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Empirical 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
The upper bound of information diffusion in code review. 2 - Jaemin Hong
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
Application of deep learning models to generate rich, dynamic and production-like test data. 5 - Hao Li
Bridging the language gap: an empirical study of bindings for open source machine learning libraries across software package ecosystems. 6 - Cristina Improta
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
The downside of functional constructs: a quantitative and qualitative analysis of their fix-inducing effects. 9 - Sebastián Pizard, Joaquín Lezama, Rodrigo García, Diego Vallespir
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
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
CloneRipples: predicting change propagation between code clone instances by graph-based deep learning. 14 - Belinda Schantong
Toward a theory on programmer's block inspired by writer's block. 15 - Jonas Eberlein, Daniel Rodríguez
The effect of data complexity on classifier performance. 16 - Flávia Coelho
A qualitative study on refactorings induced by code review. 17 - Umm-e-Habiba
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
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