2nd International Workshop on Methodological Issues with Empirical Studies in Software EngineeringWSESE 2025

Theme & Goals

With the steep increase in empirical studies and the advent of secondary studies that aggregate their results, a main concern is their quality. Although researchers have raised concerns about various quality issues for many years, many of these issues persist, partially due to the complexity of empirical studies in our field—whether human subjects are involved or not. Problems related to appropriate design and the correct usage of statistical methods are crucial for the reliability of the results. Consequently, as a community, we need to better understand these issues and how to mitigate, if not eliminate, them. The workshop’s aim is to increase awareness of the importance of quality and appropriateness in the methods applied during the different stages of software engineering empirical studies to yield reliable results and to disseminate this knowledge to the broader SE community.

This year, we are placing a special emphasis on Machine Learning (ML). We encourage submissions that explore the integration and application of ML techniques throughout the empirical process. Contributions that address methodological challenges in conducting empirical studies with ML techniques are highly welcomed.

Previous Editions

• WSESE 2024 was held on April 16, 2024 in Lisbon, Portugal (co-located with ICSE 2024).

Call for Papers

This year, we are placing a special emphasis on Machine Learning (ML). We encourage submissions that explore the integration and application of ML techniques throughout the empirical process. Contributions that address methodological challenges in conducting empirical studies with ML techniques are highly welcomed.

Topics of interest include, but are not restricted to:

• Issues with the motivation and definition of appropriate research questions.
• Issues with the operationalization, e.g., missing standard metrics.
• Issues with the systematic identification of threats to validity and how to address them
• Issues selecting an appropriate study design and the consequences of that selection,
• Issues with drawing appropriate conclusions from the findings and generalizing them
• Issues with aggregating results from individual studies
• Issues with reproduction, replication, or families of studies
• Issues with quantitative, qualitative approaches and combined approaches
• Issues with understanding failures and successes: lessons learned

Paper categories

• Technical papers (6-8 pages): formally describe studies, explain how they were designed and executed to overcome challenges, highlight concrete results, and describe any advances to the state-of-the-art.
• Experience reports / Work in progress (4-6 pages) describe the experience in conducting studies and lessons learned that address methodological issues.
• Vision / Position papers (2-4 pages) describe new directions in conducting empirical studies including convincing arguments supported by clear rationale.
• Panel proposals (1-2 pages) discuss hot topics about conducting empirical studies.

Papers must describe original work that has not been submitted to or presented at other forums (although the studies described may have been). Accepted papers will be published in the ICSE workshop proceedings.

Submission information

Submissions will be made via hotcrp. Papers must be formatted according to ICSE 2025 guidelines. The official publication date of the workshop proceedings is the date the proceedings are made available by IEEE. This date may be up to two weeks prior to the first day of ICSE 2025. The official publication date affects the deadline for any patent filings related to published work.