Table of Contents

• Which bugs are missed in code reviews: An empirical study on SmartSHARK datasetFatemeh Khoshnoud, Ali Rezaei Nasab, Zahra Toudeji, Ashkan Sami. 1-5 [doi]
• SLNET: A Redistributable Corpus of 3rd-party Simulink ModelsSohil Lal Shrestha, Shafiul Azam Chowdhury, Christoph Csallner. 1-5 [doi]
• An Empirical Evaluation of GitHub Copilot's Code SuggestionsNhan Nguyen, Sarah Nadi. 1-5 [doi]
• BotHunter: An Approach to Detect Software Bots in GitHubAhmad Abdellatif, Mairieli Santos Wessel, Igor Steinmacher, Marco Aurélio Gerosa, Emad Shihab. 6-17 [doi]
• Comments on Comments: Where Code Review and Documentation MeetNikitha Rao, Jason Tsay, Martin Hirzel, Vincent J. Hellendoorn. 18-22 [doi]
• Does This Apply to Me? An Empirical Study of Technical Context in Stack OverflowAkalanka Galappaththi, Sarah Nadi, Christoph Treude. 23-34 [doi]
• Towards Reliable Agile Iterative Planning via Predicting Documentation Changes of Work ItemsJirat Pasuksmit, Patanamon Thongtanunam, Shanika Karunasekera. 35-47 [doi]
• Beyond Duplicates: Towards Understanding and Predicting Link Types in Issue Tracking SystemsClara Marie Lüders, Abir Bouraffa, Walid Maalej. 48-60 [doi]
• Smelly Variables in Ansible Infrastructure Code: Detection, Prevalence, and LifetimeRuben Opdebeeck, Ahmed Zerouali, Coen De Roover. 61-72 [doi]
• An Alternative Issue Tracking Dataset of Public Jira RepositoriesLloyd Montgomery, Clara Marie Lüders, Walid Maalej. 73-77 [doi]
• Real-World Clone-Detection in GoQinyun Wu, Huan Song, Ping Yang. 78-79 [doi]
• Geographic Diversity in Public Code Contributions: An Exploratory Large-Scale Study Over 50 YearsDavide Rossi, Stefano Zacchiroli. 80-85 [doi]
• Operationalizing Threats to MSR Studies by Simulation-Based TestingJohannes Härtel, Ralf Lämmel. 86-97 [doi]
• The General Index of Software Engineering PapersZeinab Abou Khalil, Stefano Zacchiroli. 98-102 [doi]
• Challenges and Future Research Direction for Microtask Programming in IndustryMasanari Kondo, Shinobu Saito, Yukako Iimura, Eunjong Choi, Osamu Mizuno, Yasutaka Kamei, Naoyasu Ubayashi. 103-104 [doi]
• Starting the InnerSource Journey: Key Goals and Metrics to Measure CollaborationDaniel Izquierdo-Cortazar, Jesús Alonso-Gutiérrez, Alberto Pérez García-Plaza, Gregorio Robles, Jesús M. González-Barahona. 105-106 [doi]
• An Exploratory Study on Refactoring Documentation in Issues HandlingEman Abdullah AlOmar, Anthony Peruma, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni 0001. 107-111 [doi]
• Between JIRA and GitHub: ASFBot and its Influence on Human Comments in Issue TrackersAmbarish Moharil, Dmitrii Orlov, Samar Jameel, Tristan Trouwen, Nathan Cassee, Alexander Serebrenik. 112-116 [doi]
• Is Refactoring Always a Good Egg? Exploring the Interconnection Between Bugs and RefactoringsAmirreza Bagheri, Péter Hegedüs. 117-121 [doi]
• On the Co-Occurrence of Refactoring of Test and Source CodeNicholas Alexandre Nagy, Rabe Abdalkareem. 122-126 [doi]
• Refactoring Debt: Myth or Reality? An Exploratory Study on the Relationship Between Technical Debt and RefactoringAnthony Peruma, Eman Abdullah AlOmar, Christian D. Newman, Mohamed Wiem Mkaouer, Ali Ouni 0001. 127-131 [doi]
• Studying the Impact of Continuous Delivery Adoption on Bug-Fixing Time in Apache's Open-Source ProjectsCarlos Diego Andrade de Almeida, Diego N. Feijó, Lincoln S. Rocha. 132-136 [doi]
• Empirical Standards for Repository MiningPreetha Chatterjee, Tushar Sharma, Paul Ralph. 142-143 [doi]
• Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance IssueRui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies. 144-155 [doi]
• How to Improve Deep Learning for Software Analytics (a case study with code smell detection)Rahul Yedida, Tim Menzies. 156-166 [doi]
• To What Extent do Deep Learning-based Code Recommenders Generate Predictions by Cloning Code from the Training Set?Matteo Ciniselli, Luca Pascarella, Gabriele Bavota. 167-178 [doi]
• Searching for High-Fidelity Builds Using Active LearningHarshitha Menon, Konstantinos Parasyris, Tom Scogland, Todd Gamblin. 179-190 [doi]
• ApacheJIT: A Large Dataset for Just-In-Time Defect PredictionHossein Keshavarz, Meiyappan Nagappan. 191-195 [doi]
• ReCover: a Curated Dataset for Regression Testing ResearchFrancesco Altiero, Anna Corazza, Sergio Di Martino, Adriano Peron, Luigi L. L. Starace. 196-200 [doi]
• Mining the Ethereum Blockchain Platform: Best Practices and Pitfalls (MSR 2022 Tutorial)Gustavo A. Oliva. 201-202 [doi]
• Mining the Usage of Reactive Programming APIs: A Study on GitHub and Stack OverflowCarlos Zimmerle, Kiev Gama, Fernando Castor, José Murilo Mota Filho. 203-214 [doi]
• Painting the Landscape of Automotive Software in GitHubSangeeth Kochanthara, Yanja Dajsuren, Loek Cleophas, Mark van den Brand. 215-226 [doi]
• DISCO: A Dataset of Discord Chat Conversations for Software Engineering ResearchKeerthana Muthu Subash, Lakshmi Prasanna Kumar, Sri Lakshmi Vadlamani, Preetha Chatterjee, Olga Baysal. 227-231 [doi]
• Inspect4py: A Knowledge Extraction Framework for Python Code RepositoriesRosa Filgueira, Daniel Garijo. 232-236 [doi]
• SoCCMiner: A Source Code-Comments and Comment-Context MinerMurali Sridharan, Mika Mäntylä, Maëlick Claes, Leevi Rantala. 242-246 [doi]
• SOSum: A Dataset of Stack Overflow Post SummariesBonan Kou, Yifeng Di, Muhao Chen, Tianyi Zhang. 247-251 [doi]
• An Empirical Study on Maintainable Method Size in JavaShaiful Alam Chowdhury, Gias Uddin 0001, Reid Holmes. 252-264 [doi]
• Characterizing High-Quality Test Methods: A First Empirical StudyVictor Veloso, André C. Hora. 265-269 [doi]
• CLIP meets GamePhysics: Towards bug identification in gameplay videos using zero-shot transfer learningMohammad Reza Taesiri, Finlay Macklon, Cor-Paul Bezemer. 270-281 [doi]
• Complex Python Features in the WildYi Yang, Ana L. Milanova, Martin Hirzel. 282-293 [doi]
• ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type InferenceKevin Jesse, Premkumar T. Devanbu. 294-298 [doi]
• METHODS2TEST: A dataset of focal methods mapped to test casesMichele Tufano, Shao Kun Deng, Neel Sundaresan, Alexey Svyatkovskiy. 299-303 [doi]
• npm-filter: Automating the mining of dynamic information from npm packagesEllen Arteca, Alexi Turcotte. 304-308 [doi]
• How heated is it? Understanding GitHub locked issuesIsabella Ferreira, Bram Adams, Jinghui Cheng. 309-320 [doi]
• On the Violation of Honesty in Mobile Apps: Automated Detection and CategoriesHumphrey O. Obie, Idowu Ilekura, Hung Du, Mojtaba Shahin, John C. Grundy, Li Li 0029, Jon Whittle 0001, Burak Turhan. 321-332 [doi]
• Exploring Apache Incubator Project Trajectories with APEXAnirudh Ramchandran, Likang Yin, Vladimir Filkov. 333-337 [doi]
• The OCEAN mailing list data set: Network analysis spanning mailing lists and code repositoriesMelanie Warrick, Samuel F. Rosenblatt, Jean-Gabriel Young, Amanda Casari, Laurent Hébert-Dufresne, James P. Bagrow. 338-342 [doi]
• The Unexplored Treasure Trove of Phabricator Code ReviewsGunnar Kudrjavets, Nachiappan Nagappan, Ayushi Rastogi. 343-347 [doi]
• The Unsolvable Problem or the Unheard Answer? A Dataset of 24, 669 Open-Source Software Conference TalksKimberly Truong, Courtney Miller, Bogdan Vasilescu, Christian Kästner. 348-352 [doi]
• A Large-Scale Comparison of Python Code in Jupyter Notebooks and ScriptsKonstantin Grotov, Sergey Titov, Vladimir Sotnikov, Yaroslav Golubev, Timofey Bryksin. 353-364 [doi]
• An Empirical Study on the Survival Rate of GitHub ProjectsAdem Ait, Javier Luis Cánovas Izquierdo, Jordi Cabot. 365-375 [doi]
• Do Customized Android Frameworks Keep Pace with Android?Pei Liu, Mattia Fazzini, John C. Grundy, Li Li 0029. 376-387 [doi]
• DaSEA - A Dataset for Software Ecosystem AnalysisPetya Buchkova, Joakim Hey Hinnerskov, Kasper Olsen, Rolf-Helge Pfeiffer. 388-392 [doi]
• Dataset: Dependency Networks of Open Source Libraries Available Through CocoaPods, Carthage and Swift PMKristiina Rahkema, Dietmar Pfahl. 393-397 [doi]
• Lupa: A Framework for Large Scale Analysis of the Programming Language UsageAnna Vlasova, Maria Tigina, Ilya Vlasov, Anastasiia Birillo, Yaroslav Golubev, Timofey Bryksin. 398-402 [doi]
• GitDelver Enterprise Dataset (GDED): An Industrial Closed-source Dataset for Socio-Technical ResearchNicolas Riquet, Xavier Devroey, Benoît Vanderose. 403-407 [doi]
• SniP: An Efficient Stack Tracing Framework for Multi-threaded ProgramsK. P. Arun 0002, Saurabh Kumar 0007, Debadatta Mishra, Biswabandan Panda. 408-412 [doi]
• Tooling for Time- and Space-efficient git Repository MiningFabian Heseding, Willy Scheibel, Jürgen Döllner. 413-417 [doi]
• TSSB-3M: Mining single statement bugs at massive scaleCedric Richter, Heike Wehrheim. 418-422 [doi]
• LibDB: An Effective and Efficient Framework for Detecting Third-Party Libraries in BinariesWei Tang, Yanlin Wang, Hongyu Zhang 0002, Shi Han, Ping Luo, Dongmei Zhang 0001. 423-434 [doi]
• Noisy Label Learning for Security DefectsRoland Croft, Muhammad Ali Babar, Huaming Chen. 435-447 [doi]
• WeakSATD: Detecting Weak Self-admitted Technical DebtBarbara Russo, Matteo Camilli, Moritz Mock. 448-453 [doi]
• AndroOBFS: Time-tagged Obfuscated Android Malware Dataset with Family InformationSaurabh Kumar 0007, Debadatta Mishra, Biswabandan Panda, Sandeep Kumar Shukla. 454-458 [doi]
• TriggerZoo: A Dataset of Android Applications Automatically Infected with Logic BombsJordan Samhi, Tegawendé F. Bissyandé, Jacques Klein. 459-463 [doi]
• Vul4J: A Dataset of Reproducible Java Vulnerabilities Geared Towards the Study of Program Repair TechniquesQuang-Cuong Bui, Riccardo Scandariato, Nicolás E. Díaz Ferreyra. 464-468 [doi]
• Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical StudyTatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh 0001, Anita Raja. 469-481 [doi]
• Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding SchemesJingzhi Gong, Tao Chen. 482-494 [doi]
• Multimodal Recommendation of Messenger ChannelsEkaterina Koshchenko, Egor Klimov, Vladimir Kovalenko. 495-505 [doi]
• On the Naturalness of Fuzzer-Generated CodeRajeswari Hita Kambhamettu, John Billos, Tomi Oluwaseun-Apo, Benjamin Gafford, Rohan Padhye, Vincent J. Hellendoorn. 506-510 [doi]
• Senatus - A Fast and Accurate Code-to-Code Recommendation EngineFran Silavong, Sean J. Moran, Antonios Georgiadis, Rohan Saphal, Robert Otter. 511-523 [doi]
• GraphCode2Vec: Generic Code Embedding via Lexical and Program Dependence AnalysesWei Ma, Mengjie Zhao, Ezekiel O. Soremekun, Qiang Hu, Jie M. Zhang, Mike Papadakis, Maxime Cordy, Xiaofei Xie, Yves Le Traon. 524-536 [doi]
• Do Small Code Changes Merge Faster? A Multi-Language Empirical InvestigationGunnar Kudrjavets, Nachiappan Nagappan, Ayushi Rastogi. 537-548 [doi]
• FaST: A linear time stack trace alignment heuristic for crash report deduplicationIrving Muller Rodrigues, Daniel Aloise, Eraldo Rezende Fernandes. 549-560 [doi]
• Is Open Source Eating the World's Software? Measuring the Proportion of Open Source in Proprietary Software Using Java BinariesJulius Musseau, John Speed Meyers, George P. Sieniawski, C. Albert Thompson, Daniel German. 561-565 [doi]
• Methods for Stabilizing Models Across Large Samples of Projects (with case studies on Predicting Defect and Project Health)Suvodeep Majumder, Tianpei Xia, Rahul Krishna, Tim Menzies. 566-578 [doi]
• Mining Code Review Data to Understand Waiting Times Between Acceptance and Merging: An Empirical AnalysisGunnar Kudrjavets, Aditya Kumar, Nachiappan Nagappan, Ayushi Rastogi. 579-590 [doi]
• TwinDroid: A Dataset of Android app System call traces and Trace Generation PipelineAsma Razagallah, Raphaël Khoury, Jean-Baptiste Poulet. 591-595 [doi]
• LineVD: Statement-level Vulnerability Detection using Graph Neural NetworksDavid Hin, Andrey Kan, Huaming Chen, Muhammad Ali Babar. 596-607 [doi]
• LineVul: A Transformer-based Line-Level Vulnerability PredictionMichael Fu, Chakkrit Tantithamthavorn. 608-620 [doi]
• On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment ModelsTriet Huynh Minh Le, Muhammad Ali Babar. 621-633 [doi]
• ECench: An Energy Bug Benchmark of Ethereum Client SoftwareJinyoung Kim, Misoo Kim, Eunseok Lee. 634-638 [doi]
• Microsoft CloudMine: Data Mining for the Executive Order on Improving the Nation's CybersecurityKim Herzig, Luke Ghostling, Maximilian Grothusmann, Sascha Just, Nora Huang, Alan Klimowski, Yashasvini Ramkumar, Myles McLeroy, Kivanç Muslu, Hitesh Sajnani, Varsha Vadaga. 639 [doi]
• Evaluating the effectiveness of local explanation methods on source code-based defect prediction modelsYuxiang Gao, Yi Zhu, Qiao Yu. 640-645 [doi]
• Problems and Solutions in Applying Continuous Integration and Delivery to 20 Open-Source Cyber-Physical SystemsFiorella Zampetti, Vittoria Nardone, Massimiliano Di Penta. 646-657 [doi]
• To Type or Not to Type? A Systematic Comparison of the Software Quality of JavaScript and TypeScript Applications on GitHubJustus Bogner, Manuel Merkel. 658-669 [doi]
• Using Bandit Algorithms for Selecting Feature Reduction Techniques in Software Defect PredictionMasateru Tsunoda, Akito Monden, Koji Toda, Amjed Tahir, Kwabena Ebo Bennin, Keitaro Nakasai, Masataka Nagura, Kenichi Matsumoto. 670-681 [doi]
• Constructing Dataset of Functionally Equivalent Java Methods Using Automated Test Generation TechniquesYoshiki Higo, Shinsuke Matsumoto, Shinji Kusumoto, Kazuya Yasuda. 682-686 [doi]
• Extracting Corrective Actions from Code RepositoriesYegor Bugayenko, Kirill Daniakin, Mirko Farina, Firas Jolha, Artem V. Kruglov, Giancarlo Succi, Witold Pedrycz. 687-688 [doi]
• Code Review Practices for Refactoring Changes: An Empirical Study on OpenStackEman Abdullah AlOmar, Moataz Chouchen, Mohamed Wiem Mkaouer, Ali Ouni 0001. 689-701 [doi]
• A Time Series-Based Dataset of Open-Source Software EvolutionBruno Luan de Sousa, Mariza A. S. Bigonha, Kecia A. M. Ferreira, Glaura C. Franco. 702-706 [doi]
• A Versatile Dataset of Agile Open Source Software ProjectsVali Tawosi, Afnan A. Al-Subaihin, Rebecca Moussa, Federica Sarro. 707-711 [doi]
• FixJS: A Dataset of Bug-fixing JavaScript CommitsViktor Csuvik, László Vidács. 712-716 [doi]
• LAGOON: An Analysis Tool for Open Source CommunitiesSourya Dey, Walt Woods. 717-721 [doi]
• Automatically Prioritizing and Assigning Tasks from Code Repositories in Puzzle Driven DevelopmentYegor Bugayenko, Ayomide Bakare, Arina Cheverda, Mirko Farina, Artem V. Kruglov, Yaroslav Plaksin, Giancarlo Succi, Witold Pedrycz. 722-723 [doi]
• Software Bots in Software Engineering: Benefits and ChallengesMairieli Santos Wessel, Marco Aurélio Gerosa, Emad Shihab. 724-725 [doi]
• Bot Detection in GitHub RepositoriesNatarajan Chidambaram, Pooya Rostami Mazrae. 726-728 [doi]
• GitRank: A Framework to Rank GitHub RepositoriesNiranjan Hasabnis. 729-731 [doi]
• Maintenance and Evolution: GrimoireLab GraalW. Meijer, D. Visscher, E. De Haan, M. Schröder, L. Visscher, Andrea Capiluppi, I. Botez. 732-734 [doi]
• OpenSSL 3.0.0: An exploratory case studyJames Walden. 735-737 [doi]
• Quid Pro Quo: An Exploration of Reciprocity in Code ReviewCarlos Gavidia-Calderon, DongGyun Han, Amel Bennaceur. 738-740 [doi]
• Replicating Data Pipelines with GrimoireLabKalvin Eng, Hareem Sahar. 741-743 [doi]
• A Deep Study of the Effects and Fixes of Server-Side Request Races in Web ApplicationsZhengyi Qiu, Shudi Shao, Qi Zhao 0003, Hassan Ali Khan, Xinning Hui, Guoliang Jin. 744-756 [doi]
• A Large-scale Dataset of (Open Source) License Text VariantsStefano Zacchiroli. 757-761 [doi]
• Detecting Privacy-Sensitive Code Changes with Language ModelingGökalp Demirci, Vijayaraghavan Murali, Imad Ahmad, Rajeev Rao, Gareth Ari Aye. 761-762 [doi]
• SECOM: Towards a convention for security commit messagesSofia Reis, Rui Abreu 0001, Hakan Erdogmus, Corina S. Pasareanu. 764-765 [doi]
• Varangian: A Git Bot for Augmented Static AnalysisSaurabh Pujar, Yunhui Zheng, Luca Buratti, Burn L. Lewis, Alessandro Morari, Jim Laredo, Kevin Postlethwait, Christoph Görn. 766-767 [doi]