Pierre Donat-Bouillud

Pierre Donat-Bouillud

Researcher

Czech Technical University

Biography

I am an assistant professor in computer science. My research interests include programming languages and research software engineering. I am part of the Programming Research Lab in Prague.

I apply my PL research to the R language: JIT compilation, benchmarking, type systems, large code analysis on R code bases, reproducibility, and fuzzing and testing. I am also the developer of the mutator mutation testing package for R.

During my PhD, I worked on Antescofo at Ircam, under the supervision of Florent Jacquemard and Jean-Louis Giavitto, and more generally on systems with languages that express complex temporal relations.

I am also interested in linguistics and language education through technology.

Download my resumé.

Interests
  • Fuzzing and testing
  • Programming languages
  • R language
Education

  • PhD in Computer Science, 2019

    Sorbonne université

  • Masters in Computer Science, 2015

    École Normale Supérieure de Rennes

  • BSc in Computer Science, 2013

    École Normale Supérieure de Rennes

Experience

 
 
 
 
 
Assistant Professor
Czech Technical University
Oct 2024 – Present Prague, Czechia
Teaches in the master and bachelor programs. Supervizes bachelor and master thesis.
 
 
 
 
 
Researcher
Czech Technical University
Jul 2020 – Present Prague, Czechia
Programming language research, on huge corpus of code of dynamic programming languages.
 
 
 
 
 
Independent Researcher
Self-employed
May 2020 – Jul 2020 Paris, France
Research on eval in R for CVUT
 
 
 
 
 
Researcher
Inria Paris
Sep 2019 – Nov 2019 Paris, France
Research in computer science
 
 
 
 
 
PhD student
Sorbonne université
Sep 2016 – Aug 2019 Paris, France

Research at Ircam in the Repmus group and taught computer science.

Responsibilities include:

  • Research in computer music and programming languages on Antescofo
  • Taught bachelor students
  • Supervized research projects of master students

Thesis Supervision

Also supervised 7 B.Sc. theses at FIT CTU (2023–present).

Teaching

I currently teach the following courses at the Faculty of Information Technology, Czech Technical University in Prague. Both are taught in English.

  • Programming Language Seminar (NI-PLS)

    A reading group introducing students to programming language research through paper presentations and discussions. Organized jointly with MFF, Charles University, through the Prague Programming Languages and Systems Research Network.

    Course website · CTU course catalogue

  • Advanced Program Testing (NI-APT)

    Advanced techniques for finding bugs, including specification and structural testing, property-based testing, fuzzing, and symbolic execution. Students put these techniques into practice through a programming project where they have to build a fuzzer for C programs.

    Course website · CTU course catalogue

Recent Posts

Finding NA in serialized R values
In a previous post, I explained how to test a C++ function, find_na, used in a database for R values. find_na checks if NA is present or not in a previously serialized R value.
Last updated on 17 Apr 2023 4 min read Programming Languages, Short
Project
Testing C++ Code in R Packages
When you write a package in R, you probably write tests. A popular package for unit tests with R is testthat,1 with the final invocation: devtools::test() If your package also includes native code, let’s say, C++, you can test it by testing the R API that exercises the native functions.
Last updated on 17 Apr 2023 3 min read Programming Languages, Short
Project

Projects

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Mutation testing for R with mutator

Mutation testing for R with mutator

mutator brings mutation testing to R packages: it systematically mutates source code, runs the test suite against each mutant, and reports how many are killed, survived, or timed out.

Code Documentation

R4R: Reproducibility for R

The project focuses on the reproducibility of computational notebooks in R.

Code

Data Bugs

The goal of this project is to develop new programming language technologies to assist data scientists, using the R language for empirical validation of our novel ideas. The project is financed by the operational program Jan Amos Comenius and spans from March, 2023, to March, 2025.

Fuzzing R

Fuzzing R

R is a vector-oriented, dynamic language, mostly used in data-science. It is difficult to statically analyze, and so we mainly use dynamic techniques to gather insights about R programs. One instance of them is fuzzing.

Code
Eval in R

Eval in R

The R language eval function is powerful and makes analysis difficult. WWhat are the usage of eval in R?

Code
Rhythm Quantization

Rhythm Quantization

Rhythms are represented using trees and quantization is performed by applying rewrite rules on the rhythm trees.

Code

Recent & Upcoming Talks

Beyond Code Coverage: Mutation Testing in R with MutatoR
Bringing mutation testing to R packages with the mutator package.
7 Jul 2026 13:20 — 13:40
Code Project Slides Abstract
R4R: Reproducibility for R
Automatically tracing pipeline dependencies to build reproducible Docker images for R.
10 Aug 2025 13:00 — 14:30 Penn 2, Duke University
Code Project

Recent Publications

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Leveraging Copy-and-Patch JIT for Low-Overhead Dynamic Program Analysis
Copy-and-patch JIT compilation as a foundation for low-overhead dynamic program analysis in R, with instrumentation, coverage, profiling, and native debugging. Published at MPLR 2026.
PDF Cite Code DOI
Revisiting Row Polymorphism for Set-Theoretic Types
A row polymorphism design for set-theoretic types that keeps substitutions simple by allowing Boolean combinations of row variables directly in record type constructors, with a complete tallying algorithm and an implementation in SSTT and MLsem. Published at OOPSLA 2026.
PDF Cite DOI
Educational Legacies of Christian Missions: Evidence from the Democratic Republic of the Congo
Using data on over 20,000 schools and two million students, we show that proximity to colonial-era Christian missions in the DR Congo is still associated today with broader, higher-quality curricula and better exam outcomes. Published in the Journal of Development Economics.
Cite DOI ScienceDirect
R4R: Reproducibility for R
Ensuring reproducibility is a fundamental challenge in computational research. Reproducing results often requires reconstructing …
PDF Cite Code Project Slides DOI
signatr: A Data-Driven Fuzzing Tool for R
The fast-and-loose, permissive semantics of dynamic programming languages limit the power of static analyses. For that reason, …
PDF Cite Project
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Popular Topics

Christian missions corpus studies cpp data science database Democratic Republic of the Congo design patterns dynamic analysis dynamic languages education eval Fuzzing grant JIT MapReduce ; Hadoop ; Scheduling ; SRTF mutation testing Programming language R reproducibility testing

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