Extract Package Refactoring in ARIES. - Fabio Palomba; Michele Tufano; Gabriele Bavota; Rocco Oliveto; Andrian Marcus; Denys Poshyvanyk; Andrea De Lucia (ICSE (2), 2015)

When and Why Your Code Starts to Smell Bad. - Michele Tufano; Fabio Palomba; Gabriele Bavota; Rocco Oliveto; Massimiliano Di Penta; Andrea De Lucia; Denys Poshyvanyk (ICSE (1), 2015)

Landfill: An Open Dataset of Code Smells with Public Evaluation. - Fabio Palomba; Dario Di Nucci; Michele Tufano; Gabriele Bavota; Rocco Oliveto; Denys Poshyvanyk; Andrea De Lucia (MSR, 2015)

An empirical investigation into the nature of test smells. - Michele Tufano; Fabio Palomba; Gabriele Bavota; Massimiliano Di Penta; Rocco Oliveto; Andrea De Lucia; Denys Poshyvanyk (ASE, 2016)

Deep learning code fragments for code clone detection. - Martin White; Michele Tufano; Christopher Vendome; Denys Poshyvanyk (ASE, 2016)

Enabling mutation testing for Android apps. - Mario Linares Vásquez; Gabriele Bavota; Michele Tufano; Kevin Moran; Massimiliano Di Penta; Christopher Vendome; Carlos Bernal-Cárdenas; Denys Poshyvanyk (ESEC/SIGSOFT FSE, 2017)

How developers micro-optimize Android apps. - Mario Linares Vásquez; Christopher Vendome; Michele Tufano; Denys Poshyvanyk (J. Syst. Softw., 2017)

An empirical study on developer-related factors characterizing fix-inducing commits. - Michele Tufano; Gabriele Bavota; Denys Poshyvanyk; Massimiliano Di Penta; Rocco Oliveto; Andrea De Lucia (J. Softw. Evol. Process., 2017)

There and back again: Can you compile that snapshot? - Michele Tufano; Fabio Palomba; Gabriele Bavota; Massimiliano Di Penta; Rocco Oliveto; Andrea De Lucia; Denys Poshyvanyk (J. Softw. Evol. Process., 2017)

When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away). - Michele Tufano; Fabio Palomba; Gabriele Bavota; Rocco Oliveto; Massimiliano Di Penta; Andrea De Lucia; Denys Poshyvanyk (IEEE Trans. Software Eng., 2017)

MDroid+: a mutation testing framework for android. - Kevin Moran; Michele Tufano; Carlos Bernal-Cárdenas; Mario Linares Vásquez; Gabriele Bavota; Christopher Vendome; Massimiliano Di Penta; Denys Poshyvanyk (ICSE (Companion Volume), 2018)

Towards just-in-time refactoring recommenders. - Jevgenija Pantiuchina; Gabriele Bavota; Michele Tufano; Denys Poshyvanyk (ICPC, 2018)

An empirical investigation into learning bug-fixing patches in the wild via neural machine translation. - Michele Tufano; Cody Watson; Gabriele Bavota; Massimiliano Di Penta; Martin White; Denys Poshyvanyk (ASE, 2018)

Deep learning similarities from different representations of source code. - Michele Tufano; Cody Watson; Gabriele Bavota; Massimiliano Di Penta; Martin White; Denys Poshyvanyk (MSR, 2018)

How developers micro-optimize Android apps (journal-first abstract). - Mario Linares Vásquez; Christopher Vendome; Michele Tufano; Denys Poshyvanyk (SANER, 2018)

Guigle: a GUI search engine for Android apps. - Carlos Bernal-Cárdenas; Kevin Moran; Michele Tufano; Zichang Liu; Linyong Nan; Zhehan Shi; Denys Poshyvanyk (ICSE (Companion Volume), 2019)

On learning meaningful code changes via neural machine translation. - Michele Tufano; Jevgenija Pantiuchina; Cody Watson; Gabriele Bavota; Denys Poshyvanyk (ICSE, 2019)

Towards predicting the impact of software changes on building activities. - Michele Tufano; Hitesh Sajnani; Kim Herzig (ICSE (NIER), 2019)

Learning How to Mutate Source Code from Bug-Fixes. - Michele Tufano; Cody Watson; Gabriele Bavota; Massimiliano Di Penta; Martin White; Denys Poshyvanyk (ICSME, 2019)

Sorting and Transforming Program Repair Ingredients via Deep Learning Code Similarities. - Martin White; Michele Tufano; Matias Martinez; Martin Monperrus; Denys Poshyvanyk (SANER, 2019)

An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation. - Michele Tufano; Cody Watson; Gabriele Bavota; Massimiliano Di Penta; Martin White; Denys Poshyvanyk (ACM Trans. Softw. Eng. Methodol., 2019)

DeepMutation: a neural mutation tool. - Michele Tufano; Jason Kimko; Shiya Wang; Cody Watson; Gabriele Bavota; Massimiliano Di Penta; Denys Poshyvanyk (ICSE (Companion Volume), 2020)

On learning meaningful assert statements for unit test cases. - Cody Watson; Michele Tufano; Kevin Moran; Gabriele Bavota; Denys Poshyvanyk (ICSE, 2020)

Unit Test Case Generation with Transformers. - Michele Tufano; Dawn Drain; Alexey Svyatkovskiy; Shao Kun Deng; Neel Sundaresan (CoRR, 2020)

Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy. - Colin B. Clement; Shuai Lu; Xiaoyu Liu; Michele Tufano; Dawn Drain; Nan Duan; Neel Sundaresan; Alexey Svyatkovskiy (EMNLP (1), 2021)

GraphCodeBERT: Pre-training Code Representations with Data Flow. - Daya Guo; Shuo Ren; Shuai Lu; Zhangyin Feng; Duyu Tang; Shujie Liu 001; Long Zhou; Nan Duan; Alexey Svyatkovskiy; Shengyu Fu; Michele Tufano; Shao Kun Deng; et al. (ICLR, 2021)

Towards Automating Code Review Activities. - Rosalia Tufano; Luca Pascarella; Michele Tufano; Denys Poshyvanyk; Gabriele Bavota (ICSE, 2021)

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation. - Shuai Lu; Daya Guo; Shuo Ren; Junjie Huang 008; Alexey Svyatkovskiy; Ambrosio Blanco; Colin B. Clement; Dawn Drain; Daxin Jiang; Duyu Tang; Ge Li 001; Lidong Zhou; et al. (NeurIPS Datasets and Benchmarks, 2021)

SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair. - Zimin Chen; Steve Kommrusch; Michele Tufano; Louis-Noël Pouchet; Denys Poshyvanyk; Martin Monperrus (IEEE Trans. Software Eng., 2021)

Generating Accurate Assert Statements for Unit Test Cases using Pretrained Transformers. - Michele Tufano; Dawn Drain; Alexey Svyatkovskiy; Neel Sundaresan (AST@ICSE, 2022)

METHODS2TEST: A dataset of focal methods mapped to test cases. - Michele Tufano; Shao Kun Deng; Neel Sundaresan; Alexey Svyatkovskiy (MSR, 2022)

Exploring and evaluating personalized models for code generation. - Andrei Zlotchevski; Dawn Drain; Alexey Svyatkovskiy; Colin B. Clement; Neel Sundaresan; Michele Tufano (ESEC/SIGSOFT FSE, 2022)

An Empirical Investigation into the Use of Image Captioning for Automated Software Documentation. - Kevin Moran; Ali Yachnes; George Purnell; Junayed Mahmud; Michele Tufano; Carlos Bernal-Cárdenas; Denys Poshyvanyk; Zach H'Doubler (SANER, 2022)

Enabling Mutant Generation for Open- and Closed-Source Android Apps. - Camilo Escobar-Velásquez; Mario Linares-Vásquez; Gabriele Bavota; Michele Tufano; Kevin Moran; Massimiliano Di Penta; Christopher Vendome; Carlos Bernal-Cárdenas; Denys Poshyvanyk (IEEE Trans. Software Eng., 2022)

InferFix: End-to-End Program Repair with LLMs. - Matthew Jin; Syed Shahriar; Michele Tufano; Xin Shi; Shuai Lu; Neel Sundaresan; Alexey Svyatkovskiy (ESEC/SIGSOFT FSE, 2023)

Predicting Code Coverage without Execution. - Michele Tufano; Shubham Chandel; Anisha Agarwal; Neel Sundaresan; Colin B. Clement (CoRR, 2023)

Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming. - Anisha Agarwal; Aaron Chan; Shubham Chandel; Jinu Jang; Shaun Miller; Roshanak Zilouchian Moghaddam; Yevhen Mohylevskyy; Neel Sundaresan; Michele Tufano (CoRR, 2024)

AutoDev: Automated AI-Driven Development. - Michele Tufano; Anisha Agarwal; Jinu Jang; Roshanak Zilouchian Moghaddam; Neel Sundaresan (CoRR, 2024)

Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation. - Benjamin Steenhoek; Michele Tufano; Neel Sundaresan; Alexey Svyatkovskiy (DeepTest, 2025)

Evaluating Agent-Based Program Repair at Google. - Pat Rondon; Renyao Wei; José Cambronero; Jürgen Cito; Aaron Sun; Siddhant Sanyam; Michele Tufano; Satish Chandra 001 (SEIP@ICSE, 2025)

Agentic Bug Reproduction for Effective Automated Program Repair at Google. - Runxiang Cheng; Michele Tufano; Jürgen Cito; José Cambronero; Pat Rondon; Renyao Wei; Aaron Sun; Satish Chandra 001 (CoRR, 2025)