Table of Contents

• SCOR: source code retrieval with semantics and orderShayan A. Akbar, Avinash C. Kak. 1-12 [doi]
• PathMiner: a library for mining of path-based representations of codeVladimir Kovalenko, Egor Bogomolov, Timofey Bryksin, Alberto Bacchelli. 13-17 [doi]
• Import2vec learning embeddings for software librariesBart Theeten, Frederik Vandeputte, Tom Van Cutsem. 18-28 [doi]
• Semantic source code models using identifier embeddingsVasiliki Efstathiou, Diomidis Spinellis. 29-33 [doi]
• DeepJIT: an end-to-end deep learning framework for just-in-time defect predictionThong Hoang, Hoa Khanh Dam, Yasutaka Kamei, David Lo 0001, Naoyasu Ubayashi. 34-45 [doi]
• Lessons learned from using a deep tree-based model for software defect prediction in practiceHoa Khanh Dam, Trang Pham, Shien Wee Ng, Truyen Tran 0001, John C. Grundy, Aditya Ghose, Taeksu Kim, Chul-Joo Kim. 46-57 [doi]
• Empirical study in using version histories for change risk classificationMax Kiehn, Xiangyi Pan, Fatih Camci. 58-62 [doi]
• Snoring: a noise in defect prediction datasetsAalok Ahluwalia, Davide Falessi, Massimiliano Di Penta. 63-67 [doi]
• Exploring word embedding techniques to improve sentiment analysis of software engineering textsEeshita Biswas, K. Vijay-Shanker, Lori L. Pollock. 68-78 [doi]
• Cleaning StackOverflow for machine translationMusfiqur Rahman, Peter C. Rigby, Dharani Palani, Tien N. Nguyen. 79-83 [doi]
• Predicting good configurations for GitHub and stack overflow topic modelsChristoph Treude, Markus Wagner 0007. 84-95 [doi]
• A dataset of parametric cryptographic misusesAnna-Katharina Wickert, Michael Reif, Michael Eichberg, Anam Dodhy, Mira Mezini. 96-100 [doi]
• Does UML modeling associate with lower defect proneness?: a preliminary empirical investigationAdithya Raghuraman, Truong Ho-Quang, Michel R. V. Chaudron, Alexander Serebrenik, Bogdan Vasilescu. 101-104 [doi]
• STRAIT: a tool for automated software reliability growth analysisStanislav Chren, Radoslav Micko, Barbora Buhnova, Bruno Rossi 0001. 105-110 [doi]
• A data set of program invariants and error pathsDirk Beyer. 111-115 [doi]
• Test coverage in python programsHongyu Zhai, Casey Casalnuovo, Premkumar T. Devanbu. 116-120 [doi]
• On the effectiveness of manual and automatic unit test generation: ten years laterDomenico Serra, Giovanni Grano, Fabio Palomba, Filomena Ferrucci, Harald C. Gall, Alberto Bacchelli. 121-125 [doi]
• Time present and time past: analyzing the evolution of JavaScript code in the wildDimitris Mitropoulos, Panos Louridas, Vitalis Salis, Diomidis Spinellis. 126-137 [doi]
• The software heritage graph dataset: public software development under one roofAntoine Pietri, Diomidis Spinellis, Stefano Zacchiroli. 138-142 [doi]
• World of code: an infrastructure for mining the universe of open source VCS dataYuxing Ma, Chris Bogart, Sadika Amreen, Russell Zaretzki, Audris Mockus. 143-154 [doi]
• Crossflow: a framework for distributed mining of software repositoriesDimitris S. Kolovos, Patrick Neubauer, Konstantinos Barmpis, Nicholas Matragkas, Richard F. Paige. 155-159 [doi]
• Recommending energy-efficient Java collectionsWellington Oliveira, Renato Oliveira, Fernando Castor, Benito Fernandes, Gustavo Pinto 0001. 160-170 [doi]
• GreenHub farmer: real-world data for Android energy miningHugo Matalonga, Bruno Cabral, Fernando Castor, Marco Couto 0001, Rui Pereira, Simão Melo de Sousa, João Paulo Fernandes. 171-175 [doi]
• GreenSource: a large-scale collection of Android code, tests and energy metricsRui Rua, Marco Couto 0001, João Saraiva. 176-180 [doi]
• Striking gold in software repositories?: an econometric study of cryptocurrencies on GitHubAsher Trockman, Rijnard van Tonder, Bogdan Vasilescu. 181-185 [doi]
• A panel data set of cryptocurrency development activity on GitHubRijnard van Tonder, Asher Trockman, Claire Le Goues. 186-190 [doi]
• SOTorrent: studying the origin, evolution, and usage of stack overflow code snippetsSebastian Baltes, Christoph Treude, Stephan Diehl 0001. 191-194 [doi]
• Mining rule violations in JavaScript code snippetsUriel Campos, Guilherme Smethurst, João Pedro Moraes, Rodrigo Bonifácio, Gustavo Pinto 0001. 195-199 [doi]
• Snakes in paradise?: insecure python-related coding practices in stack overflowAkond Rahman, Effat Farhana, Nasif Imtiaz. 200-204 [doi]
• Man vs machine: a study into language identification of stack overflow code snippetsJens Dietrich, Markus Luczak-Rösch, Elroy Dalefield. 205-209 [doi]
• Python coding style compliance on stack overflowNikolaos Bafatakis, Niels Boecker, Wenjie Boon, Martin Cabello Salazar, Jens Krinke, Gazi Oznacar, Robert White. 210-214 [doi]
• Towards mining answer edits to extract evolution patterns in stack overflowThemistoklis Diamantopoulos, Maria-Ioanna Sifaki, Andreas L. Symeonidis. 215-219 [doi]
• Analyzing comment-induced updates on stack overflowAbhishek Soni, Sarah Nadi. 220-234 [doi]
• What edits are done on the highly answered questions in stack overflow?: an empirical studyXianhao Jin, Francisco Servant. 225-229 [doi]
• Can duplicate questions on stack overflow benefit the software development community?Durham Abric, Oliver E. Clark, Matthew Caminiti, Keheliya Gallaba, Shane McIntosh. 230-234 [doi]
• How often and what StackOverflow posts do developers reference in their GitHub projects?Saraj Singh Manes, Olga Baysal. 235-239 [doi]
• Characterizing duplicate code snippets between stack overflow and tutorialsManziba Akanda Nishi, Agnieszka Ciborowska, Kostadin Damevski. 240-244 [doi]
• Challenges with responding to static analysis tool alertsNasif Imtiaz, Akond Rahman, Effat Farhana, Laurie Williams. 245-249 [doi]
• Impact of stack overflow code snippets on software cohesion: a preliminary studyMashal Ahmad, Mel Ó Cinnéide. 250-254 [doi]
• We need to talk about microservices: an analysis from the discussions on StackOverflowAlan Bandeira, Carlos Alberto Medeiros, Matheus Paixão, Paulo Henrique Maia. 255-259 [doi]
• What do developers know about machine learning: a study of ML discussions on StackOverflowAbdul Ali Bangash, Hareem Sahar, Shaiful Alam Chowdhury, Alexander William Wong, Abram Hindle, Karim Ali. 260-264 [doi]
• Investigating next steps in static API-misuse detectionSven Amann, Hoan Anh Nguyen, Sarah Nadi, Tien N. Nguyen, Mira Mezini. 265-275 [doi]
• Identifying experts in software libraries and frameworks among GitHub usersJoão Eduardo Montandon, Luciana Lourdes Silva, Marco Tulio Valente. 276-287 [doi]
• Data-driven solutions to detect API compatibility issues in Android: an empirical studySimone Scalabrino, Gabriele Bavota, Mario Linares Vásquez, Michele Lanza, Rocco Oliveto. 288-298 [doi]
• Generating commit messages from diffs using pointer-generator networkQin Liu, Zihe Liu, Hongming Zhu, Hongfei Fan, Bowen Du, Yu Qian. 299-309 [doi]
• Automatically generating documentation for lambda expressions in JavaAnwar Alqaimi, Patanamon Thongtanunam, Christoph Treude. 310-320 [doi]
• Extracting API tips from developer question and answer websitesShaohua Wang, NhatHai Phan, Yan Wang, Yong Zhao. 321-332 [doi]
• The emergence of software diversity in maven centralCésar Soto-Valero, Amine Benelallam, Nicolas Harrand, Olivier Barais, Benoit Baudry. 333-343 [doi]
• The maven dependency graph: a temporal graph-based representation of maven centralAmine Benelallam, Nicolas Harrand, César Soto-Valero, Benoit Baudry, Olivier Barais. 344-348 [doi]
• Dependency versioning in the wildJens Dietrich 0001, David J. Pearce, Jacob Stringer, Amjed Tahir, Kelly Blincoe. 349-359 [doi]
• Splitting APIs: an exploratory study of software unbundlingAnderson S. Matos, João Bosco Ferreira Filho, Lincoln S. Rocha. 360-370 [doi]
• Automated software vulnerability assessment with concept driftTriet Huynh Minh Le, Bushra Sabir, M. Ali Babar. 371-382 [doi]
• A manually-curated dataset of fixes to vulnerabilities of open-source softwareSerena Elisa Ponta, Henrik Plate, Antonino Sabetta, Michele Bezzi, Cédric Dangremont. 383-387 [doi]
• Negative results on mining crypto-API usage rules in Android appsJun Gao, Pingfan Kong, Li Li, Tegawendé F. Bissyandé, Jacques Klein. 388-398 [doi]
• A dataset of non-functional bugsAida Radu, Sarah Nadi. 399-403 [doi]
• RmvDroid: towards a reliable Android malware dataset with app metadataHaoyu Wang, Junjun Si, Hao Li, Yao Guo 0001. 404-408 [doi]
• An empirical study of multiple names and email addresses in OSS version control repositoriesJiaxin Zhu, Jun Wei 0001. 409-420 [doi]
• Characterizing the roles of contributors in open-source scientific software projectsReed Milewicz, Gustavo Pinto, Paige Rodeghero. 421-432 [doi]
• git2net: mining time-stamped co-editing networks from large git repositoriesChristoph Gote, Ingo Scholtes, Frank Schweitzer. 433-444 [doi]
• The rise of Android code smells: who is to blame?Sarra Habchi, Naouel Moha, Romain Rouvoy. 445-456 [doi]
• Assessing diffusion and perception of test smells in scala projectsJonas De Bleser, Dario Di Nucci, Coen De Roover. 457-467 [doi]
• STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithmsVadim Markovtsev, Waren Long, Hugo Mougard, Konstantin Slavnov, Egor Bulychev. 468-478 [doi]
• Can issues reported at stack overflow questions be reproduced?: an exploratory studySaikat Mondal, Mohammad Masudur Rahman 0001, Chanchal K. Roy. 479-489 [doi]
• Exploratory study of slack Q&A chats as a mining source for software engineering toolsPreetha Chatterjee, Kostadin Damevski, Lori L. Pollock, Vinay Augustine, Nicholas A. Kraft. 490-501 [doi]
• Impacts of daylight saving time on software developmentJunichi Hayashi, Yoshiki Higo, Shinsuke Matsumoto, Shinji Kusumoto. 502-506 [doi]
• A large-scale study about quality and reproducibility of jupyter notebooksJoão Felipe Pimentel, Leonardo Murta, Vanessa Braganholo, Juliana Freire. 507-517 [doi]
• Cross-language clone detection by learning over abstract syntax treesDaniel Perez, Shigeru Chiba. 518-528 [doi]
• SeSaMe: a data set of semantically similar Java methodsMarius Kamp, Patrick Kreutzer, Michael Philippsen. 529-533 [doi]
• Predicting co-changes between functionality specifications and source code in behavior driven developmentAidan Z. H. Yang, Daniel Alencar da Costa, Ying Zou 0001. 534-544 [doi]
• Tracing back log data to its log statement: from research to practiceDaan Schipper, Maurício Finavaro Aniche, Arie van Deursen. 545-549 [doi]
• Beyond GumTree: a hybrid approach to generate edit scriptsJunnosuke Matsumoto, Yoshiki Higo, Shinji Kusumoto. 550-554 [doi]
• The impact of systematic edits in history slicingRyosuke Funaki, Shinpei Hayashi, Motoshi Saeki. 555-559 [doi]
• Scalable software merging studies with MergAnserMoein Owhadi-Kareshk, Sarah Nadi. 560-564 [doi]
• Standing on shoulders or feet?: the usage of the MSR data papersZoe Kotti, Diomidis Spinellis. 565-576 [doi]
• Boa meets python: a boa dataset of data science software in python languageSumon Biswas, Md Johirul Islam, Yijia Huang, Hridesh Rajan. 577-581 [doi]
• A benchmark of data loss bugs for Android appsOliviero Riganelli, Marco Mobilio, Daniela Micucci, Leonardo Mariani. 582-586 [doi]
• RapidRelease: a dataset of projects and issues on github with rapid releasesSaket Dattatray Joshi, Sridhar Chimalakonda. 587-591 [doi]
• ConPan: a tool to analyze packages in software containersAhmed Zerouali, Valerio Cosentino, Gregorio Robles, Jesús M. González-Barahona, Tom Mens. 592-596 [doi]
• An empirical history of permission requests and mistakes in open source Android appsGian Luca Scoccia, Anthony Peruma, Virginia Pujols, Ben Christians, Daniel E. Krutz. 597-601 [doi]