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ORCIDEmpirical Software Engineering, Volume 30
Volume 30, Number 1, February 2025
- Khaled Sellami
, Mohamed Aymen Saied:
Extracting microservices from monolithic systems using deep reinforcement learning. 1 - Michael Dorner, Daniel Méndez, Krzysztof Wnuk, Ehsan Zabardast, Jacek Czerwonka:
The upper bound of information diffusion in code review. 2 - Jaemin Hong, Sukyoung Ryu:
Type-migrating C-to-Rust translation using a large language model. 3 - Umme Ayman Koana, Quang Hy Le, Shaikur Raman, Chris Carlson, Francis Chew, Maleknaz Nayebi:
Correction to: Examining ownership models in software teams. 4 - Chao Tan, Razieh Behjati, Erik Arisholm:
Application of deep learning models to generate rich, dynamic and production-like test data. 5 - Hao Li, Cor-Paul Bezemer:
Bridging the language gap: an empirical study of bindings for open source machine learning libraries across software package ecosystems. 6 - Cristina Improta, Pietro Liguori, Roberto Natella, Bojan Cukic, Domenico Cotroneo:
Enhancing robustness of AI offensive code generators via data augmentation. 7 - Ricardo de Sousa Job, André C. Hora:
How and why developers implement OS-specific tests. 8 - Fiorella Zampetti, Cyrine Zid, Giuliano Antoniol, Massimiliano Di Penta:
The downside of functional constructs: a quantitative and qualitative analysis of their fix-inducing effects. 9 - Sebastián Pizard, Joaquín Lezama, Rodrigo García, Diego Vallespir, Barbara A. Kitchenham:
Using rapid reviews to support software engineering practice: a systematic review and a replication study. 10 - Shishuai Yang, Qinsheng Hou, Shuang Li, Fenghao Xu, Wenrui Diao:
From guidelines to practice: assessing Android app developer compliance with google's security recommendations. 11 - Monoshiz Mahbub Khan, Zhe Yu:
Approaching code search for python as a translation retrieval problem with dual encoders. 12 - Hanying Shao, Zishuo Ding, Weiyi Shang, Jinqiu Yang, Nikolaos Tsantalis:
Towards effectively testing machine translation systems from white-box perspectives. 13 - Yijian Wu, Yuan Chen, Xin Peng, Bin Hu, Xiaochen Wang, Baiqiang Fu, Wenyun Zhao:
CloneRipples: predicting change propagation between code clone instances by graph-based deep learning. 14 - Belinda Schantong, Norbert Siegmund, Janet Siegmund:
Toward a theory on programmer's block inspired by writer's block. 15 - Jonas Eberlein, Daniel Rodríguez, Rachel Harrison:
The effect of data complexity on classifier performance. 16 - Flávia Coelho, Nikolaos Tsantalis, Tiago Massoni, Everton L. G. Alves:
A qualitative study on refactorings induced by code review. 17 - Umm-e-Habiba, Mohammad Kasra Habib, Justus Bogner, Jonas Fritzsch, Stefan Wagner:
How do ML practitioners perceive explainability? an interview study of practices and challenges. 18 - Luca Giamattei, Matteo Biagiola, Roberto Pietrantuono, Stefano Russo, Paolo Tonella:
Reinforcement learning for online testing of autonomous driving systems: a replication and extension study. 19 - Yijun Shen, Xiang Gao, Hailong Sun, Yu Guo:
Understanding vulnerabilities in software supply chains. 20 - Weidong Wang, Dian Li, Yujian Kang, Yang Zhao:
An intelligent java method name recommendation framework via two-phase neural networks. 21 - Daniel Blackwell, Ingolf Becker, David Clark:
Hyperfuzzing: black-box security hypertesting with a grey-box fuzzer. 22 - Mehil B. Shah, Mohammad Masudur Rahman, Foutse Khomh:
Towards enhancing the reproducibility of deep learning bugs: an empirical study. 23 - Lanxin Yang, Bohan Liu, Junyu Jia, Jinwei Xu, Junming Xue, He Zhang, Alberto Bacchelli:
Prioritizing code review requests to improve review efficiency: a simulation study. 24 - Annalí Casanueva Artís, Davide Rossi, Stefano Zacchiroli, Théo Zimmermann:
The impact of the COVID-19 pandemic on women's contribution to public code. 25 - Lev Sorokin, Damir Safin, Shiva Nejati:
Can search-based testing with pareto optimization effectively cover failure-revealing test inputs? 26 - Luana Almeida Martins, Valeria Pontillo, Heitor A. X. Costa, Filomena Ferrucci, Fabio Palomba, Ivan do Carmo Machado:
Test code refactoring unveiled: where and how does it affect test code quality and effectiveness? 27 - Junda He, Bowen Xu, Zhou Yang, DongGyun Han, Chengran Yang, Jiakun Liu, Zhipeng Zhao, David Lo:
PTM4Tag+: Tag recommendation of stack overflow posts with pre-trained models. 28 - Julian Frattini, Davide Fucci, Richard Torkar, Lloyd Montgomery, Michael Unterkalmsteiner, Jannik Fischbach, Daniel Méndez:
Applying bayesian data analysis for causal inference about requirements quality: a controlled experiment. 29 - James Caddy, Christoph Treude, Markus Wagner, Earl T. Barr:
The role of surprisal in issue trackers. 30 - Taiming Wang, Yuxia Zhang, Lin Jiang, Yi Tang, Guangjie Li, Hui Liu:
Deep learning based identification of inconsistent method names: How far are we? 31 - Zihan Sha, Chao Zhang, Hao Wang, Zeyu Gao, Bolun Zhang, Yang Lan, Hui Shu:
PromeTrans: Bootstrap binary functionality classification with knowledge transferred from pre-trained models. 32 - Emad Fallahzadeh, Peter C. Rigby, Bram Adams:
Contrasting test selection, prioritization, and batch testing at scale. 33 - Alina Mailach, Dominik Gorgosch, Norbert Siegmund, Janet Siegmund:
"Ok Pal, we have to code that now": interaction patterns of programming beginners with a conversational chatbot. 34 - Povilas Godliauskas, Darja Smite:
The well-being of software engineers: a systematic literature review and a theory. 35 - Xunzhu Tang, Haoye Tian, Pingfan Kong, Saad Ezzini, Kui Liu, Xin Xia, Jacques Klein, Tegawendé F. Bissyandé:
Correction to: App review driven collaborative bug finding. 36 - Xin Zhou, DongGyun Han, David Lo:
Bridging expert knowledge with deep learning techniques for just-in-time defect prediction. 37 - Xueqi Yang, Mariusz Jakubowski, Li Kang, Haojie Yu, Tim Menzies:
SparseCoder: Advancing source code analysis with sparse attention and learned token pruning. 38 - Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh:
Harnessing pre-trained generalist agents for software engineering tasks. 39 - Elçin Yenisen Yavuz, Dirk Riehle, Ankita Mehrotra:
Why do companies create and how do they succeed with a vendor-led open source foundation. 40
Volume 30, Number 2, March 2025
- Deepika Badampudi, Muhammad Usman, Xingru Chen:
Large scale reuse of microservices using CI/CD and InnerSource practices - a case study. 41 - Dhanushka Jayasuriya, Samuel Ou, Saakshi Hegde, Valerio Terragni, Jens Dietrich, Kelly Blincoe:
An extended study of syntactic breaking changes in the wild. 42 - Anders Sundelin, Javier Gonzalez-Huerta, Richard Torkar, Krzysztof Wnuk:
Governing the commons: code ownership and code-clones in large-scale software development. 43 - Sangwon Hyun, Eunkyoung Jee, Doo-Hwan Bae:
Collaboration failure analysis in cyber-physical system-of-systems using context fuzzy clustering. 44 - Sungmin Kang, Bei Chen, Shin Yoo, Jian-Guang Lou:
Explainable automated debugging via large language model-driven scientific debugging. 45 - Shamsa Abid, Xuemeng Cai, Lingxiao Jiang:
Measuring model alignment for code clone detection using causal interpretation. 46 - Norbert Tihanyi, Tamás Bisztray, Mohamed Amine Ferrag, Ridhi Jain, Lucas C. Cordeiro:
How secure is AI-generated code: a large-scale comparison of large language models. 47 - Mahdi Saeedi Nikoo, Sangeeth Kochanthara, Önder Babur, Mark van den Brand:
An empirical study of business process models and model clones on GitHub. 48 - Zihan Sha, Yang Lan, Chao Zhang, Hao Wang, Zeyu Gao, Bolun Zhang, Hui Shu:
OpTrans: enhancing binary code similarity detection with function inlining re-optimization. 49 - Zibin Zheng, Kaiwen Ning, Qingyuan Zhong, Jiachi Chen, Wenqing Chen, Lianghong Guo, Weicheng Wang, Yanlin Wang:
Towards an understanding of large language models in software engineering tasks. 50
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