Product line engineering remains a central strategy in 2024, utilizing economies of scale, cost savings on shared assets across product families, and rapid adoption of innovative technologies in diverse product and service portfolios.
Many organizations have gained significant benefits by applying product line practices, achieving a high level of customizability and quality while reducing the time-to-market and costs associated with engineering and maintaining software-intensive products. However, the implementation of product line engineering still faces challenges and compromises that can hinder its success and widespread adoption. The need for investment and strategic planning in reuse seems conflicting, especially considering the rapidly evolving technological landscapes.
The need for adaptability and flexibility, together with emerging technologies such as artificial intelligence, digital twins, blockchain, and cyber-security technologies, present new challenges as a result of worldwide crises, including the still-present effects of the COVID-19 pandemic, and supply chain interruptions caused by geopolitical conflicts. Yet, these challenges also provide unique opportunities.
In this evolving context, particularly with the rapid advancements in AI and large language models (LLMs), we are calling for contributions from both industry and academia on the practical applications of product line engineering to software and systems, including the integration and implications of AI and LLMs. We are particularly interested in contributions that detail the specifics, challenges, successes, and evaluations at various stages of technology readiness levels. This includes insights into how AI and LLMs are influencing product line engineering strategies and practices. Contributions from industries employing modular platform concepts to manage reuse in hardware and mechatronic systems, including – but not limited to – industrial equipment, automotive, appliances, semiconductors, etc., are highly encouraged. The incorporation of AI and LLM technologies in these sectors, and their impact on product development and lifecycle management, are of particular interest. These insights will provide valuable perspectives on state-of-the-art practices and future directions in product line engineering.
Topics
We solicit papers on the following topics (but not limited to):
- Adopting or Migrating to Product Line Engineering
- Scoping of Product/Solution Portfolios and Assets
- Architecture, Design, and Implementation of Product Lines
- Process Aspects (e.g., DevOps and Agile Processes)
- Strategic Reuse in the Face of Increasing Volatility and Uncertainty
- Variability Management Across All Lifecycle Stages
- Model-Driven and Model-Based Engineering
- Organizational and Business Aspects (e.g., Business Ecosystems)
- Continuous Integration and Deployment (evolving product lines)
- Artificial Intelligence (Including Deep and Machine Learning Technologies) in SPLs
- Digital twins in product line engineering
- Quantum computing applications in product lines
- High-Performance Computing (HPC) and Exascale computing in product lines
- Case studies on successful implementations of modular platforms
- Non-functional property considerations in product line development
- Managing guidance and governance in product line engineering
- Product Line Testing, Verification, and Validation
- Version and Configuration Management
- Disruptive Innovations and Their Effects on Product Lines
- Strategic Reuse Attempts That Failed
Submission Guidelines
The industry track is open to submissions in two categories:
- Full papers: Reporting experience from product line applications, preferably from but not limited to an industry domain. The papers in this category must provide sufficient context of the problems identified or addressed, describe clear requirements and/or experiences in solving them, provide an assessment of benefits and drawbacks or other lessons learned, and explain why the contribution is innovative or valuable for others.
- Short papers: Describing early returns on new product line and software ecosystem applications and projects, or other shorter topics of interest.
The page limit is 10 pages of content (+ 2 pages for references) for full papers and up to 5 pages of content (+ 2 pages for references) for short papers. Each submission will be carefully reviewed by at least three members of the industry track program committee.
Submission link
Submissions need to be sent using EasyChair:
https://easychair.org/conferences/?conf=splc2024 (Industry Track)
Paper Formatting Instructions
The SPLC proceedings will be published in the ACM Digital Library.
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 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]{acmart}
\acmConference[SPLC’24]{28th ACM International Systems and Software Product Lines Conference}{ September 2-6, 2024}{Luxembourg}
Submission Policies
Papers submitted for consideration to SPLC must not have been already published elsewhere and must not be under review or submitted for review elsewhere during the reviewing period. Specifically, authors are required to adhere to the ACM Policy and Procedures on Plagiarism and the ACM Policy on Prior Publication and Simultaneous Submissions.
By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all ACM Publications Policies, including ACM’s new Publications Policy on Research Involving Human Participants and Subjects. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.
Please ensure that you and your co-authors obtain an ORCID ID, so you can complete the publishing process for your accepted paper. ACM has been involved in ORCID from the start, and we have recently made a commitment to collect ORCID IDs from all of the published authors. ACM is committed to improving author discoverability, ensuring proper attribution, and contributing to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.
Important Dates (AoE time)
- Abstract submission:
April 11, 2024April 18th, 2024 (23h59, AoE) - Paper submission:
April 18, 2024April 25th, 2024 (23h59, AoE) - Notification:
May 30, 2024June 3, 2024 - Camera-ready paper:
June 20, 2024July 1st, 2024 (23h59, AoE) - Conference: September 2nd to 6th, 2024
Chairs
Iris Groher Johannes Kepler University Linz, Austria  Deepak Dhungana IMC University of Applied Sciences, Krems Austria
Program Committee
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