ASE Workshop Events 2026
41st IEEE/ACM International Conference on Automated Software Engineering (ASE Events 2026)
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1st International Workshop on Automated Techniques for Integrity and Quality in Software-Engineering Research (ATIQSER 2026), October 12–16, 2026, Munich, Germany

ATIQSER 2026 – Preliminary Table of Contents

Contents - Abstracts - Authors

1st International Workshop on Automated Techniques for Integrity and Quality in Software-Engineering Research (ATIQSER 2026)

Frontmatter

Title Page

Article: asews26atiqserforeword-fm000-p (type: Frontmatter) doi:
Welcome from the Chairs
As powerful tools increasingly streamline how software engineering (SE) research is conducted and reported, submission volumes at top-tier SE venues are surging. To ensure this growth does not compromise research quality, scalable and reliable automated techniques are essential to support peer review and publishing practices. These range from traditional methods—such as validating bibliography integrity against public databases (e.g., the hallucinator tool)—to AI-assisted review support (as used at AAAI) and administrative automation (e.g., TPMS for paper bidding and assignment).
ATIQSER provides a dedicated platform for researchers developing, evaluating, or utilizing these techniques.
Article: asews26atiqserforeword-fm001-p (type: Frontmatter) doi:
ATIQSER 2026 Organization
ATIQSER 2026 Organization The First International Workshop on Automated Techniques for Integrity and Quality in Software-Engineering Research (ATIQSER) Organizers • Jürgen Cito, TU Wien, Austria • Ben Hermann, University of Stuttgart, Germany Program Committee • Doehyun Baek, CISPA Helmholtz Center for Information Security, Germany • Jonathan Bell, Northeastern University, United States • Michael Hilton, Carnegie Mellon University, United States • Anne Koziolek, Karlsruhe Institute of Technology, Germany • Jacob Krüger, Eindhoven University of Technology, Netherlands
Article: asews26atiqserforeword-fm002-p (type: Frontmatter) doi:

Papers

doi-checker: A Tool for Validating References of Research Papers
Dirk Beyer and Marian Lingsch-Rosenfeld
(LMU Munich, Germany)
The bibliography of a research paper links its claims to prior work, but reference lists frequently contain digital object identifiers (DOIs) that are missing, invalid, or—most dangerously—resolvable yet pointing to a completely different publication. The last case is a threat to academic integrity and a hallmark of hallucinated ref- erences produced by AI-assisted writing. To improve upon this situation we present DOIchecker, a tool that extracts the refer- ences of a paper, resolves their metadata against the Crossref and DataCite registries, and reports for each reference whether its DOI is missing, invalid, or inconsistent with the cited work. In addi- tion, DOIchecker also checks the metadata of each reference for consistency with the listed authors. We evaluate DOIchecker on all the available open access proceedings of six major conferences (CAV, TACAS, POPL, PLDI, FSE, and ISSTA) between 2020 and 2026 covering the three page formats common in computer science: LNCS, ACM double column, and ACM single column. Across the 192 909 references of these 3 888 papers, the share that prints a DOI rises from 24.7 % in 2020 to 58.2 % in 2026. Of the DOIs that are printed, 0.82 % do not resolve, and for 6.43 % the registered meta- data disagrees with the cited entry. Setting aside a single volume whose references are extracted poorly, we find no evidence that such disagreements concentrate in recent years.
Publisher's Version Published Artifact Artifacts Available Article: asews26atiqsermain-p1-p (type: Full Paper) doi:10.1145/3844135.3845864
Software Open Reproduction Package for ATIQSER 2026 Proceedings "doi-checker: A Tool for Validating References of Research Papers" (doi:10.5281/zenodo.22678552): This artifact is the reproduction package for the paper “doi-checker: A Tool for Validating Bibliographies of Research Papers”, accepted at ATIQSER 2026, co-located with ASE 2026. The paper presents doi-checker, which extracts the references from a paper PDF and verifies the DOIs they print against Crossref and ...
ATIBA: Grounded Integrity and Quality Checking for Research Papers
Veli Karakaya, Semih Çağlar, Yusuf Yiğit Korkmaz, and Eray Tüzün
(Bilkent University, Türkiye)
Checking a manuscript's reference integrity, its compliance with a target venue's specific submission rules, and its adherence to community reporting standards is manual, repetitive, and different for every venue so in practice it is done inconsistently or skipped. We present ATIBA, a tool that runs five grounded integrity and quality checks on a manuscript: a reference-integrity check that verifies each citation against bibliographic sources and flags retracted or unfindable references; a venue/track compliance check that derives submission criteria directly from a venue's own call-for-papers page and evaluates the manuscript against them, each verdict anchored to a verbatim quote from that page; an empirical-standards compliance check against the ACM SIGSOFT Empirical Standards, with a hallucination defence that discards any evidence quote it cannot locate verbatim in the manuscript; a multi-mode AI review (venue-specific, formal, and page-anchored annotation) powered by GPT-5.4 through Azure OpenAI; and a citation-suggestion feature that proposes candidate references for a manuscript and verifies each against bibliographic sources before it is shown to the user. All five checks are designed around the same principle: an LLM is only trusted to judge, never to invent the evidence it judges against. We evaluated ATIBA through a moderated user study with 13 non-author participants. Agreement across the six survey items ranged from 69% to 92%, with a mean of 85%, providing initial evidence of positive perceived usefulness across the evaluated workflows. These findings establish perceived usefulness; objective accuracy remains to be measured.
Publisher's Version Article: asews26atiqsermain-p2-p (type: Full Paper) doi:10.1145/3844135.3845865
RefVerifier: Semi-automated Reference Claim Verification for Scientific Manuscripts
Stefania Mocan, Florian Angermeir, and Mark Kreitz
(TU Munich, Germany; fortiss, Germany; Blekinge Institute of Technology, Sweden; University of the Bundeswehr Munich, Germany)
As software engineering research submission counts surge, peer reviewers face severe time constraints, making systematic verification of citation-supported claims prohibitively expensive. Consequently, unsubstantiated claims and semantic drift can propagate undetected across scientific literature. Existing approaches such as fact-checking and retrieval-augmented generation tools operate on open-domain web data or evaluate claims in isolation without processing complete manuscripts. To address this gap, we present RefVerifier, a semi-automated, citation-bounded reference verification prototype designed to support in academic peer review. RefVerifier extracts citation-bearing sentences from manuscripts, checks bibliography metadata against scholarly databases, resolves references to full-text open-access PDFs, localizes relevant evidence passages, and generates verdicts with natural language explanations. Evaluating RefVerifier on public benchmarks shows claim detection at an F1 score of 0.990, open-access resolution of 57.6% of references, and evidence localization with a hit rate of 98% on abstracts and 68% on complete cited papers. In an end-to-end test with eight manuscripts, RefVerifier achieves a verdict accuracy of 71%. By automating document retrieval and evidence localization while preserving reviewer oversight, RefVerifier provides first indicators for the feasibility of semi-automated integrity checks in scholarly publishing.
Publisher's Version Article: asews26atiqsermain-p3-p (type: Full Paper) doi:10.1145/3844135.3845866

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