The International Symposium on Empirical Software Engineering and Measurement (ESEM) technical papers track features submissions that describe original, unpublished work in software engineering and software measurement, with a strong empirical foundation.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 related results. Strong emphasis should be given to the methodological aspects of the research and the assessment of the validity of the contributions.

Submissions should 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:

- Empirical studies using qualitative, quantitative, and mixed methods
- Cross- and multi-disciplinary methods and studies
- Formal experiments and quasi-experiments
- Case studies, action research, ethnography and field studies
- Survey research
- Simulation studies
- Artifact studies
- Data mining using statistical and machine learning approaches
- Secondary and tertiary studies including
-- Systematic literature reviews and rapid reviews, that include a strong synthesis part
-- Meta-analyses, and qualitative, quantitative or structured syntheses of studies
- Replication of empirical studies and families of studies

Papers should be positioned in terms of research methodology and contribution in relation to established frameworks, e.g. https://link.springer.com/article/10.1007/s10664-020-09858-z, https://dl.acm.org/doi/10.1145/3241743 or https://github.com/acmsigsoft/EmpiricalStandards.

Topics 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 which include machine learning components and data dependencies
- Applications of software engineering to different types of systems and domains (e.g. IoT, Industry 4.0, Context-awareness systems, Cyber-physical systems)
- Human factors, teamwork, and behavioral aspects of software engineering

We welcome submissions on these research meta-topics:

- Development, evaluation, and comparison of empirical approaches and methods
- Infrastructure for conducting empirical studies
- Techniques and tools for supporting empirical studies
- Empirically-based decision making

We also welcome submissions that:

- demonstrate multi-disciplinary work,
- transfer and apply empirical methods from other disciplines,
- replication studies, and
- studies with negative findings.

For further information see: https://conf.researchr.org/track/esem-2023/esem-2023-technical-track