[fg-arc] CFP Neuro-Symbolic Software Engineering Workshop - ICSE 2025

Anne Koziolek (KASTEL) koziolek at kit.edu
Thu Oct 3 15:59:14 CEST 2024


As I know that many of you are as excited about the opportunities that 
AI may bring to the field of software architecture, allow me to share 
this CfP for a workshop @ ICSE with you. It focusses on neuro-symbolic 
(a.k.a. intersymbolic) SE, which aims at the question of how to best 
combine classical, symbolic SE techniques with AI.

Maybe a position paper on the topic could already be put together based 
on discussions at the Fachgruppen-Jahrestagung "Architekturen" in 
Paderborn (24. und 25. Oktober)? Best, Anne Koziolek

*****

NSE 2025

1st International Workshop on Neuro-Symbolic Software Engineering

Co-located with 47th International Conference on Software Engineering 
ICSE, to be held April 27-May 3 2025 in Ottawa.

Workshop day TBA

Website: _https://conf.researchr.org/home/icse-2025/nse-2025 
<https://conf.researchr.org/home/icse-2025/nse-2025>_

Deadline: November 11th, 2024

*****

*Call for Papers*

Software engineering has a success history of evolving symbolic 
techniques, e.g., formal methods and programming languages, to solve 
increasingly challenging problems like providing safety and performance 
guarantees for autonomous intelligent systems fulfilling 
mission-critical functions. With the availability of machine learning 
(ML) techniques, software engineering expanded its set of problems to 
how learning from data enables applications from code summarization & 
generation to automatic program repair & formal verification. The 
integration of symbolic and ML techniques has opened new novel 
methodological challenges that go beyond applying ML to build software 
(ML4SE) or applying software engineering to build ML (SE4ML). These 
challenges fall under the umbrella of Neuro-Symbolic methods and 
comprise problems of “how to reason about learning” and “how to learn 
about reasoning”.

The NSE workshop aims to discuss these problems in the context of 
software engineering tasks that have been transformed by the adoption of 
machine learning techniques. We invite insights on merging symbolic and 
ML techniques across the software development life-cycle, its 
activities, tasks, and tools. We welcome case studies, conceptual 
innovative approach descriptions, empirical research, and more formal or 
theoretical considerations.

NSE seeks submissions describing novel research, emerging ideas, and 
work-in-progress describing original and unpublished results in the 
field of Neuro-symbolic methods for software engineering.

*Topics <https://conf.researchr.org/home/icse-2025/nse-2025#topics>*

    * Neuro-Symbolic methods in automated software engineering tools,
      e.g., code & test generation, bug fixing, code summarization, code
      review, etc.

    * Neuro-Symbolic agents to support collaboration and decision-making
      in software teams.

    * Neuro-Symbolic methods in validation and verification tools.

    * Neuro-Symbolic methods for designing safety-mission-critical systems.

    * Neuro-Symbolic methods for extracting and maintaining knowledge
      graphs for software engineering.

    * Methods for reasoning about learning from software data.

    * Methods for learning while reasoning about software, e.g.,
      automatically & adaptively determining decision thresholds and
      magnitude of actions for a desired effect of a software tool &
      technique.

    * Methods for applying prior symbolic or probabilistic knowledge to
      new or improved software tools & methods.

*_Important Dates 
<https://conf.researchr.org/home/icse-2025/nse-2025#important-dates>_*

Paper submissions: *November 11th*, 2024.

Paper notifications: December 1st, 2024..

Camera-ready versions: February 5th, 2025.

Workshop: TBA

CFP: _https://conf.researchr.org/home/icse-2025/nse-2025#Call-for-Papers 
<https://conf.researchr.org/home/icse-2025/nse-2025#Call-for-Papers>_

Our goal is to collect experiences, challenges, and solutions involved 
in combining symbolic methods and machine learning to tackle new and 
traditional challenges of software engineering tasks from requirements 
to analysis & design, coding, testing, and maintenance & evolution. We 
welcome contributions in any of the following formats:

    * Full research papers

    * Case studies

    * Proofs-of-concept

    * New ideas and emerging results

    * Evaluation of tools

    * Controlled experiment reports

Best regards!

Christian Medeiros Adriano (christian.adriano at hpi.de 
<mailto:christian.adriano at hpi.de>)

Sona Ghahremani

Daiki Kimura

Ruben Ruiz-Torrubiano

NSE 2025 Co-organizers

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