Hi! I'm Michele Tufano,

a Computer Science Ph.D. from The College of William and Mary.
I currently work at Microsoft in the Natural Language Understanding team.

Interests

My research interests include Deep Learning applied to Software Engineering, Software Evolution and Maintenance, Mining Software Repositories, and Android Testing. I currently work at Microsoft in the Natural Language Understanding team, focusing on improving the entity understanding.

Deep Learning in SE

Mining Software Repositories

Source Code Bug & Bad Smells

Android Testing

Publications

Ph.D. Thesis


Learning Code Transformations via Neural Machine Translation
Michele Tufano
A Dissertation presented to the Graduate Faculty of The College of William & Mary in Candidacy for the Degree of Doctor of Philosophy

International Journals


[J6] SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair
Z. Chen, S. Kommrusch, M. Tufano, L.-N. Pouchet, D. Poshyvanyk, M. Monperrus
IEEE Transactions on Software Engineering (TSE 2019)

[J5] An Empirical Investigation into Learning Bug-Fixing Patches in the Wild via Neural Machine Translation
M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, D. Poshyvanyk
ACM Transactions on Software Engineering and Methodology (TOSEM 2019)

[J4] How Developers Micro-Optimize Android Apps
M. Linares-Vásquez, C. Vendome, M. Tufano, and D. Poshyvanyk
Journal of Systems and Software (JSS 2017)

[J3] When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away)
M. Tufano, F. Palomba, G. Bavota, R. Oliveto, M. Di Penta, A. De Lucia, and D. Poshyvanyk
IEEE Transactions on Software Engineering (TSE 2017)

[J2] There and Back Again: Can you Compile that Snapshot?
M. Tufano, F. Palomba, G. Bavota, M. Di Penta, R. Oliveto, A. De Lucia, and D. Poshyvanyk
Journal of Software: Evolution and Process (JSEP 2016)

[J1] An Empirical Study on Developer Related Factors Characterizing Fix-Inducing Commits
M. Tufano, G. Bavota, D. Poshyvanyk, M. Di Penta, R. Oliveto, and A. De Lucia
Journal of Software: Evolution and Process (JSEP 2016)

International Conferences


[C17] On Learning Meaningful Assert Statements for Unit Test Cases
C. Watson, M. Tufano, K. Moran, G. Bavota, D. Poshyvanyk
Proceedings 42nd ACM/IEEE International Conference on Software Engineering (ICSE 2020) - Seoul, South Korea, May 23-29, 2020, 4 pages. Acceptance Rate: 20.9%

[C16] DeepMutation: A Neural Mutation Tool
M. Tufano, J. Kimko, S. Wang, C. Watson, G. Bavota, M. Di Penta, D. Poshyvanyk
Proceedings 42nd ACM/IEEE International Conference on Software Engineering (ICSE 2020), Demonstrations Track - Seoul, South Korea, May 23-29, 2020, 4 pages. Acceptance Rate: 33.3%

[C15] Learning How to Mutate Source Code from Bug-Fixes
M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, D. Poshyvanyk
Proceedings 35th IEEE International Conference on Software Maintenance and Evolution (ICSME 2019) - Cleveland, OH, USA, October 2-4, 2019, to appear 12 pages. Acceptance Rate: 23%

[C14] On Learning Meaningful Code Changes via Neural Machine Translation
M. Tufano, J. Pantiuchina, C. Watson, G. Bavota, and D. Poshyvanyk
Proceedings 41st ACM/IEEE International Conference on Software Engineering (ICSE 2019) - Montréal, QC, Canada, May 25-31, 2019, to appear 12 pages. Acceptance Rate: 21%

[C13] Towards Predicting the Impact of Software Changes on Building Activities
M. Tufano, H. Sajnani, and K. Herzig
Proceedings 41st ACM/IEEE International Conference on Software Engineering (ICSE 2019), New Ideas and Emerging Results - Montréal, QC, Canada, May 25-31, 2019, to appear 4 pages. Acceptance Rate: 31%

[C12] Guigle: A GUI Search Engine for Android Apps
C. Bernal-Cárdenas, K. Moran, M. Tufano, Z. Liu, L. Nan, Z. Shi, and D. Poshyvanyk
Proceedings 41st ACM/IEEE International Conference on Software Engineering (ICSE 2019), Formal Research Tool Demonstration - Montréal, QC, Canada, May 25-31, 2019, to appear 4 pages. Acceptance Rate: 47%

[C11] Sorting and Transforming Program Repair Ingredients via Deep Learning Code Similarities
M. White, M. Tufano, M. Martinez, M. Monperrus, and D. Poshyvanyk
Proceedings 26th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2019) - Hangzhou, China, February 24-27, 2019, to appear12 pages. Acceptance Rate: 27%

[C10] An Empirical Investigation into Learning Bug-Fixing Patches in the Wild via Neural Machine Translation
M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, D. Poshyvanyk
Proceedings of the 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE 2018) - Montpellier, France, Sept. 3-7, 2018, New Ideas Paper. Acceptance Rate: 21%

[C9] Deep Learning Similarities from Different Representations of Source Code
M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, D. Poshyvanyk
Proceedings of the 15th IEEE/ACM International Conference on Mining Software Repositories (MSR 2018) - Gothenburg, Sweden, 2018, 12 pages, to appear. Acceptance Rate: 33%

[C8] Towards Just-In-Time Refactoring Recommenders
J. Pantiuchina, G. Bavota, M. Tufano, D. Poshyvanyk
Proceedings of the 26th IEEE/ACM International Conference on Program Comprehension (ICPC 2018), Early Research Achievement Track - Gothenburg, Sweden, 2018, 4 pages, to appear. Acceptance Rate: 47.8%
Best ERA Paper Award

[C7] MDroid+: A Mutation Testing Framework for Android
K. Moran, M. Tufano, C. Bernal-Cardenas, M. Linares-Vasquez, G. Bavota, C. Vendome, M. Di Penta, D. Poshyvanyk
Proceedings of the 40th IEEE/ACM International Conference on Software Engineering (ICSE 2018), Formal Research Demonstrations Track - Gothenburg, Sweden, 2018, 4 pages, to appear. Acceptance Rate: 35%

[C6] Enabling Mutation Testing for Android Apps
M. Linares-Vasquez, G. Bavota, M. Tufano, K. Moran, M. Di Penta, C. Vendome, C. Bernal-Cardenas, D. Poshyvanyk
In Proceedings of 11th Joint Meeting of the European Software Engineering Conference and the 22nd ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE 2017) - Paderborn, Germany, 2017, 12 pages, to appear. Acceptance Rate: 72/295 (24%)

[C5] Deep Learning Code Fragments for Code Clone Detection
M. White, M. Tufano, C. Vendome, and D. Poshyvanyk
In Proceedings of the International Conference on Automated Software Engineering (ASE 2016) - Singapore, Singapore, 2016, 12 pages, To appear. Acceptance Rate: 19%

[C4] An Empirical Investigation into the Nature of Test Smells
M. Tufano, F. Palomba, G. Bavota, R. Oliveto, M. Di Penta, A. De Lucia, and D. Poshyvanyk
In Proceedings of the International Conference on Automated Software Engineering (ASE 2016) - Singapore, Singapore, 2016, 12 pages, To appear. Acceptance Rate: 19%

[C3] Landfill: an Open Dataset of Code Smells with Public Evaluation
F. Palomba, D. Di Nucci, M. Tufano, G. Bavota, R. Oliveto, D. Poshyvanyk, A. De Lucia
In Proceedings of the 12th IEEE/ACM Working Conference on Mining Software Repositories (MSR 2015) - Florence, Italy, 2015, 4 pages, To appear

[C2] When and Why Your Code Starts to Smell Bad
M. Tufano, F. Palomba, G. Bavota, R. Oliveto, M. Di Penta, A. De Lucia, and D. Poshyvanyk
In Proceedings of the 37th International Conference on Software Engineering (ICSE 2015), Florence, Italy, 2015, 12 pages, To appear. Acceptance Rate: 84/452 (18%)
ACM/SIGSOFT Distinguished Paper Award

[C1] Extract Package Refactoring in ARIES
F. Palomba, M. Tufano, G. Bavota, R. Oliveto, A. Marcus, D. Poshyvanyk, and A. De Lucia
In Proceedings of the 37th International Conference on Software Engineering (ICSE 2015) - Demonstrations Track, Florence, Italy, 2015, 4 pages, To appear. Acceptance Rate: 25/42 (59%)

Workshops


[W1] ARIES: An Eclipse plug-in to Support Extract Class Refactoring
G. Bavota, A. De Lucia, A. Marcus, R. Oliveto, F. Palomba, and M. Tufano
In Proceedings of 8th Italian Workshop on Eclipse Technologies (Eclipse-it), Crema, Italy, 2013. LCNS Press

Teaching

Spring 2015

CS 421 - Database Systems - Teaching Assistant

Fall 2014

CS 141 - Computational Problem Solving - Teaching Assistant

Microsoft Research

Research Intern at Microsoft Research during summer 2018


Advised by Kim Herzig and Hitesh Sajnani









About Me

I was born in Avellino (Italy) on July, 22th, 1989. I received (cum laude) my Master degree in Computer Science from the University of Salerno (Italy) in 2014 defending a thesis on Mining Software Repositories, advised by Prof. Andrea De Lucia. I obtained my Ph.D. in Computer Science at The College of William and Mary on May, 2019, advised by Dr. Denys Poshyvanyk.

I speak three languages: Italian, English, and Neapolitan (a facc ro cazz!). However, only for the former and the latter I can obtain precision and recall up to 90%. I like computers and all kind of technology. When I'm not in front of a computer, I usually like to go out with my friends, try new food, swim and go to the gym.

...btw I spend too much time in front of my computer!

Contact

Office: Bellevue, Washington, 98004
Email: mtufano@email.wm.edu