5 Search Results for "Feret, Jerome"

Document
DOI: 10.4230/LIPIcs.DNA.31.4
Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems

Authors: Inhoo Lee, Salvador Buse, and Erik Winfree

Published in: LIPIcs, Volume 347, 31st International Conference on DNA Computing and Molecular Programming (DNA 31) (2025)

Abstract
Many molecular systems are best understood in terms of prototypical species and reactions. The central dogma and related biochemistry are rife with examples: gene i is transcribed into RNA i, which is translated into protein i; kinase n phosphorylates substrate m; protein p dimerizes with protein q. Engineered nucleic acid systems also often have this form: oligonucleotide i hybridizes to complementary oligonucleotide j; signal strand n displaces the output of seesaw gate m; hairpin p triggers the opening of target q. When there are many variants of a small number of prototypes, it can be conceptually cleaner and computationally more efficient to represent the full system in terms of indexed species (e.g. for dimerization, M_p, D_pq) and indexed reactions (M_p + M_q → D_pq). Here, we formalize the Indexed Chemical Reaction Network (ICRN) model and describe a Python software package designed to simulate such systems in the well-mixed and reaction-diffusion settings, using a differentiable programming framework originally developed for large-scale neural network models, taking advantage of GPU acceleration when available. Notably, this framework makes it straightforward to train the models’ initial conditions and rate constants to optimize a target behavior, such as matching experimental data, performing a computation, or exhibiting spatial pattern formation. The natural map of indexed chemical reaction networks onto neural network formalisms provides a tangible yet general perspective for translating concepts and techniques from the theory and practice of neural computation into the design of biomolecular systems.
Cite as

Inhoo Lee, Salvador Buse, and Erik Winfree. Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems. In 31st International Conference on DNA Computing and Molecular Programming (DNA 31). Leibniz International Proceedings in Informatics (LIPIcs), Volume 347, pp. 4:1-4:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{lee_et_al:LIPIcs.DNA.31.4,
  author =	{Lee, Inhoo and Buse, Salvador and Winfree, Erik},
  title =	{{Differentiable Programming of Indexed Chemical Reaction Networks and Reaction-Diffusion Systems}},
  booktitle =	{31st International Conference on DNA Computing and Molecular Programming (DNA 31)},
  pages =	{4:1--4:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-399-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{347},
  editor =	{Schaeffer, Josie and Zhang, Fei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.31.4},
  URN =		{urn:nbn:de:0030-drops-238534},
  doi =		{10.4230/LIPIcs.DNA.31.4},
  annote =	{Keywords: Differentiable Programming, Chemical Reaction Networks, Reaction-Diffusion Systems}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2025.34
Taming and Dissecting Recursions Through Interprocedural Weak Topological Ordering

Authors: Jiawei Yang, Xiao Cheng, Bor-Yuh Evan Chang, Xiapu Luo, and Yulei Sui

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
Abstract interpretation provides a foundational framework for approximating program semantics by interpreting code through abstract domains using semantic functions over ordered sets along a program’s control flow graph (CFG). To facilitate fixpoint computation in abstract interpretation, weak topological ordering (WTO) is an effective strategy for handling loops, as it identifies strategic control points in the CFG where widening and narrowing operations should be applied. However, existing abstract interpreters still face challenges when extending WTO computation in the presence of recursive programs. Computing a precise whole-program WTO requires full context-sensitive analysis which is not scalable for large programs, while context-insensitive analysis introduces spurious cycles that compromise precision. Current approaches either ignore recursion (resulting in unsoundness) or rely on conservative approximations, sacrificing precision by adopting the greatest elements of abstract domains and applying widening at function boundaries without subsequent narrowing refinements. These can lead to undesired results for downstream tasks, such as bug detection. To address the above limitations, we present RecTopo, a new technique to boost the efficiency of precise abstract interpretation in the presence of recursive programs through interprocedural weak topological ordering (IWTO). Rather than pursuing an expensive whole-program WTO analysis, RecTopo employs an on-demand approach that strategically decomposes programs at recursion boundaries and constructs targeted IWTOs for each recursive component. RecTopo dissects and analyzes (nested) recursions through interleaved widening and narrowing operations. This approach enables precise control over interpretation ordering within recursive structures while eliminating spurious recursions through systematic correlation of control flow and call graphs. We implemented RecTopo and evaluated its effectiveness using an assertion-based checking client focused on buffer overflow detection, comparing it against three popular open-source abstract interpreters (IKOS, Clam, CSA). The experiments on 8312 programs from the NIST dataset demonstrate that, on average, RecTopo is 31.99% more precise and achieves a 17.49% higher recall rate compared to three other tools. Moreover, RecTopo exhibits an average precision improvement of 46.51% and a higher recall rate of 32.98% compared to our baselines across ten large open-source projects. Further ablation studies reveal that IWTO reduces spurious widening operations compared to whole-program WTO, resulting in a 12.83% reduction in analysis time.
Cite as

Jiawei Yang, Xiao Cheng, Bor-Yuh Evan Chang, Xiapu Luo, and Yulei Sui. Taming and Dissecting Recursions Through Interprocedural Weak Topological Ordering. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 34:1-34:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{yang_et_al:LIPIcs.ECOOP.2025.34,
  author =	{Yang, Jiawei and Cheng, Xiao and Chang, Bor-Yuh Evan and Luo, Xiapu and Sui, Yulei},
  title =	{{Taming and Dissecting Recursions Through Interprocedural Weak Topological Ordering}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{34:1--34:31},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.34},
  URN =		{urn:nbn:de:0030-drops-233265},
  doi =		{10.4230/LIPIcs.ECOOP.2025.34},
  annote =	{Keywords: Abstract interpretation, recursion, weak topological ordering}
}
Document
Experience Paper
DOI: 10.4230/LIPIcs.ECOOP.2025.37
RacerF: Lightweight Static Data Race Detection for C Code (Experience Paper)

Authors: Tomáš Dacík and Tomáš Vojnar

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
We present RacerF, a novel static analyser for thread-modular data race detection. The approach behind RacerF exploits static analysis of sequential program behaviour whose results are generalised for multi-threaded programs using a combination of lightweight under- and over-approximating methods. The tool is implemented as a plugin of the Frama-C platform and can leverage several analysis backends, most notably the Frama-C’s abstract interpreter EVA. Although our methods are mostly heuristic without providing formal guarantees, our experimental evaluation shows that even for intricate programs, RacerF can provide very precise results competitive with more heavyweight approaches while being faster than them.
Cite as

Tomáš Dacík and Tomáš Vojnar. RacerF: Lightweight Static Data Race Detection for C Code (Experience Paper). In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 37:1-37:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dacik_et_al:LIPIcs.ECOOP.2025.37,
  author =	{Dac{\'\i}k, Tom\'{a}\v{s} and Vojnar, Tom\'{a}\v{s}},
  title =	{{RacerF: Lightweight Static Data Race Detection for C Code}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{37:1--37:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.37},
  URN =		{urn:nbn:de:0030-drops-233298},
  doi =		{10.4230/LIPIcs.ECOOP.2025.37},
  annote =	{Keywords: concurrency, data race detection, static analysis}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2025.32
Compositional Static Value Analysis for Higher-Order Numerical Programs

Authors: Milla Valnet, Raphaël Monat, and Antoine Miné

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
Static analyzers have been successfully developed to detect runtime errors in many languages. However, the automatic analysis of functional languages remains a challenge due to their recursive functions, recursive algebraic data types, and higher-order functions. Classic type systems provide compositional methods that are in general not precise enough to prove the absence of runtime errors such as assertion failures. At the other end of the spectrum, deductive methods are more expressive but may require user guidance to prove invariants. Our work describes a static value analysis by abstract interpretation for a higher-order pure functional language. This analysis provides a sound and automatic approach to discover invariants and prevent assertion and match failures. We have designed a compositional analysis: functions are analyzed only once, at their definition site, generating a summary of their behavior. The summaries can be viewed as input-output relations expressed with relational abstract domains. We present two new abstract domains. A first abstract domain summarizes recursive algebraic data types. A second abstract domain lifts existing disjunctive relational summaries to higher-order by formalizing them as domains able to abstract higher-order functions. Both abstractions are parameterized by the abstractions of basic types (strings, integers, ...). Thanks to this parametric nature, both domains can be combined, allowing the analysis of higher-order functions manipulating algebraic data types and, conversely, algebraic data types using functions as first-class values. We have implemented this analysis in the open-source MOPSA platform. Preliminary evaluation confirms the precision of our approach on a set of 40 handwritten toy programs as well as 20 programs from the state-of-the-art Salto analyzer benchmark.
Cite as

Milla Valnet, Raphaël Monat, and Antoine Miné. Compositional Static Value Analysis for Higher-Order Numerical Programs. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 32:1-32:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{valnet_et_al:LIPIcs.ECOOP.2025.32,
  author =	{Valnet, Milla and Monat, Rapha\"{e}l and Min\'{e}, Antoine},
  title =	{{Compositional Static Value Analysis for Higher-Order Numerical Programs}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{32:1--32:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.32},
  URN =		{urn:nbn:de:0030-drops-233249},
  doi =		{10.4230/LIPIcs.ECOOP.2025.32},
  annote =	{Keywords: Static Value Analysis, Functional Programming, Abstract Interpretation}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2012.276
Graphs, Rewriting and Pathway Reconstruction for Rule-Based Models

Authors: Vincent Danos, Jerome Feret, Walter Fontana, Russell Harmer, Jonathan Hayman, Jean Krivine, Chris Thompson-Walsh, and Glynn Winskel

Published in: LIPIcs, Volume 18, IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2012)

Abstract
In this paper, we introduce a novel way of constructing concise causal histories (pathways) to represent how specified structures are formed during simulation of systems represented by rule-based models. This is founded on a new, clean, graph-based semantics introduced in the first part of this paper for Kappa, a rule-based modelling language that has emerged as a natural description of protein-protein interactions in molecular biology [Bachman 2011]. The semantics is capable of capturing the whole of Kappa, including subtle side-effects on deletion of structure, and its structured presentation provides the basis for the translation of techniques to other models. In particular, we give a notion of trajectory compression, which restricts a trace culminating in the production of a given structure to the actions necessary for the structure to occur. This is central to the reconstruction of biochemical pathways due to the failure of traditional techniques to provide adequately concise causal histories, and we expect it to be applicable in a range of other modelling situations.
Cite as

Vincent Danos, Jerome Feret, Walter Fontana, Russell Harmer, Jonathan Hayman, Jean Krivine, Chris Thompson-Walsh, and Glynn Winskel. Graphs, Rewriting and Pathway Reconstruction for Rule-Based Models. In IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2012). Leibniz International Proceedings in Informatics (LIPIcs), Volume 18, pp. 276-288, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{danos_et_al:LIPIcs.FSTTCS.2012.276,
  author =	{Danos, Vincent and Feret, Jerome and Fontana, Walter and Harmer, Russell and Hayman, Jonathan and Krivine, Jean and Thompson-Walsh, Chris and Winskel, Glynn},
  title =	{{Graphs, Rewriting and Pathway Reconstruction for Rule-Based Models}},
  booktitle =	{IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2012)},
  pages =	{276--288},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-47-7},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{18},
  editor =	{D'Souza, Deepak and Radhakrishnan, Jaikumar and Telikepalli, Kavitha},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2012.276},
  URN =		{urn:nbn:de:0030-drops-38669},
  doi =		{10.4230/LIPIcs.FSTTCS.2012.276},
  annote =	{Keywords: concurrency, rule-based models, graph rewriting, pathways, causality}
}
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