Historically, formal methods academic research and practical software development have had limited mutual interactions — except possibly in specialized domains such as safety-critical software. In recent times, the outlook has considerably improved: on the one hand, formal methods research has delivered more flexible techniques and tools that can support various aspects of the software development process — from user requirements elicitation, to design, implementation, verification and validation, as well as the creation of documentation. On the other hand, software engineering has developed a growing interest in rigorous techniques applied at scale.

The FormaliSE conference series promotes work at the intersection of the formal methods and software engineering communities, providing a venue to exchange ideas, experiences, techniques, and results. We believe more collaboration between these two communities can be mutually beneficial by fostering the creation of formal methods that are practically useful and by helping develop higher-quality software.

Originally a workshop event, since 2018 FormaliSE has been organized as a conference co-located with ICSE. The 13th edition of FormaliSE will also take place as a co-located conference of ICSE 2025.

Area of interest include:

• requirements formalization and formal specification;
• approaches, methods and tools for verification and validation;
• formal approaches to safety and security related issues;
• analysis of performance and other non-functional properties based on formal approaches;
• scalability of formal method applications
• integration of formal methods within the software development lifecycle (e.g., change -management, continuous integration, regression testing, and deployment)
• model-based engineering approaches;
• correctness-by-construction approaches for software and systems engineering;
• application of formal methods to specific domains, e.g., autonomous, cyber-physical, intelligent, and IoT systems;
• formal methods for AI-based systems (FM4AI), and AI applied in formal method approaches (AI4FM);
• formal methods in a certification context
• case studies developed/analyzed with formal approaches
• experience reports on the application of formal methods to real-world problems;
• guidelines to use formal methods in practice;
• usability of formal methods.

Accepted Papers

Call for Papers

We accept papers in three categories:

• Full research papers describing original research work and results. We encourage authors to include validation of their contributions by means of a case study or experiments. We also welcome research papers focusing on tools and tool development.
• Case study papers discussing a significant application that suggests general lessons learned and motivates further research, or empirically validates theoretical results (such as a technique’s scalability).
• Research ideas papers describing new ideas in preliminary form, in a way that can stimulate interesting discussions at the conference, and suggest future work.

All papers submitted to the FormaliSE 2025 conference must be written in English, must be unpublished original work, and must not be under review or submitted elsewhere at the time of submission. Submissions must comply with the FormaliSE’s lightweight double-anonymous review process (see below).

Full research papers and case study papers can take up to 10 pages including all text, figures, tables and appendices, but excluding references. Research ideas papers can take up to 4 pages, plus up to 1 additional page solely for references.

To avoid that authors waste time fitting their papers into the stated limit at the expense of presentation clarity, paper lengths slightly exceeding the stated limit will still be considered, provided that the reviewers find that the presentation is of high quality.

All submissions must be in PDF format and must conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines (i.e., title in 24pt font and full text in 10pt type). In LaTeX, use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf options. Note that IEEE format is being used this year, whereas last year it was ACM format, hence the appearance will differ from year to year.

To submit a paper to FormaliSE 2025 use the following HotCRP link.

Lightweight Double-Anonymous Review Process for Papers

As in recent editions, FormaliSE 2025 will use a lightweight double-anonymous process. Authors must omit their names and institutions from the title page, cite their own work in the third person, and omit acknowledgments that may reveal their identity or affiliation. The purpose is reducing chances of reviewer bias influenced by the authors’ identities. The double-anonymous process is, however, lightweight, which means that it should not pose a heavy burden for authors, nor should make a paper’s presentation weaker or more difficult to review. Also, advertising the paper as part of your usual research activities (for example, on your personal web-page, in a pre-print archive, by email, in talks or discussions with colleagues) is permitted without penalties.

PAPER SELECTION

Each paper will be reviewed by at least three program committee members that will judge its overall quality in terms of its soundness, significance, novelty, verifiability, and presentation clarity.

FormaliSE 2025 will adopt a lightweight response process: if all the reviewers of a given paper agree that a clarification from the authors regarding a specific question could move the paper from “borderline” to “accept”, the chairs will relay the reviewers’ questions to the authors by email, and then share their reply with the reviewers in HotCRP. The goal of lightweight responses is reducing the chance of random decisions on borderline papers. Hence, they will only be used for a minority of submissions; most papers will not require such an author response. Nevertheless, we would ask the corresponding authors of all submissions to make sure that they are available to answer questions by email upon request.

PUBLICATION

All accepted papers are published as part of the ICSE 2025 Proceedings in the ACM and IEEE Digital Libraries.

At least one author of each accepted paper is required to register for the conference and present the paper at the conference — physically or, if the circumstances do not allow so, virtually. Failure to register an author will result in a paper being removed from the proceedings.

Adversarial Perturbations and Self-Defenses for Large Language Models on Coding Task

Abstract: Large language models (LLMs) have demonstrated impressive capabilities for coding tasks including writing and reasoning about code. They improve upon previous neural network models of code that already demonstrated competitive results when performing tasks such as code summarization and identifying code vulnerabilities . However, it is known that these pre-LLM code models are vulnerable to adversarial examples, i.e. small syntactic perturbations that do not change the program’s semantics, such as the inclusion of “dead code” through false conditions, the addition of inconsequential print statements, or change in control flow, designed to “fool” the models. LLMs can also be vulnerable to the same adversarial perturbations. In this talk we discuss the effect of adversarial perturbations on coding tasks with LLMs and propose effective defenses against such adversaries. The coding tasks we’ll consider include both classification (e.g., use LLMs for summarization, vulnerability detection) and code generation (e.g., use LLMs for code completion, based on prompts plus code snippets).

Corina Pasareanu is an ACM Fellow and an IEEE ASE Fellow, working at NASA Ames. She is affiliated with KBR and Carnegie Mellon University's CyLab. Her research interests include model checking, symbolic execution, compositional verification, probabilistic software analysis, autonomy, and security. She is the recipient of several awards, including ETAPS Test of Time Award (2021), ASE Most Influential Paper Award (2018), ESEC/FSE Test of Time Award (2018), ISSTA Retrospective Impact Paper Award (2018), ACM Impact Paper Award (2010), and ICSE 2010 Most Influential Paper Award (2010).

TBA

Abstract: TBA

Krzysztof Czarnecki is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, with a cross-appointment to the School of Computer Science. He is the leader of the Waterloo Intelligent Systems Engineering Lab. His research focuses on generative software development. His expertise encompasses model-driven software engineering, including software product lines, variability modeling, consistency management, bi-directional transformations, and example-driven modeling. Throughout his career, Dr. Czarnecki has received several prestigious awards, including the Premier’s Research Excellence Award in 2004 and the British Computing Society’s Upper Canada Award for Outstanding Contributions to the IT Industry in 2008. In 2023, he was honored with a University Research Chair at the University of Waterloo.