At the Department, we value Research and Development as a form of learning by doing. We believe that in such a rapidly growing area as software engineering, R&D activities should be practice-oriented and problem-driven. Our goal is to keep the competence of our staff up-to-date with the latest research achievements and technologies, and for that we strive for conducting high-impact and actionable research for solving real problems driven by industry needs. The academic background of our core staff with decades long educator’s and researcher’s background, the notable pool of students, young researchers and engineers and countless projects successfully performed is the basis for conducting R&D that is beneficial for the department, our industrial partners and students alike.
R&D activities in our 6 core competence areas explore new frontiers and solve problems in some of the most important fields related to software engineering today.
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Software Quality: Code Analysis and Testing. During the years, we have gained a significant amount of know-how in software quality assurance: code analysis and software testing. We have developed a wide range of methods and tools for quality assessment and the improvement of large, industrial systems, and our group is globally known as one of the top competence centers globally in this area.
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CyberSecurity: IT Security is an important dimension of software quality, and it is increasingly important in areas that are critical from a security vulnerability point of view, including cloud technologies, networking, and IoT devices. Our department has developed competences in various related fields such as vulnerability assessment, security testing, robustness and fuzz testing, and secure coding, among others.
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M2M & Embedded Systems: Machine-to-Machine ecosystems is a special field that has a wide variety of challenges. It has a strongly distributed and heterogeneous nature both in the physical and platform dimensions. It covers not only the field of software engineering, but also telecommunications, hardware design and development, and several areas like healthcare and AMR.
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Cloud: The interoperation of cloud, fog and IoT technologies and the analysis of complex systems created with them. Our department is the key developer of the MobIoTSim and DISSECT-CF simulation environments, and related research tools.
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IoT: Utilizing its decades long experience in compiler technologies, the Department has been participating in the development of IoT execution environments for resource-constrained, embedded, smart, IoT devices.
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Deep Learning & NLP in Software Engineering: Deep learning has gained significant attention in recent years because it is successfully applied to a large number of difficult problems, which was previously not possible to solve due to the lack of computation power and suitable training data. Our department explores the application of Deep Learning together with Natural Language Processing to software engineering problems.
In addition to these main technical areas, the Department has a significant horizontal knowledge in open source technologies and development processes. We have a long history in contributing to open source projects and cooperating with open source communities. Highlights of this work include compiler development, file system implementations, Drupal-based development and the energy management of embedded systems.
Our strategic goal is to spread the accumulated knowledge in all the areas above at all levels of education, including university curricula, and special professional trainings offered to organizations and individuals.