Table of Contents

• Mining Workflows for Anomalous Data TransfersHuy Tu, George Papadimitriou 0002, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman, Tim Menzies. 1-12 [doi]
• PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from CodeEgor Spirin, Egor Bogomolov, Vladimir Kovalenko, Timofey Bryksin. 13-17 [doi]
• Comparative Study of Feature Reduction Techniques in Software Change PredictionRuchika Malhotra, Ritvik Kapoor, Deepti Aggarwal, Priya Garg. 18-28 [doi]
• Automatic Part-of-Speech Tagging for Security Vulnerability DescriptionsSofonias Yitagesu, Xiaowang Zhang, Zhiyong Feng 0002, Xiaohong Li 0001, Zhenchang Xing. 29-40 [doi]
• Identifying Critical Projects via PageRank and Truck FactorRolf-Helge Pfeiffer. 41-45 [doi]
• An Empirical Study of Developer Discussions on Low-Code Software Development ChallengesMd. Abdullah Al Alamin, Sanjay Malakar, Gias Uddin 0001, Sadia Afroz, Tameem Bin Haider, Anindya Iqbal. 46-57 [doi]
• Learning Off-By-One Mistakes: An Empirical StudyHendrig Sellik, Onno van Paridon, Georgios Gousios, Maurício Aniche. 58-67 [doi]
• The Secret Life of Hackathon Code Where does it come from and where does it go?Ahmed Imam, Tapajit Dey, Alexander Nolte, Audris Mockus, James D. Herbsleb. 68-79 [doi]
• gambit - An Open Source Name Disambiguation Tool for Version Control SystemsChristoph Gote, Christian Zingg. 80-84 [doi]
• Escaping the Time Pit: Pitfalls and Guidelines for Using Time-Based Git DataSamuel W. Flint, Jigyasa Chauhan, Robert Dyer 0001. 85-96 [doi]
• Attention-based model for predicting question relatedness on Stack OverflowJiayan Pei, Yimin Wu, Zishan Qin, Yao Cong, Jingtao Guan. 97-107 [doi]
• An Empirical Study on the Usage of BERT Models for Code CompletionMatteo Ciniselli, Nathan Cooper, Luca Pascarella, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota. 108-119 [doi]
• On Improving Deep Learning Trace Analysis with System Call ArgumentsQuentin Fournier, Daniel Aloise, Seyed Vahid Azhari, François Tetreault. 120-130 [doi]
• An Empirical Study of OSS-Fuzz BugsZhen Yu Ding, Claire Le Goues. 131-142 [doi]
• An Exploratory Study of Log Placement Recommendation in an Enterprise SystemJeanderson Cândido, Jan Haesen, Maurício Aniche, Arie van Deursen. 143-154 [doi]
• On the Naturalness and Localness of Software LogsSina Gholamian, Paul A. S. Ward. 155-166 [doi]
• Automatically Selecting Follow-up Questions for Deficient Bug ReportsMia Mohammad Imran, Agnieszka Ciborowska, Kostadin Damevski. 167-178 [doi]
• Architecture Smells and Pareto Principle: A Preliminary Empirical ExplorationAlexandra-Maria Chaniotaki, Tushar Sharma. 190-194 [doi]
• Technical Debt in the Peer-Review Documentation of R Packages: a rOpenSci Case StudyZadia Codabux, Melina C. Vidoni, Fatemeh H. Fard. 195-206 [doi]
• How Java Programmers Test Exceptional BehaviorDiego Marcilio, Carlo A. Furia. 207-218 [doi]
• A Replication Study on the Usability of Code Vocabulary in Predicting Flaky TestsGuillaume Haben, Sarra Habchi, Mike Papadakis, Maxime Cordy, Yves Le Traon. 219-229 [doi]
• Leveraging Models to Reduce Test Cases in Software RepositoriesGolnaz Gharachorlu, Nick Sumner. 230-241 [doi]
• Which contributions count? Analysis of attribution in open sourceJean-Gabriel Young, Amanda Casari, Katie McLaughlin, Milo Z. Trujillo, Laurent Hébert-Dufresne, James P. Bagrow. 242-253 [doi]
• On the Use of Dependabot Security Pull RequestsMahmoud Alfadel, Diego Elias Costa, Emad Shihab, Mouafak Mkhallalati. 254-265 [doi]
• S3M: Siamese Stack (Trace) Similarity MeasureAleksandr Khvorov, Roman Vasiliev, George A. Chernishev, Irving Muller Rodrigues, Dmitrij V. Koznov, Nikita Povarov. 266-270 [doi]
• Challenges in Developing Desktop Web Apps: a Study of Stack Overflow and GitHubGian Luca Scoccia, Patrizio Migliarini, Marco Autili. 271-282 [doi]
• Studying the Change Histories of Stack Overflow and GitHub SnippetsSaraj Singh Manes, Olga Baysal. 283-294 [doi]
• TNM: A Tool for Mining of Socio-Technical Data from Git RepositoriesNikolai Sviridov, Mikhail Evtikhiev, Vladimir Kovalenko. 295-299 [doi]
• Mining the ROS ecosystem for Green Architectural Tactics in Robotics and an Empirical EvaluationIvano Malavolta, Katerina Chinnappan, Stan Swanborn, Grace A. Lewis, Patricia Lago. 300-311 [doi]
• Mining API Interactions to Analyze Software Revisions for the Evolution of Energy ConsumptionAndreas Schuler, Gabriele Kotsis. 312-316 [doi]
• Googling for Software Development: What Developers Search For and What They FindAndré C. Hora. 317-328 [doi]
• Fast and Memory-Efficient Neural Code CompletionAlexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltiadis Allamanis. 329-340 [doi]
• Identifying Versions of Libraries used in Stack Overflow Code SnippetsAhmed Zerouali, Camilo Velázquez-Rodríguez, Coen De Roover. 341-345 [doi]
• Can I Solve It? Identifying APIs Required to Complete OSS TasksFabio Santos, Igor Wiese, Bianca Trinkenreich, Igor Steinmacher, Anita Sarma, Marco Aurélio Gerosa. 346-257 [doi]
• Data Balancing Improves Self-Admitted Technical Debt DetectionMurali Sridharan, Mika Mäntylä, Leevi Rantala, Maëlick Claes. 358-368 [doi]
• JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect PredictionChanathip Pornprasit, Chakkrit Tantithamthavorn. 369-379 [doi]
• Rollback Edit Inconsistencies in Developer ForumSaikat Mondal, Gias Uddin 0001, Chanchal K. Roy. 380-391 [doi]
• What Code Is Deliberately Excluded from Test Coverage and Why?André C. Hora. 392-402 [doi]
• Waiting around or job half-done? Sentiment in self-admitted technical debtGianmarco Fucci, Nathan Cassee, Fiorella Zampetti, Nicole Novielli, Alexander Serebrenik, Massimiliano Di Penta. 403-414 [doi]
• Mining DEV for social and technical insights about software developmentMaria Papoutsoglou, Johannes Wachs, Georgia M. Kapitsaki. 415-419 [doi]
• How Do Software Developers Use GitHub Actions to Automate Their Workflows?Timothy Kinsman, Mairieli Wessel, Marco Aurélio Gerosa, Christoph Treude. 420-431 [doi]
• Practitioners' Perceptions of the Goals and Visual Explanations of Defect Prediction ModelsJirayus Jiarpakdee, Chakkrit Tantithamthavorn, John C. Grundy. 432-443 [doi]
• Does Code Review Promote Conformance? A Study of OpenStack PatchesPanyawut Sri-Iesaranusorn, Raula Gaikovina Kula, Takashi Ishio. 444-448 [doi]
• Revisiting Dockerfiles in Open Source Software Over TimeKalvin Eng, Abram Hindle. 449-459 [doi]
• Characterising the Knowledge about Primitive Variables in Java Code CommentsMahfouth Alghamdi, Shinpei Hayashi, Takashi Kobayashi, Christoph Treude. 460-470 [doi]
• Predicting Design Impactful Changes in Modern Code Review: A Large-Scale Empirical StudyAnderson G. Uchôa, Caio Barbosa, Daniel Coutinho, Willian Nalepa Oizumi, Wesley K. G. Assunção, Silvia Regina Vergilio, Juliana Alves Pereira, Anderson Oliveira, Alessandro F. Garcia 0001. 471-482 [doi]
• Mining Energy-Related Practices in Robotics SoftwareMichel Albonico, Ivano Malavolta, Gustavo Pinto 0001, Emitza Guzman, Katerina Chinnappan, Patricia Lago. 483-494 [doi]
• On the Rise and Fall of Simple Stupid Bugs: a Life-Cycle Analysis of SStuBsBalázs Mosolygó, Norbert Vándor, Gábor Antal, Péter Hegedüs. 495-499 [doi]
• How Effective is Continuous Integration in Indicating Single-Statement Bugs?Jasmine Latendresse, Rabe Abdalkareem, Diego Elias Costa, Emad Shihab. 500-504 [doi]
• Applying CodeBERT for Automated Program Repair of Java Simple BugsEhsan Mashhadi, Hadi Hemmati. 505-509 [doi]
• A large-scale study on human-cloned changes for automated program repairFernanda Madeiral, Thomas Durieux. 510-514 [doi]
• Mea culpa: How developers fix their own simple bugs differently from other developersWenhan Zhu, Michael W. Godfrey. 515-519 [doi]
• PySStuBs: Characterizing Single-Statement Bugs in Popular Open-Source Python ProjectsArthur V. Kamienski, Luisa Palechor, Cor-Paul Bezemer, Abram Hindle. 520-524 [doi]
• On the Distribution of "Simple Stupid Bugs" in Unit Test Files: An Exploratory StudyAnthony Peruma, Christian D. Newman. 525-529 [doi]
• On the Effectiveness of Deep Vulnerability Detectors to Simple Stupid Bug DetectionJiayi Hua, Haoyu Wang 0001. 530-534 [doi]
• AndroidCompass: A Dataset of Android Compatibility Checks in Code RepositoriesSebastian Nielebock 0001, Paul Blockhaus, Jacob Krüger, Frank Ortmeier. 535-539 [doi]
• Denchmark: A Bug Benchmark of Deep Learning-related SoftwareMisoo Kim, YoungKyoung Kim, Eunseok Lee. 540-544 [doi]
• Duets: A Dataset of Reproducible Pairs of Java Library-ClientsThomas Durieux, César Soto-Valero, Benoit Baudry. 545-549 [doi]
• KGTorrent: A Dataset of Python Jupyter Notebooks from KaggleLuigi Quaranta, Fabio Calefato, Filippo Lanubile. 550-554 [doi]
• A Traceability Dataset for Open Source SystemsMouna Hammoudi, Christoph Mayr-Dorn, Atif Mashkoor, Alexander Egyed. 555-559 [doi]
• Sampling Projects in GitHub for MSR StudiesOzren Dabic, Emad Aghajani, Gabriele Bavota. 560-564 [doi]
• The Wonderless Dataset for Serverless ComputingNafise Eskandani, Guido Salvaneschi. 565-569 [doi]
• AndroCT: Ten Years of App Call Traces in AndroidWen Li, Xiaoqin Fu, Haipeng Cai. 570-574 [doi]
• Search4Code: Code Search Intent Classification Using Weak SupervisionNikitha Rao, Chetan Bansal, Joe Guan. 575-579 [doi]
• Andromeda: A Dataset of Ansible Galaxy Roles and Their EvolutionRuben Opdebeeck, Ahmed Zerouali, Coen De Roover. 580-584 [doi]
• ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type InferenceAmir M. Mir, Evaldas Latoskinas, Georgios Gousios. 585-589 [doi]
• QScored: A Large Dataset of Code Smells and Quality MetricsTushar Sharma, Marouane Kessentini. 590-594 [doi]
• Apache Software Foundation Incubator Project Sustainability DatasetLikang Yin, Zhiyuan Zhang, Qi Xuan, Vladimir Filkov. 595-599 [doi]
• Andror2: A Dataset of Manually-Reproduced Bug Reports for Android appsTyler Wendland, Jingyang Sun, Junayed Mahmud, S. M. Hasan Mansur, Steven Huang, Kevin Moran, Julia Rubin, Mattia Fazzini. 600-604 [doi]
• GE526: A Dataset of Open-Source Game EnginesDheeraj Vagavolu, Vartika Agrahari, Sridhar Chimalakonda, Akhila Sri Manasa Venigalla. 605-609 [doi]
• EqBench: A Dataset of Equivalent and Non-equivalent Program PairsSahar Badihi, Yi Li 0008, Julia Rubin. 610-614 [doi]
• Tracking Hackathon Code Creation and ReuseAhmed Imam, Tapajit Dey. 615-617 [doi]
• Building the Collaboration Graph of Open-Source Software EcosystemElena Lyulina, Mahmoud Jahanshahi. 618-620 [doi]
• Tracing Vulnerable Code LineageDavid Reid, Kalvin Eng, Chris Bogart, Adam Tutko. 621-623 [doi]
• An Exploratory Study of Project Activity Changepoints in Open Source Software EvolutionJames Walden, Noah Burgin, Kuljit Kaur. 624-626 [doi]
• The Diversity-Innovation Paradox in Open-Source SoftwareMengchen Sam Yong, Lavinia Paganini, Huilian Sophie Qiu, José Bayoán Santiago Calderón. 627-629 [doi]