Guenther Ruhe


Department of Computer Science

Industrial Research Chair in Software Engineering, Unveristy of Calgary

University of Calgary

Doctor of Habilitation Informatics

Kaiserlautern University, 2001

Doctor of Habilitation Operations Research

Leipzig University of Tech, 1988

Doctor of Natural Sciences Operations Research

TU Bergakademie Frieberg, 1981

Bach of Math

University of Leipzig, 1975

Contact information


Office : ICT545


  • CPSC 594 - Software Engineering Project
  • SENG 511 - Software Project Management
  • SENG 608 - Analytical Software Project Management

Research and teaching

Research areas

  • Software Engineering Decision Support
  • Empirical Software Engineering
  • Requirements Engineering
  • Release Engineering
  • Software Project Management
  • Data Analytics
  • Open Innovationn
  • Search-based Optimization
  • Crowdsourcing


The research of the Software Engineering Decision Support (SEDS) laboratory is centered on models, method and tools to facilitate better decision-making. Emphasis is on the early stages of the software life-cycle. The idea of offering decision support always arises when decisions have to be made in complex, uncertain and/or dynamic environments. What that means is to offer a context-specific methodology which helps in (i) increasing the likelihood to make a good decision towards achieving stated goals, (ii) structuring and reducing the space of alternatives to facilitate human expert involvement for the final selection of the decision alternative, and (iii) justifying and explaining proposed decision alternatives. In my research group, there is an increasing focus on Analytics of Software Engineering Data as a means to extract information and to support decisions. The new direction of Analytical Open Innovation combines the open access to information, knowledge, artefacts and resources with the strengths of analytical methods. Optimization and search-based techniques for problem with one or multiple criteria are one of the approaches used to actually determine (optimized) solution alternatives.