ESEM - Technical TrackESEIW 2025

ESEM 2024 - Technical Papers Track - Call for Papers

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Software Engineering and Measurement (ESEM) technical papers track features submissions that describe original, unpublished work in software engineering and software measurement, with a strong empirical foundation.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.
Please note:

• Make sure the paper follows the standard IEEE template in conference mode (see https://www.ieee.org/conferences/publishing/templates.html)

• Make sure you adhere to the Open Science Policy (As described below)

• Make sure your paper follows the double-blind instructions and does not reveal the authors’ identities

General Scope of Submissions

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.

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.

Important Dates

(All dates are end of the day, anywhere on earth)

• Abstract (mandatory): Apr. 18th, 2025
• Submission: Apr. 25th, 2025
• Notification: June, 6th, 2025
• Camera-ready: June, 27th, 2025

How to Submit

Submissions to this track are limited to 10 pages excluding references and 12 pages with references and must be submitted through EasyChair by selecting the track “Technical Papers.”

All submissions must be written in English and must be submitted via EasyChair in PDF format, and they must be formatted according to the standard IEEE template in conference mode (which can be found at https://www.ieee.org/conferences/publishing/templates.html) or in Overleaf at https://www.overleaf.com/gallery/tagged/ieee-official).

A structured abstract is required with the headings: Background, Aims, Method, Results, and Conclusions. Papers must contain an explicit description of the empirical strategy used or investigated. The submission must also comply with the IEEE ethics guidelines https://journals.ieeeauthorcenter.ieee.org/wp-content/uploads/IEEE-Author-Ethics-Guidelines.pdf. In particular, it must not have been published elsewhere and must not be under review elsewhere while under review for ESEM.

ESEM 2025 Technical Track will employ a double-blind review process. Thus, submissions may not reveal their authors’ identities. The authors must make an acceptable effort to honor the double-blind review process. In particular, the authors’ names must be omitted from the submission and references to their prior work should be in the third person. More details on author ethics and peer review can be found at https://conferences.ieeeauthorcenter.ieee.org/.

All submissions will be peer-reviewed by at least three experts from the international program committee of each track and will receive an additional meta-review. Any papers that are outside the scope of the symposium, exceed the maximum number of pages for the respective category, or do not follow the formatting guidelines will be desk rejected without review. The PC members’ bidding information may be used to assess what is considered out of scope.

Finally, please note that each accepted paper in the technical track must have at least one author registered as a full (non-student) participant by the deadline for the camera-ready submission. If a researcher is an author on multiple accepted papers, each paper must still have its own full registration. In such cases, other co-authors must register to fulfill the requirement for each paper. Also, each paper must be presented by one of the authors. Failure to meet these criteria will result in the paper’s removal from the proceedings.

Open Science Policy

Openness in science is key to fostering progress via transparency, reproducibility, and replicability. While all submissions will undergo the same review process independent of whether or not they disclose their tools, data, and code, we expect authors to include a data availability statement in their submissions that either provides links to the open data/replication package or that explains why data cannot be disclosed (e.g., due to the sensitivity of the data or due to existing non-disclosure agreements). We recommend adding the data availability statement in the submission at the end of the introduction section explaining whether and where the data and related material is available and under which conditions the data/material can be accessed. For submissions based on open data sources, the publication of any cleaned or filtered data is mandatory.

To submit your tools, data, and code while still following the double-blind process, please refer to these guidelines.

Authors are requested to share their tools, data, and code in the form of a replication package and explain how to use and navigate it.

• Qualitative studies should provide explanations about the study protocol, coding and transcription schemas, and further relevant information.

• Quantitative studies should include information about the source code and its main dependencies (incl. version), description of input/output relevant to every step of data cleaning and labeling, feature engineering, model training, and evaluation.

We recommend providing these explanations in the method section of the paper, while further explanations and concrete instructions on how to navigate and use the replication package can be detailed in a README file.

We recommend:

• Share pre-prints in a non-commercial repository (e.g., arXiv) using an appropriate license (e.g., arXiv default non-exclusive license, Creative Commons CC-BY). When sharing pre-prints, authors must avoid specifying that the manuscript was submitted to ESEM 2024. We recommend against anonymizing them (i.e., by changing authors, title, abstract). The review committee members are instructed NOT to try to find out the identity of the authors.

• Share replication packages in an archival repository (e.g., Zenodo) using an appropriate license (e.g., based on Creative Commons).

For further information, please refer to “Open Science in Software Engineering” book chapter.