# ESEM — International Symposium on Empirical Software Engineering and Measurement

- **Submission deadline**: 2026-04-22
- **Notification date**: 2026-06-30
- **Conference date**: 2026-10-04
- **Location**: Munchen, Germany
- **Rankings**: CCF B · CORE A · QUALIS A2
- **Conference Partner Index**: 72.7/100 (ranked #289, confidence 0.80, algorithm 1.1) — how this is computed: https://www.myhuiban.com/ranking
- **Trackers**: 64
- **Attendees**: 5
- **Canonical page**: https://www.myhuiban.com/conference/174

## Call for papers

The International Symposium on Empirical Software Engineering and Measurement (ESEM) technical papers (main) track features submissions that describe original, unpublished work in software engineering and software measurement, with a strong empirical foundation. Papers in this track should communicate fully developed research and results. Strong emphasis should be given to the methodological aspects of the research and the assessment of the validity of the contributions. Please note: Open Science policy: ESEM is open by default. Submissions must comply with the Open Science Policy and provide the artifacts needed to understand and reproduce the analysis, unless legal/ethical barriers exist (see details on Data Availability below). Double-anonymous review format: ESEM 2026 uses double blind reviewing. Submissions must not reveal authors’ identities. General scope of submissions Submissions must not be under consideration for publication or presentation elsewhere. In addition to the specific scope of this track, submissions may address any aspect of software engineering but must tackle the problem from an empirical perspective and using a rigorous empirical method, including (but not limited to): Empirical studies using qualitative, quantitative, and mixed methods Cross- and multi-disciplinary methods and studies Controlled experiments and quasi-experiments Case studies, action research, ethnography, and field studies Survey research Simulation studies Artifact studies Data mining using statistical, machine learning, and AI-based approaches Meta-studies and evidence syntheses, including: Systematic literature reviews and rapid reviews with a strong synthesis component and a clear contribution beyond overview summarization Meta-analyses, and qualitative, quantitative, or structured syntheses of prior studies that generate clear new insights Replication studies Papers should be positioned in terms of research methodology and contribution in relation to established frameworks for empirical software engineering and measurement. Negative results are also welcome as long as the research is based on well-motivated hypotheses in line with the state-of-the-art, relevant scientific knowledge that is then well-documented, analysed in depth, and provides clear value to the community. Topics of interest (illustrative, not exhaustive) Topics in scope for ESEM 2026 and commonly addressed using an empirical approach include, but are not limited to: Evaluation and comparison of software models, tools, techniques, and practices Modeling, measuring, and assessing product or process quality and productivity Continuous software engineering Software verification and validation, including analysis and testing Engineering of software systems that include machine learning components and data dependencies Applications of software engineering to different types of systems and domains (e.g., IoT, cyber-physical systems, Industry 4.0) Human factors, teamwork, and behavioral aspects of software engineering We also welcome submissions that relate to meta-topics around empirical software engineering research, including for example: Development, evaluation, and comparison of empirical approaches and methods Infrastructure, techniques, and tools for conducting and supporting empirical studies

## Related conferences

- ESEIW — Empirical Software Engineering International Week — https://www.myhuiban.com/conference/3672
- ICRA — International Conference on Robotics and Automation — https://www.myhuiban.com/conference/421
- IJCAI — International Joint Conference on Artificial Intelligence — https://www.myhuiban.com/conference/405
- ICASSP — International Conference on Acoustics, Speech and Signal Processing — https://www.myhuiban.com/conference/429
- PODS — ACM SIGMOD Conference on Principles of DB Systems — https://www.myhuiban.com/conference/138

## Related journals

- Measurement — https://www.myhuiban.com/journal/678
- Empirical Software Engineering — https://www.myhuiban.com/journal/81
- Measurement: Sensors — https://www.myhuiban.com/journal/1105
- Measurement and Control — https://www.myhuiban.com/journal/1030
- Software & Systems Modeling — https://www.myhuiban.com/journal/99

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Source: Conference Partner — https://www.myhuiban.com/conference/174 (rankings reproduced from CCF / ICORE / QUALIS; data cached up to 1 hour)