Abstract is missing.
- Scaling Genetic Improvement and Automated Program RepairMark Harman. 1-7 [doi]
- Language Models Can Prioritize Patches for Practical Program PatchingSungmin Kang, Shin Yoo. 8-15 [doi]
- Revisiting Object Similarity-based Patch Ranking in Automated Program Repair: An Extensive StudyAli Ghanbari 0001. 16-23 [doi]
- Figra: Evaluating a larger search space for Cardumen in Automatic Program RepairAlcides Fonseca, Máximo Oliveira. 24-30 [doi]
- Be Realistic: Automated Program Repair is a Combination of Undecidable ProblemsAmirfarhad Nilizadeh, Gary T. Leavens. 31-32 [doi]
- What Can Program Repair Learn From Code Review?Madeline Endres, Pemma Reiter, Stephanie Forrest, Westley Weimer. 33-37 [doi]
- Framing Program Repair as Code CompletionFrancisco Ribeiro, Rui Abreu 0001, João Saraiva. 38-45 [doi]
- Some Automatically Generated Patches are More Likely to be Correct than Others: An Analysis of Defects4J Patch FeaturesGareth Bennett, Tracy Hall, David Bowes. 46-52 [doi]
- Enhancing Spectrum Based Fault localization Via Emphasizing Its Formulas With Importance WeightQusay Idrees Sarhan. 53-60 [doi]
- Towards JavaScript program repair with Generative Pre-trained Transformer (GPT-2)Márk Lajkó, Viktor Csuvik, László Vidács. 61-68 [doi]
- Can OpenAI's Codex Fix Bugs?: An evaluation on QuixBugsJulian Aron Prenner, Hlib Babii, Romain Robbes. 69-75 [doi]