SPLC 2022 : 26th ACM International Systems and Software Product Line Conference

Context

The International Systems and Software Product Lines Conference (SPLC) is the leading conference on variability and configuration of hardware and software systems. Researchers, practitioners, and educators present and discuss the most recent research breakthroughs, ideas, trends, experiences, challenges and solutions to advance the state-of-the-art. SPLC is ranked as a top conference and for this 26th edition, we strive to continue the success of previous years by welcoming high-quality submissions for the research track.

SPLC started 26 years ago with a focus on software product lines, but by now it has become a main event for numerous closely related areas, such as configurable systems, product configuration, and software variability.

We are negotiating a special issue with a top-tier journal. In addition, each accepted full paper of the research track is considered for the Best Research Paper Award, and the authors are encouraged to submit an extended version of their paper to the special issue. The Best Student Research Paper Award is reserved for papers with a PhD student as the main author.

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Topics

The following is a list of topics of interest to SPLC, but we also invite submissions to related topics. If in doubt, feel free to ask the track chairs (see below).

AI: genetic algorithms, neural networks, and machine learning for product lines
Architecture, design, and visualization of product lines
Dynamic software product lines, reconfigurable systems, (self-)adaptive systems
Evolution, maintenance, and continuous integration for product lines (e.g., DevOps)
Formal methods and SPL verification techniques (e.g., program analysis, model checking)
Green and sustainable technologies for variation
Human, organizational and social aspects of product lines (e.g., BPM, collaborative modeling and development, cooperative configuration processes, economics, program comprehension)
Language product lines, and domain-specific and programming languages for product lines
Multi product lines, program families, product lines of product lines, software ecosystems
Non-functional properties: modeling, analysis, and optimization (e.g., performance, energy)
Reverse engineering, variability mining and refactoring (e.g., migration from clone-and-own)
Recommender systems for configurators and feature models (e.g., CSP/SAT/SMT solvers)
Specification and modeling of SPL (e.g., domain-specific modeling, model-driven engineering)
Testing product lines (e.g., product sampling, test-case selection and prioritization, mutations)
Variability management and variability modeling (e.g., feature models, decision models)

Submission Guidelines

The research track is open to submissions in two categories:

Full papers describing original results of conceptual, theoretical, empirical, or experimental research. The papers in this category must rely on theoretical or empirical evaluation.
Short papers describing emerging ideas or outstanding challenges along with possible approaches for resolving them.

In this 26th edition of SPLC, we will follow a double-blind review process. The identity of authors will not be known to the program committee at any time during the process. The papers submitted must not reveal the authors’ identities in any way.

Authors should leave out author names and affiliations from the body of their submission.
Authors should ensure that any citation to related work by themselves is written in the third person, that is, “the prior work of XYZ” as opposed to “our prior work”.
Authors should avoid providing URLs to author-revealing sites (tools, data sets). The paper can mention the existence of such sites, but the visit of such sites should not be needed to conduct the review.
Authors should anonymize author-revealing company names, yet can provide general characteristics of the organizations involved needed to understand the context of the paper.

Authors having further questions on double-blind reviewing are encouraged to contact the Program Chairs by email. Papers that do not comply with the double-blind review process will be desk-rejected.

Each submission will be carefully reviewed by at least three members of the research track program committee. The page limit is 10 pages of content (+ 2 pages for references) for full papers and 5 pages of content (+ 2 pages for references) for short papers. Submissions must adhere to the latest ACM Master Article Template: https://www.acm.org/publications/proceedings-template

Latex users should use the “sigconf” option, so they are recommended to use the template that can be found in “sample-sigconf.tex”. In this way, the following latex code can be placed at the start of the latex document to create a double column layout:

\documentclass[sigconf,review,anonymous]{acmart}

\acmConference[SPLC’22]{26th ACM International Systems and Software Product Lines Conference}{12-16 September, 2022}{Graz, Austria}

The proceedings will be published in the ACM Digital Library. At least one author of each accepted submission must register and participate in SPLC 2022 in order for the submission to be published. Submissions need to be sent using EasyChair: https://easychair.org/my/conference?conf=splc22
Artifact Evaluation

Authors of accepted research papers are invited to submit the artifacts associated with the paper for evaluation. To do so, they should submit a PDF via Easychair (select the Research Artifacts track). The PDF should contain a stable URL (or DOI) to the artifacts. The URL must contain the steps or general instructions to execute/analyze the artifact. Each artifact submission will be reviewed by at least two reviewers.

According to ACM’s “Result and Artifact Review and Badging” policy, an “artifact” is “a digital object that was either created by the authors to be used as part of the study or generated by the experiment itself [… which can include] software systems, scripts used to run experiments, input datasets, raw data collected in the experiment, or scripts used to analyze results.”

Accepted artifacts will receive one of the following badges on the first page of the paper, table of contents, and in the ACM Digital Library:

Artifacts Evaluated

• Functional: The artifacts are complete, well-documented and allow obtaining the same results as the paper.

• Reusable: As above, but the artifacts are of such a high quality that they can be reused as is on other data sets or for other purposes.

Each accepted research paper associated with an accepted artifact must provide a link to the artifact in the camera-ready version of the paper. The authors must ensure that the artifacts are available from a stable URL or DOI. Please note that these badges exclude proprietary data or tools.