Call for Papers ― EMSE Special Issue on “Trends in Predictive Models and Data Analytics in Software Engineering”

A special issue of the Empirical Software Engineering Journal. http://www.springer.com/computer/swe/journal/10664

Editors of the Special Issue

• Steffen Herbold, University of Passau
• Eunjong Choi, Kyoto Institute of Technology

Contact person

• Steffen Herbold, University of Passau - steffen.herbold@uni-passau.de
• Eunjong Choi, Kyoto Institute of Technology - echoi@kit.ac.jp

Description of the Special Issue

This special issue in the Empirical Software Engineering journal is intended to provide practitioners and researchers with a venue to present insights, innovations, and solutions in construction and/or application of predictive models and data analytics in software engineering. Submitted papers must have a strong empirical basis/component to be eligible for this special issue. Empirical Software Engineering (http://link.springer.com/journal/10664) provides a forum for applied software engineering research with a strong empirical component and a venue for publishing empirical results relevant to both researchers and practitioners. In addition to the open call for papers, all authors with an accepted paper to PROMISE 2023 are encouraged to submit extended versions of their work. To comply with the goals of a journal publication, we are asking to revise and substantially extend original PROMISE 2023 papers. Some possible extensions can be adding additional practical applications determined through case studies or experiments, additional empirical validation, systematic comparisons with other approaches, or a sound theoretical foundation. Revised papers should explicitly explain how they extend the original PROMISE papers.

All submissions will be reviewed using the Empirical Software Engineering Journal standards and will undergo a rigorous reviewing process. Reviews of extended papers may include some of the reviewers of the PROMISE 2023 paper as well as some new reviewers. The guest editors of the special issue are not permitted to submit.

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least two independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.

Submission Topics

Application-oriented papers: prediction of cost, effort, quality, defects, business value; quantification and prediction of other intermediate or final properties of interest in software development regarding people, process or product aspects; using predictive models and data analytics in different settings, e.g. lean/agile, waterfall, distributed, and community-based software development; dealing with changing environments in software engineering tasks; dealing with multiple-objectives in software engineering tasks; using predictive models and software data analytics in policy and decision-making.

Ethically-aligned papers: can we apply and adjust our AI-for-SE tools (including predictive models) to handle ethical non-functional requirements such as inclusiveness, transparency, oversight and accountability, privacy, security, reliability, safety, diversity and fairness?

Theory-oriented papers: model construction, evaluation, sharing and reusability; interdisciplinary and novel approaches to predictive modelling and data analytics that contribute to the theoretical body of knowledge in software engineering; verifying/refuting/challenging previous theory and results; combinations of predictive models and search-based software engineering; the effectiveness of human experts vs. automated models in predictions.

Data-oriented papers: data quality, sharing, and privacy; curated data sets made available for the community to use; ethical issues related to data collection and sharing; metrics; tools and frameworks to support researchers and practitioners to collect data and construct models to share/repeat experiments and results.

Validity-oriented papers: replication and repeatability of previous work using predictive modelling and data analytics in software engineering; assessment of measurement metrics for reporting the performance of predictive models; evaluation of predictive models with industrial collaborators.

Schedule

Submission Deadline: April 14th, 2024 May 3rd, 2024

Submission Instructions

Papers should be submitted through the Empirical Software Engineering editorial manager website (http://www.editorialmanager.com/emse/) as follows (1) select “Research Papers” and (2) later on the Additional Information page: Answer “Yes” to “Does this paper belong to a special issue?” and select “PROMISE 2023” for “Please select the issue your manuscript belongs to”. For formatting guidelines as well as submission instructions, visit http://www.springer.com/computer/swe/journal/10664?detailsPage=pltci_2530593