Research output per year
Research output per year
Project Details
Description
This cluster focuses on the engineering of software systems, which are large, constantly changing, adaptive, and as a consequence, systems of socio-technical systems. We address both software engineering principles and practices for smart systems (SE4AI) and design smart approaches to support the engineering of software (AI4SE).
Vision of the cluster
Our vision is to pave way for continuous software engineering approaches that combine human experimentation, autonomous experimentation and data-driven behavior in an integral approach, including architecture, development processes and management perspectives.
Main research questions
The overall research questions relate to the integration of continuous experimentation and data-driven software engineering into the practice of large-scale software engineering. Which development, experimentation and data analysis methods are efficient and scalable? Which approaches give value to the end user? How to support bridging management and engineering of software?
Vision of the cluster
Our vision is to pave way for continuous software engineering approaches that combine human experimentation, autonomous experimentation and data-driven behavior in an integral approach, including architecture, development processes and management perspectives.
Main research questions
The overall research questions relate to the integration of continuous experimentation and data-driven software engineering into the practice of large-scale software engineering. Which development, experimentation and data analysis methods are efficient and scalable? Which approaches give value to the end user? How to support bridging management and engineering of software?
| Status | Finished |
|---|---|
| Effective start/end date | 2020/01/01 → 2021/08/31 |
Collaborative partners
- Lund University (lead)
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Concepts in testing of autonomous systems: Academic literature and industry practice
Song, Q., Engstrom, E. & Runeson, P., 2021, Proceedings - 2021 IEEE/ACM 1st Workshop on AI Engineering - Software Engineering for AI, WAIN 2021. IEEE - Institute of Electrical and Electronics Engineers Inc., p. 74-81 8 p. 9474374. (Proceedings - 2021 IEEE/ACM 1st Workshop on AI Engineering - Software Engineering for AI, WAIN 2021).Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review
Open Access -
Controlled experimentation in continuous experimentation: Knowledge and challenges
Auer, F., Ros, R., Kaltenbrunner, L., Runeson, P. & Felderer, M., 2021, In: Information and Software Technology. 134, 106551.Research output: Contribution to journal › Article › peer-review
Open Access -
Getting Started with Chaos Engineering – design of an implementation framework in practice
Jernberg, H., Runeson, P. & Engström, E., 2020, Proceedings of the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) Industry Track. Cataldo, M. & Ciolkowski, M. (eds.). Association for Computing Machinery (ACM), 10 p. 43Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review
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WASP: Wallenberg AI, Autonomous Systems and Software Program at Lund University
Årzén, K.-E. (Researcher)
2015/10/01 → 2029/12/31
Project: Research
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Software testing of autonomous systems
Song, Q. (Researcher), Runeson, P. (Supervisor) & Engström, E. (Assistant supervisor)
2020/01/01 → 2024/12/31
Project: Dissertation
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Continuous system testing using autonomous monitors
Hrusto, A. (PI), Runeson, P. (Supervisor), Engström, E. (Assistant supervisor) & Ohlsson, M. C. (Assistant supervisor)
2019/11/13 → 2024/11/08
Project: Dissertation