37th IEEE International Symposium on Software Reliability Engineering (ISSRE 2026): First Call for Papers (Research Track)

2 Jan 2026

      *** First Call for Papers (Research Track) ***

37th IEEE International Symposium on Software Reliability Engineering
(ISSRE 2026)

October 20-23, 2026, 5* St. Raphael Resort and Marina
Limassol, Cyprus

https://cyprusconferences.org/issre2026/<http://www.cs.ucy.ac.cy/~george/GPLists_2021/lm.php?tk=YWlyLWwJCQlhaXItbEBsaXN0c2Vydi5hb2lyLm9yZwkzN3RoIElFRUUgSW50ZXJuYXRpb25hbCBTeW1wb3NpdW0gb24gU29mdHdhcmUgUmVsaWFiaWxpdHkgRW5naW5lZXJpbmcgKElTU1JFIDIwMjYpOiBGaXJzdCBDYWxsIGZvciBQYXBlcnMgKFJlc2VhcmNoIFRyYWNrKQk0OTMJVmFyaWFiaWxpdHkJMTQ0CWNsaWNrCXllcwlubw==&url=https%3A%2F%2Fcyprusconferences.org%2Fissre2026%2F>

The International Symposium on Software Reliability Engineering (ISSRE) is the leading
conference on software reliability research and practice. ISSRE focuses on techniques and
tools for assessing, predicting, and improving the reliability, safety, security, and resilience
of software systems. As modern software increasingly integrates AI/ML components,
operates autonomously, and spans cloud-to-edge environments, ensuring reliable system
behavior is more critical than ever.

Topics of Interest

ISSRE 2026 invites high-quality contributions that advance the theory and practice of
software reliability across contemporary software-intensive systems, including systems
that incorporate AI/ML components. Topics of interest include, but are not limited to:

Foundations of Reliability and Dependability
• Principles, models, metrics, empirical methods, and theories of software reliability,
resilience, robustness, and safety
• Systematic approaches to fault prevention, fault removal, fault tolerance, and fault
forecasting in modern software systems
• Testing and debugging, formal methods, model checking, static/dynamic analysis,
verification, and runtime assurance

Reliability in AI-Driven and Autonomic Systems
• Reliability engineering for AI-enabled, autonomous, self-adaptive, and cyber-physical
systems
• Assurance, testing, verification, and certification of AI/ML components, including
foundation and generative models
• Reliability of AI-generated code: validation, verification, explainability, defect analysis,
and trustworthy automation of development tasks
• Impact of AI on software lifecycle processes (design, testing, evolution, operations, and
quality management)

AI Techniques for Reliability Engineering
• Machine learning for defect prediction, anomaly detection, debugging assistance, fault
localization, and test automation
• Learning-based approaches to self-healing, resilience management, predictive
maintenance, and reliability optimization
• Reliability governance in AI-driven DevOps pipelines, including transparency,
interpretability, and auditability

Software Reliability in Emerging System Domains
• Reliability assurance for cloud, edge, IoT, 5G/6G, cyber-physical, high-performance,
and network softwarization environments
• Dependability of open-source ecosystems, data-driven pipelines, model hubs, and
AI-assisted contributions
• Benchmarking, stress testing, workload modeling, and measurement frameworks for
large-scale and AI-based systems

Trustworthiness, Security, and Responsible Software Engineering
• Intersections of reliability with security, privacy, fairness, transparency, and regulatory
compliance
• Societal, ethical, and human impacts of pervasive AI-enabled software systems
• Responsible governance of AI-based systems, including lifecycle assurance, auditability,
and risk analysis

Human-Centered, Empirical, and Reproducible Reliability Research
• Field studies, experience reports, user studies, and human factors in reliability
engineering
• Public datasets, benchmark suites, reproducibility packages, and replication/negative-
result studies
• Tooling, automation, continuous reliability monitoring, observability, and operational
feedback loops

Research Track Paper Categories

The research track at ISSRE 2026 invites high-quality submissions of technical research
papers that describe original, unpublished results exploring new scientific ideas,
contribute new evidence to established research directions, or reflect on practical
experience. Specifically, ISSRE solicits submissions in three categories:

• Research (RES) papers
• Practical experience reports (PER)
• Tools and artefacts (TAR) papers

Papers will be assessed with criteria appropriate to each category. All the papers of the
three categories are regular and full papers, and will be published in the same ISSRE
proceedings.

RES Papers
RES papers (12 pages, including references) should describe a novel contribution to the
reliability of software systems. Novelty should be argued via concrete evidence and
appropriate positioning within the state of the art. RES papers are also expected to
explain the validation process and its limitations clearly.

PER Papers
PER papers (12 pages, including references) should provide an in-depth exposition of
practical experiences ideally performed by a collaboration of researchers and industry
practitioners. The key contribution of these papers should be lessons learned from
applying established research tools and methods to ISSRE topics, or new knowledge
acquired through empirical studies conducted using various research methodologies.
Negative results are welcome, e.g., discussing where or why current research cannot be
applied in an industrially relevant context.

TAR Papers
TAR papers (6 – 10 pages, including references) should describe a new tool or artefact.
Tool-focused TAR papers must present either a new tool or a novel and substantial
extension of an existing tool. They should include a description of (i) the theoretical
foundations, (ii) the design and implementation aspects, and (iii) experiments with
realistic case studies. Making the tool publicly available is strongly encouraged.
Artefact-focused TAR papers should cover (i) a working copy of the software and (ii)
experimental data sets. Dataset papers should introduce a new dataset that supports
experimentation, benchmarking, evaluation, or training in AI-driven software engineering.
Submissions should describe: (i) dataset motivation and scope, (ii) data collection and
processing methodology, (iii) dataset structure and statistics, and (iv) potential use cases.
Benchmark papers should present a new benchmark suite for evaluating tools, LLMs, or
algorithms. Submissions should include: (i) benchmark design principles, (ii) task
definitions and evaluation metrics, (iii) baseline results, and (iv) reproducibility package.

The ISSRE conference encourages authors of all three categories of research track papers
to follow the principles of transparency, reproducibility, and replicability. Authors are
encouraged to disclose data to increase reproducibility and replicability. Should the paper
be accepted, the authors will have the opportunity (and are encouraged to) submit
artifacts to the Artifact Evaluation (AE) track, to enhance the reproducibility and quality of
the research. By submitting your artifacts, you not only contribute to the progress of our
field but also stand a chance to earn badges that will be displayed on your papers in the
conference proceedings, showcasing the credibility and rigor of your work.

At least one author of each accepted paper must register as an author and present the
paper in person at the conference.

Best Research Paper Award

ISSRE is pleased to announce the IEEE Best Research Paper Award, awarded every year to
the best paper in the Research Track.

Special Journal Issue

Authors of accepted papers will be invited to submit an extended version of their work to
a special issue of the Empirical Software Engineering (EMSE) journal (under negotiation as
in previous editions of the conference). The Call for Papers will be available soon.

Review Process & Quality Assurance in ISSRE 2026 (New)