arXiv cs.SE Software Engineering
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Reposted by arXiv cs.SE Software Engineering
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S\'andor P. Fekete, Phillip Keldenich, Dominik Krupke, Michael Perk: Efficient Heuristics and Exact Methods for Pairwise Interaction Sampling https://arxiv.org/abs/2510.05955 https://arxiv.org/pdf/2510.05955 https://arxiv.org/html/2510.05955
Reposted by arXiv cs.SE Software Engineering
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Ludwig Stage, Mirela Riveni, Raimundas Matulevi\v{c}ius, Dimka Karastoyanova: AdProv: A Method for Provenance of Process Adaptations https://arxiv.org/abs/2510.05936 https://arxiv.org/pdf/2510.05936 https://arxiv.org/html/2510.05936
Reposted by arXiv cs.SE Software Engineering
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Radivonchik, Kuzin, Chizhov, Shcheka, Firsov, Smirnov, Chernishev: Speeding up SQL subqueries via decoupling of non-correlated predicate (extended version) https://arxiv.org/abs/2510.05907 https://arxiv.org/pdf/2510.05907 https://arxiv.org/html/2510.05907
Reposted by arXiv cs.SE Software Engineering
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Jacopo Bufalino, Mario Di Francesco, Agathe Blaise, Stefano Secci: SBOMproof: Beyond Alleged SBOM Compliance for Supply Chain Security of Container Images https://arxiv.org/abs/2510.05798 https://arxiv.org/pdf/2510.05798 https://arxiv.org/html/2510.05798
Reposted by arXiv cs.SE Software Engineering
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Xin-Cheng Wen, Zirui Lin, Yijun Yang, Cuiyun Gao, Deheng Ye: Vul-R2: A Reasoning LLM for Automated Vulnerability Repair https://arxiv.org/abs/2510.05480 https://arxiv.org/pdf/2510.05480 https://arxiv.org/html/2510.05480
Reposted by arXiv cs.SE Software Engineering
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Mukul Singh, Somya Chatterjee, Arjun Radhakrishna, Sumit Gulwani: Do Code Models Suffer from the Dunning-Kruger Effect? https://arxiv.org/abs/2510.05457 https://arxiv.org/pdf/2510.05457 https://arxiv.org/html/2510.05457
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Griffin Pitts, Aum Pandya, Darsh Rank, Tirth Bhatt, Muntasir Hoq, Bita Akram: Automated Program Repair of Uncompilable Student Code https://arxiv.org/abs/2510.06187 https://arxiv.org/pdf/2510.06187 https://arxiv.org/html/2510.06187
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Elijah Kayode Adejumo, Brittany Johnson: Explaining Code Risk in OSS: Towards LLM-Generated Fault Prediction Interpretations https://arxiv.org/abs/2510.06104 https://arxiv.org/pdf/2510.06104 https://arxiv.org/html/2510.06104
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Daniel Otten, Trevor Stalnaker, Nathan Wintersgill, Oscar Chaparro, Denys Poshyvanyk: Prompting in Practice: Investigating Software Developers' Use of Generative AI Tools https://arxiv.org/abs/2510.06000 https://arxiv.org/pdf/2510.06000 https://arxiv.org/html/2510.06000
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Darja Smite, Franz Zieris, Lars-Ola Damm: A Wave of Resignations in the Aftermath of Remote Onboarding https://arxiv.org/abs/2510.05878 https://arxiv.org/pdf/2510.05878 https://arxiv.org/html/2510.05878
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Nikita Pavlichenko, et al.: Mellum: Production-Grade in-IDE Contextual Code Completion with Multi-File Project Understanding https://arxiv.org/abs/2510.05788 https://arxiv.org/pdf/2510.05788 https://arxiv.org/html/2510.05788
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Robin Kimmel, Judith Michael, Andreas Wortmann, Jingxi Zhang: Digital Twins for Software Engineering Processes https://arxiv.org/abs/2510.05768 https://arxiv.org/pdf/2510.05768 https://arxiv.org/html/2510.05768
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Eva Mart\'in del Pico, Josep Llu\'is Gelp\'i, Salvador Capella-Guti\'errez: The Software Observatory: aggregating and analysing software metadata for trend computation and FAIR assessment https://arxiv.org/abs/2510.05705 https://arxiv.org/pdf/2510.05705 https://arxiv.org/html/2510.05705
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Rintaro Kanaji, Brittany Reid, Yutaro Kashiwa, Raula Gaikovina Kula, Hajimu Iida: An Empirical Study of Security-Policy Related Issues in Open Source Projects https://arxiv.org/abs/2510.05604 https://arxiv.org/pdf/2510.05604 https://arxiv.org/html/2510.05604
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Goldman, Lin, Pasuksmit, Thongtanunam, Tantithamthavorn, Wang, Zhang, Behnaz, Jiang, Siers, Jiang, Buller, Jeong, Wu: What Types of Code Review Comments Do Developers Most Frequently Resolve? https://arxiv.org/abs/2510.05450 https://arxiv.org/pdf/2510.05450 https://arxiv.org/html/2510.05450
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Yiannis Charalambous, Claudionor N. Coelho Jr, Luis Lamb, Lucas C. Cordeiro: UnitTenX: Generating Tests for Legacy Packages with AI Agents Powered by Formal Verification https://arxiv.org/abs/2510.05441 https://arxiv.org/pdf/2510.05441 https://arxiv.org/html/2510.05441
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Felicity Anderson, Julien Sindt, Neil Chue Hong: Who Do You Think You Are? Creating RSE Personas from GitHub Interactions https://arxiv.org/abs/2510.05390 https://arxiv.org/pdf/2510.05390 https://arxiv.org/html/2510.05390
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Irtaza Sajid Qureshi (Jack), Zhen Ming (Jack), Jiang: Test Case Generation from Bug Reports via Large Language Models: A Cognitive Layered Evaluation Framework https://arxiv.org/abs/2510.05365 https://arxiv.org/pdf/2510.05365 https://arxiv.org/html/2510.05365
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Lesly Miculicich, Mihir Parmar, Hamid Palangi, Krishnamurthy Dj Dvijotham, Mirko Montanari, Tomas Pfister, Long T. Le: VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation https://arxiv.org/abs/2510.05156 https://arxiv.org/pdf/2510.05156 https://arxiv.org/html/2510.05156
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Yu Zhu: Adaptive Reinforcement Learning for Dynamic Configuration Allocation in Pre-Production Testing https://arxiv.org/abs/2510.05147 https://arxiv.org/pdf/2510.05147 https://arxiv.org/html/2510.05147
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[2025-10-08 Wed (UTC), 15 new articles found for csSE Software Engineering]
Reposted by arXiv cs.SE Software Engineering
Reposted by arXiv cs.SE Software Engineering
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Peshala Perera, Deshan Sumanathilaka: A Low-Resource Speech-Driven NLP Pipeline for Sinhala Dyslexia Assistance https://arxiv.org/abs/2510.04750 https://arxiv.org/pdf/2510.04750 https://arxiv.org/html/2510.04750
Reposted by arXiv cs.SE Software Engineering
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Tang, Meininger, Xu, Shi, Huang, McMillan, Li: NaturalEdit: Code Modification through Direct Interaction with Adaptive Natural Language Representation https://arxiv.org/abs/2510.04494 https://arxiv.org/pdf/2510.04494 https://arxiv.org/html/2510.04494