

  • Ayse Basar Bener, Ryerson University, Canada
  • Christian Bird, Microsoft Research, United States
  • Maya Daneva, University of Twente, The Netherlands
  • Oscar Dieste, Universidad Politecnica de Madrid, Spain
  • Michael Felderer, University of Innsbruck, Austria
  • Robert Feldt, Blekinge Institute of Technology, Sweden
  • Christian Fruehwirth, Helsinki University of Technology, Finland
  • Jens Heidrich, Fraunhofer IESE, Germany
  • Magne Jorgensen, Simula Research Laboratory, Norway
  • Michael Klaes, Fraunhofer IESE, Germany
  • Ana Magazinius, Viktoria Swedish ICT, Sweden
  • Gerrit Meixner, Heilbronn University, Germany
  • Emilia Mendes, Blekinge Institute of Technology, Sweden
  • 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
  • Sebastiano Panichella, University of Zurich, Switzerland
  • Andreas Rausch, TU Clausthal, Germany
  • Norbert Seyff, University of Zurich, Switzerland
  • Burak Turhan, University of Oulu, Finland
  • Stefan Wagner, University of Stuttgart, Germany