Software and Systems (SAS)

The Division of Software and Systems is part of the Department of Computer and Information Science. The division conducts research and education in software engineering and computer systems.

A person sits in front of a computer screen and handles a floor robot Photo credit Jonas Järmen Research and education are conducted in the following areas:

  • Software Engineering
  • Programming Models and Environments
  • Software and System Modelling and Simulation
  • System Software
  • Embedded/Cyberphysical Software/Hardware Systems
  • Computer Systems Engineering
  • Real-Time Systems and System Dependability
  • Parallel and Distributed Software and Systems
  • Software and System Verification and Testing


The research activities covers both basic research and projects in cooperation with industry - projects are or have been conducted in cooperation with ABB Robotics, ABB Industrial Systems, Ericsson Softlab AB, Ericsson Radio Systems, Ericsson Telecom, SKF, Saab, Saab Dynamics, Saab Combitech and several other companies.

Hands on laptop keyboard, a circuit board in the background Photo credit Jonas Järmen
In addition, the research activities include several long-term open-source system development efforts, such as the OpenModelica framework for object-oriented equation-based modeling and simulation of cyberphysical systems, and the SkePU high-level programming framework for heterogeneous parallel systems.

Nine full professors, eight associate/assistant professors and several postdocs are involved in the research together with about 25 graduate students. 

Students listening to a teacher pointing to an example at a big screen. Photo credit Jonas Järmen

The SaS Seminars is a permanent series of open seminars with topics related to research at the division.

Research is conducted in three laboratories

Embedded Systems (ESLAB)
Codesign and design for testability of embedded/cyberphysical hardware/software systems and formal methods for embedded systems.

Programming Environments (PELAB)
Software engineering tools and architectures, large-scale software engineering, model-based software engineering, programming languages and systems, including compilers, debuggers, testing tools, and programming tools for parallel, distributed and real-time systems.

Real Time Systems (RTSLAB)
Dependable systems and networks, including reliability, safety and security, resource efficiency with respect to computation capacity, memory, bandwidth and energy.


The division accounts for a significant share of the department's comprehensive undergraduate and master-level education activities, operating about 70 undergraduate/master-level courses per year as well as providing final-thesis supervision.Group of students working on computers.. Photo credit Jonas Järmen
The undergraduate teaching activities are jointly carried out by the researchers and by the UPP education group for programming and programming didactics, which consists of about ten full-time university teachers and many teaching assistants.

Doctoral studies are offered in the field of Computer Science.  

News at SAS

News and major articles

Power generation in an illustrated landscape

Open Modelica helping to solve complex societal issues

OpenModelica is a free tool, partially developed at Linköping University, to model and simulate complex systems. It is an open-source system, which enables many actors to contribute and benefit companies and society.

Chu Wanjun visar för gruppen vilka frukter roboten kan känna igen just nu. I förgrunden ligger en apelsin.

Minister for Energy and Digital Development visits IDA

On Wednesday, 20 april 2022, the minister for digital development Khashayar Farmanbar visited the Department of Computer and Information Science together with the Linköping municipal councillor Mari Hultgren.

Computer turned on with colorful light.

30 million in grant for developing software for smart technology

The Swedish Foundation for Strategic Research (Stiftelsen för strategisk forskning, SSF) has given SEK 30 million in a grant to a research project at Linköping University.

Research at SAS

Latest publications


Mohamed Ebeed, Shimaa Ali, Ahmed M. Kassem, Mohamed Hashem, Salah Kamel, Abdelazim Hussien, Francisco Jurado, Emad A. Mohamed (2024) Solving stochastic optimal reactive power dispatch using an Adaptive Beluga Whale optimization considering uncertainties of renewable energy resources and the load growth Ain Shams Engineering Journal, Vol. 15, Article 102762 Continue to DOI
José Antonio Hernández López, Jesus Sanchez Cuadrado, Riccardo Rubei, Davide Di Ruscio (2024) ModelXGlue: a benchmarking framework for ML tools in MDE Software and Systems Modeling Continue to DOI
Nabil Neggaz, Amir Seyyedabbasi, Abdelazim Hussien, Mekki Rahim, Mehmet Beskirli (2024) Optimal Nodes Localization in Wireless Sensor Networks Using Nutcracker Optimizer Algorithms: Istanbul Area IEEE Access, Vol. 12, p. 67986-68002 Continue to DOI
P. L. S. Jayalaxmi, Manali Chakraborty, Rahul Saha, Gulshan Kumar, Mauro Conti (2024) MADESANT: malware detection and severity analysis in industrial environments Cluster Computing Continue to DOI
Bjorn Birath, August Ernstsson, John Tinnerholm, Christoph Kessler (2024) High-Level Programming of FPGA-Accelerated Systems with Parallel Patterns International journal of parallel programming Continue to DOI
Johannes Klaus Fichte, Thomas Eiter, Hecher Markus, Stefan Woltran (2024) Epistemic Logic Programs: Non-Ground and Counting Complexity Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24)
Fatma A. Hashim, Abdelazim Hussien, Anas Bouaouda, Nagwan Abdel Samee, Ruba Abu Khurma, Hayam Alamro, Mohammed Azmi Al-Betar (2024) An enhanced exponential distribution optimizer and its application for multi-level medical image thresholding problems Alexandria Engineering Journal, Vol. 93, p. 142-188 Continue to DOI
Reham R. Mostafa, Abdelazim Hussien, Marwa A. Gaheen, Ahmed A. Ewees, Fatma A. Hashim (2024) AEOWOA: hybridizing whale optimization algorithm with artificial ecosystem-based optimization for optimal feature selection and global optimization Evolving Systems Continue to DOI
Ponugoti Kalpana, R. Anandan, Abdelazim Hussien, Hazem Migdady, Laith Abualigah (2024) Plant disease recognition using residual convolutional enlightened Swin transformer networks Scientific Reports, Vol. 14, Article 8660 Continue to DOI
Yaning Xiao, Hao Cui, Abdelazim Hussien, Fatma A. Hashim (2024) MSAO: A multi-strategy boosted snow ablation optimizer for global optimization and real-world engineering applications Advanced Engineering Informatics, Vol. 61, Article 102464 Continue to DOI

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