Table of Contents

• 50K-C: a dataset of compilable, and compiled, Java projectsPedro Martins 0001, Rohan Achar, Cristina V. Lopes. 1-5 [doi]
• Jbench: a dataset of data races for concurrency testingJian Gao, Xin Yang, Yu Jiang, Han Liu, Weiliang Ying, Xian Zhang. 6-9 [doi]
• Bugs.jar: a large-scale, diverse dataset of real-world Java bugsRipon K. Saha, Yingjun Lyu, Wing Lam, Hiroaki Yoshida, Mukul R. Prasad. 10-13 [doi]
• A gold standard for emotion annotation in stack overflowNicole Novielli, Fabio Calefato, Filippo Lanubile. 14-17 [doi]
• VulinOSS: a dataset of security vulnerabilities in open-source systemsAntonios Gkortzis, Dimitris Mitropoulos, Diomidis Spinellis. 18-21 [doi]
• A dataset of duplicate pull-requests in githubYue Yu, Zhixing Li, Gang Yin, Tao Wang, Huaimin Wang. 22-25 [doi]
• Structured information on state and evolution of dockerfiles on githubGerald Schermann, Sali Zumberi, Jürgen Cito. 26-29 [doi]
• A graph-based dataset of commit history of real-world Android appsFranz-Xaver Geiger, Ivano Malavolta, Luca Pascarella, Fabio Palomba, Dario Di Nucci, Alberto Bacchelli. 30-33 [doi]
• Public git archive: a big code dataset for allVadim Markovtsev, Waren Long. 34-37 [doi]
• Word embeddings for the software engineering domainVasiliki Efstathiou, Christos Chatzilenas, Diomidis Spinellis. 38-41 [doi]
• npm-miner: an infrastructure for measuring the quality of the npm registryKyriakos C. Chatzidimitriou, Michail D. Papamichail, Themistoklis G. Diamantopoulos, Michail Tsapanos, Andreas L. Symeonidis. 42-45 [doi]
• CROP: linking code reviews to source code changesMatheus Paixão, Jens Krinke, DongGyun Han, Mark Harman. 46-49 [doi]
• Developer interaction traces backed by IDE screen recordings from think aloud sessionsAiko Yamashita, Fábio Petrillo, Foutse Khomh, Yann-Gaël Guéhéneuc. 50-53 [doi]
• A multi-level dataset of linux kernel patchworkYulin Xu, Minghui Zhou. 54-57 [doi]
• Documented unix facilities over 48 yearsDiomidis Spinellis. 58-61 [doi]
• Enriched event streams: a general dataset for empirical studies on in-IDE activities of software developersSebastian Proksch, Sven Amann, Sarah Nadi. 62-65 [doi]
• Comprehension effort and programming activities: related? or not related?Akond Rahman. 66-69 [doi]
• The hidden cost of code completion: understanding the impact of the recommendation-list length on its efficiencyXianhao Jin, Francisco Servant. 70-73 [doi]
• Empirical study on the relationship between developer's working habits and efficiencyAriel Rodríguez, Fumiya Tanaka, Yasutaka Kamei. 74-77 [doi]
• Mining and extraction of personal software process measures through IDE interaction logsAlireza Joonbakhsh, Ashkan Sami. 78-81 [doi]
• Predicting developers' IDE commands with machine learningTyson Bulmer, Lloyd Montgomery, Daniela E. Damian. 82-85 [doi]
• Do software engineers use autocompletion features differently than other developers?Rahul Amlekar, Andrés Felipe Rincón Gamboa, Keheliya Gallaba, Shane McIntosh. 86-89 [doi]
• Who's this?: developer identification using IDE event dataJohn Wilkie, Ziad Al Halabi, Alperen Karaoglu, Jiafeng Liao, George Ndungu, Chaiyong Ragkhitwetsagul, Matheus Paixão, Jens Krinke. 90-93 [doi]
• Detecting and characterizing developer behavior following opportunistic reuse of code snippets from the webAgnieszka Ciborowska, Nicholas A. Kraft, Kostadin Damevski. 94-97 [doi]
• Revisiting "programmers' build errors" in the visual studio context: a replication study using IDE interaction tracesNoam Rabbani, Michael S. Harvey, Sadnan Saquif, Keheliya Gallaba, Shane McIntosh. 98-101 [doi]
• Common statement kind changes to inform automatic program repairMauricio Soto, Claire Le Goues. 102-105 [doi]
• Studying developer build issues and debugger usage via timeline analysis in visual studio IDEChristopher Bellman, Ahmad Seet, Olga Baysal. 106-109 [doi]
• Detection and analysis of behavioral T-patterns in debugging activitiesCésar Soto-Valero, Johann Bourcier, Benoit Baudry. 110-113 [doi]
• A study on the use of IDE features for debuggingAfsoon Afzal, Claire Le Goues. 114-117 [doi]
• Mining the mind, minding the mine: grand challenges in comprehension and miningAndrew J. Ko. 118 [doi]
• An evaluation of open-source software microbenchmark suites for continuous performance assessmentChristoph Laaber, Philipp Leitner. 119-130 [doi]
• Studying the impact of adopting continuous integration on the delivery time of pull requestsJoão Helis Bernardo, Daniel Alencar da Costa, Uirá Kulesza. 131-141 [doi]
• What did really change with the new release of the app?Paolo Calciati, Konstantin Kuznetsov, Xue Bai, Alessandra Gorla. 142-152 [doi]
• CLEVER: combining code metrics with clone detection for just-in-time fault prevention and resolution in large industrial projectsMathieu Nayrolles, Abdelwahab Hamou-Lhadj. 153-164 [doi]
• I'm leaving you, Travis: a continuous integration breakup storyDavid Gray Widder, Michael Hilton, Christian Kästner, Bogdan Vasilescu. 165-169 [doi]
• An empirical evaluation of OSGi dependencies best practices in the eclipse IDELina Ochoa, Thomas Degueule, Jurgen J. Vinju. 170-180 [doi]
• On the impact of security vulnerabilities in the npm package dependency networkAlexandre Decan, Tom Mens, Eleni Constantinou. 181-191 [doi]
• Feature location using crowd-based screencastsParisa Moslehi, Bram Adams, Juergen Rilling. 192-202 [doi]
• Profiling call changes via motif miningBarbara Russo. 203-214 [doi]
• Toward predicting architectural significance of implementation issuesArman Shahbazian, Daye Nam, Nenad Medvidovic. 215-219 [doi]
• The Android update problem: an empirical studyMehran Mahmoudi, Sarah Nadi. 220-230 [doi]
• Why are Android apps removed from Google Play?: a large-scale empirical studyHaoyu Wang, Hao Li, Li Li, Yao Guo 0001, Guoai Xu. 231-242 [doi]
• Anatomy of functionality deletion: an exploratory study on mobile appsMaleknaz Nayebi, Konstantin Kuznetsov, Paul Chen, Andreas Zeller, Guenther Ruhe. 243-253 [doi]
• Characterising deprecated Android APIsLi Li 0029, Jun Gao, Tegawendé F. Bissyandé, Lei Ma, Xin Xia 0001, Jacques Klein. 254-264 [doi]
• Leveraging historical versions of Android apps for efficient and precise taint analysisHaipeng Cai, John Jenkins. 265-269 [doi]
• Understanding the usage, impact, and adoption of non-OSI approved licensesRômulo Manciola Meloca, Gustavo Pinto 0001, Leonardo Baiser, Marco Mattos, Ivanilton Polato, Igor Scaliante Wiese, Daniel M. Germán. 270-280 [doi]
• Prevalence of confusing code in software projects: atoms of confusion in the wildDan Gopstein, Hongwei Henry Zhou, Phyllis G. Frankl, Justin Cappos. 281-291 [doi]
• How swift developers handle errorsNathan Cassee, Gustavo Pinto 0001, Fernando Castor, Alexander Serebrenik. 292-302 [doi]
• What are your programming language's energy-delay implications?Stefanos Georgiou, Maria Kechagia, Panos Louridas, Diomidis Spinellis. 303-313 [doi]
• "Automatically assessing code understandability" reanalyzed: combined metrics matterAsher Trockman, Keenen Cates, Mark Mozina, Tuan Nguyen, Christian Kästner, Bogdan Vasilescu. 314-318 [doi]
• SOTorrent: reconstructing and analyzing the evolution of stack overflow postsSebastian Baltes, Lorik Dumani, Christoph Treude, Stephan Diehl 0001. 319-330 [doi]
• A design structure matrix approach for measuring co-change-modularity of software productsRobert Benkoczi, Daya Ram Gaur, Shahadat Hossain, Muhammad A. Khan. 331-335 [doi]
• A study on inappropriately partitioned commits: how much and what kinds of IP commits in Java projects?Ryo Arima, Yoshiki Higo, Shinji Kusumoto. 336-340 [doi]
• Data-driven search-based software engineeringVivek Nair, Amritanshu Agrawal, Jianfeng Chen, Wei Fu 0002, George Mathew, Tim Menzies, Leandro L. Minku, Markus Wagner 0007, Zhe Yu. 341-352 [doi]
• The open-closed principle of modern machine learning frameworksHoussem Ben Braiek, Foutse Khomh, Bram Adams. 353-363 [doi]
• A benchmark study on sentiment analysis for software engineering researchNicole Novielli, Daniela Girardi, Filippo Lanubile. 364-375 [doi]
• A deep learning approach to identifying source code in images and videoJordan Ott, Abigail Atchison, Paul Harnack, Adrienne Bergh, Erik Linstead. 376-386 [doi]
• Natural language or not (NLON): a package for software engineering text analysis pipelineMika V. Mäntylä, Fabio Calefato, Maëlick Claes. 387-391 [doi]
• How is video game development different from software development in open source?Luca Pascarella, Fabio Palomba, Massimiliano Di Penta, Alberto Bacchelli. 392-402 [doi]
• Which contributions predict whether developers are accepted into github teamsJustin Middleton, Emerson R. Murphy-Hill, Demetrius Green, Adam W. Meade, Roger Mayer, David White, Steve McDonald. 403-413 [doi]
• Automatic classification of software artifacts in open-source applicationsYuzhan Ma, Sarah Fakhoury, Michael Christensen, Venera Arnaoudova, Waleed Zogaan, Mehdi Mirakhorli. 414-425 [doi]
• Large-scale analysis of the co-commit patterns of the active developers in github's top repositoriesEldan Cohen, Mariano P. Consens. 426-436 [doi]
• Towards automatically identifying paid open source developersMaëlick Claes, Mika Mäntylä, Miikka Kuutila, Umar Farooq. 437-441 [doi]
• Analyzing requirements and traceability information to improve bug localizationMichael Rath 0002, David Lo 0001, Patrick Mäder. 442-453 [doi]
• Towards extracting web API specifications from documentationJinqiu Yang, Erik Wittern, Annie T. T. Ying, Julian Dolby, Lin Tan. 454-464 [doi]
• Evaluating how developers use general-purpose web-search for code retrievalMd Masudur Rahman, Jed Barson, Sydney Paul, Joshua Kayan, Federico Andres Lois, Sebastian Fernandez Quezada, Christopher Parnin, Kathryn T. Stolee, Baishakhi Ray. 465-475 [doi]
• Learning to mine aligned code and natural language pairs from stack overflowPengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig. 476-486 [doi]
• A search system for mathematical expressions on software binariesRidhi Jain, Sai Prathik, Venkatesh Vinayakarao, Rahul Purandare. 487-491 [doi]
• Imprecisions diagnostic in source code deltasGuillermo De la Torre, Romain Robbes, Alexandre Bergel. 492-502 [doi]
• Exploring the use of automated API migrating techniques in practice: an experience report on AndroidMaxime Lamothe, Weiyi Shang. 503-514 [doi]
• The patch-flow method for measuring inner source collaborationMaximilian Capraro, Michael Dorner, Dirk Riehle. 515-525 [doi]
• Was self-admitted technical debt removal a real removal?: an in-depth perspectiveFiorella Zampetti, Alexander Serebrenik, Massimiliano Di Penta. 526-536 [doi]
• Restmule: enabling resilient clients for remote APIsBeatriz A. Sanchez, Konstantinos Barmpis, Patrick Neubauer, Richard F. Paige, Dimitrios S. Kolovos. 537-541 [doi]
• Deep learning similarities from different representations of source codeMichele Tufano, Cody Watson, Gabriele Bavota, Massimiliano Di Penta, Martin White, Denys Poshyvanyk. 542-553 [doi]
• 500+ times faster than deep learning: a case study exploring faster methods for text mining stackoverflowSuvodeep Majumder, Nikhila Balaji, Katie Brey, Wei Fu 0002, Tim Menzies. 554-563 [doi]
• Studying the relationship between exception handling practices and post-release defectsGuilherme B. de Pádua, Weiyi Shang. 564-575 [doi]
• Analyzing conflict predictors in open-source Java projectsPaola R. G. Accioly, Paulo Borba, Léuson Silva, Guilherme Cavalcanti. 576-586 [doi]
• Bayesian hierarchical modelling for tailoring metric thresholdsNeil A. Ernst. 587-591 [doi]