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Venue Distribution

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This page provides the extended venue-level distribution associated with the survey Fuzzing AI Systems: Foundations, Techniques, and Open Challenges.

The analysis is based on 125 primary studies identified within the January 2015–February 2026 search window.

Overview

The selected studies appear across software engineering, software testing, software reliability, systems, security, programming languages, artificial intelligence, and preprint venues.

The distribution is concentrated in major software engineering and testing venues, showing that fuzzing AI systems is strongly connected to established research communities in software quality, reliability, and automated testing.

Conference and workshop publications support rapid dissemination of new techniques and tools, while journals and transactions provide longer-form empirical studies and extended evaluations.

Detailed Venue Distribution

The complete venue-level distribution is presented below. Each paper identifier (PID) links to the corresponding entry in the Primary Studies catalogue, which provides the full title, authors, publication year, venue, BibTeX key, and DOI or publication link.

Conference, Proceedings, and Preprint Venues — 87 studies
Venue # Studies Primary studies
ISSTA 13 P005, P015, P017, P019, P021, P023, P026, P028, P032, P041, P045, P113, P169
ICSE 13 P002, P009, P010, P013, P016, P020, P029, P030, P034, P035, P038, P058, P164
arXiv 10 P077, P080, P082, P100, P111, P114, P152, P154, P158, P197
ASE 10 P014, P025, P031, P036, P039, P049, P060, P079, P122, P178
QRS / QRS Companion 7 P091, P147, P193, P096, P148, P167, P200
FSE 6 P006, P008, P033, P042, P044, P050
ISSRE 3 P051, P069, P133
OOPSLA 3 P046, P090, P099
CSCWD 2 P127, P162
APLAS 1 P089
APSEC 1 P153
ASENS 1 P116
ASPLOS 1 P001
CCS 1 P066
CODASPY 1 P043
DAC 1 P018
DSA 1 P136
DSC 1 P104
ICIST 1 P170
ICPADS 1 P125
ICRSA 1 P024
ICSME 1 P081
IJCNN 1 P202
NaNA 1 P146
PACMSE 1 P083
SANER 1 P182
SMC 1 P103
TrustCom 1 P145
WWW 1 P003
Overall 87
Journal and Transaction Venues — 38 studies
Venue # Studies Primary studies
TSE 8 P061, P068, P078, P088, P095, P143, P144, P156
TOSEM 8 P086, P087, P106, P119, P120, P137, P157, P160
IST 4 P004, P007, P012, P027
JSS 4 P011, P076, P165, P198
TR 2 P142, P180
Applied Intelligence 1 P201
Computers & Security 1 P208
Cybersecurity 1 P101
IET Software 1 P130
IJIS 1 P174
Information Sciences 1 P172
JMS 1 P121
JNCA 1 P022
Neurocomputing 1 P040
PLOS ONE 1 P140
TNNLS 1 P176
TNSE 1 P204
Overall 38

Note: QRS and QRS Companion are merged into a single venue group because they belong to the same conference family. arXiv is grouped with conference/proceedings/preprint venues because it represents preprint dissemination. OOPSLA and PACMSE are listed with conference/proceedings venues following the normalized venue grouping used in the dataset. Venue abbreviations follow the normalized names used in the survey dataset.

Interpretation

Three broad patterns emerge from the venue distribution.

Strong Presence in Software Engineering and Testing

ISSTA, ICSE, ASE, FSE, TSE, and TOSEM account for a substantial portion of the selected studies.

This concentration reflects the close relationship between AI-system fuzzing and research on:

Contributions from Both Conferences and Journals

The corpus includes major conferences as well as archival journals and transactions.

Conference venues support fast dissemination of emerging techniques, benchmarks, and tools, while journals and transactions provide space for extended methodology, broader evaluation, and more detailed empirical analysis.

Role of Preprints

arXiv appears among the most frequent publication venues.

Preprints contribute to rapid dissemination, particularly in emerging areas such as:

The 2026 venue distribution should be interpreted as partial because the survey search window ends in February 2026.

Broader Venue Coverage

Beyond the most frequent venues, the corpus also includes publications from research communities concerned with:

This broader distribution reflects the cross-layer nature of AI-system fuzzing, which spans learned models, frameworks and libraries, compiler backends, runtime infrastructure, and integrated AI-enabled systems.

Main Observation

The venue landscape indicates that fuzzing AI systems is primarily rooted in software engineering, software testing, and reliability research while also drawing contributions from systems, security, programming languages, and AI communities.

The combination of conference, journal, transaction, and preprint venues shows that the area supports both rapid methodological development and longer-form empirical investigation.