24 papers · ranked by Valyu relevance
Shantanu Mandal, Todd A. Anderson, Javier S. Turek, Justin Gottschlich + 1 more
'Justin Gottschlich' 'Abdullah Muzahid'] Automatic software generation based on some specification is known as program synthesis. Most existing approaches formulate program synthesis as a search problem with discrete parameters. In this paper, we present a novel formulation of program synthesis as a continuous…
Yuan Yuan, Wolfgang Banzhaf
Program synthesis aims to automatically find programs from an underlying programming language that satisfy a given specification. While this has the potential to revolutionize computing, how to search over the vast space of programs efficiently is an unsolved challenge in program synthesis. In cases where large…
Jose Guadalupe Hernandez, Anil Kumar Saini, Gabriel Ketron, Jason H. Moore
Genetic programming (GP) and large language models (LLMs) differ in how program specifications are provided: GP uses input-output examples, and LLMs use text descriptions. In this work, we compared the ability of PushGP and GPT-4o to synthesize computer programs for tasks from the PSB2 benchmark suite. We used three…
John Feser, Işıl Dillig, Armando Solar-Lezama
We present a new domain-agnostic synthesis technique for generating programs from input-output examples. Our method, called metric program synthesis, relaxes the well-known observational equivalence idea (used widely in bottom-up enumerative synthesis) into a weaker notion of observational similarity, with the goal of…
Kobaladze, Zurabi, Arnania, Anna + 1 more
Program synthesis, the automated generation of executable code from a high-level specification, has been a central goal of computer science for over half a century. This thesis presents a comparative literature review of the primary paradigms that have defined and shaped this field. It charts the historical and…
Alessandro Abate, Haniel Barbosa, Clark Barrett, Cristina David + 5 more
'Pascal Kesseli' 'Daniel Kroening' 'Elizabeth Polgreen' 'Andrew Reynolds' 'Cesare Tinelli'] Program synthesis is the mechanised construction of software. One of the main difficulties is the efficient exploration of the very large solution space, and tools often require a user-provided syntactic restriction of the…
Margarida Ferreira, Victor Nicolet, Joey Dodds, Daniel Kroening
We present the first technique to synthesize programs that compose side-effecting functions, pure functions, and control flow, from partial traces containing records of only the side-effecting functions. This technique can be applied to synthesize API composing scripts from logs of calls made to those APIs, or a script…
Jiangyi Liu, Charlie Murphy, Anvay Grover, Keith J. C. Johnson + 2 more
'Thomas Reps' 'Loris D’Antoni'] Program verification and synthesis frameworks that allow one to customize the language in which one is interested typically require the user to provide a formally defined semantics for the language. Because writing a formal semantics can be a daunting and error-prone task, this…
Christopher J. Mungall, Adnan Malik, Daniel R. Korn, Justin T. Reese + 2 more
Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for…
Joshua S. Rule, Steven T. Piantadosi, Andrew Cropper, Kevin Ellis + 2 more
Throughout their lives, humans seem to learn a variety of rules for things like applying category labels, following procedures, and explaining causal relationships. These rules are often algorithmically rich but are nonetheless acquired with minimal data and computation. Symbolic models based on program learning…
Pablo Samuel Castro, Nenad Tomasev, Ankit Anand, Navodita Sharma + 13 more
Symbolic models play a key role in cognitive science, expressing computationally precise hypotheses about how the brain implements a cognitive process. Identifying an appropriate model typically requires a great deal of effort and ingenuity on the part of a human scientist. Here, we adapt FunSearch 39, a recently…
Yunzhuo Hu, Danni Pan, Fei Xu, Bifang Huang + 3 more
'Shiqiang Lin' 'Rogerio Sotelo-Mundo'] Researchers often need to synthesize genes of interest in this era of synthetic biology. Gene synthesis by PCR assembly of multiple DNA fragments is a quick and economical method that is widely applied. Up to now, there have been a few software solutions for designing fragments in…
Pavel Kodytek, Alexandra Bodzas, Jan Zidek, Govind Vashishtha
Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field…
George Chao, Evan Appleton, Clair S. Gutierrez, Lilia Evgeniou + 4 more
Pluripotent cells specialize into numerous cell types by receiving external signals, making fate decisions, and executing differentiation functions – a paradigm similar to computer algorithms. While advances in biosensor design have enabled cells to respond to diverse stimuli, the ability to maintain a synthetic memory…
Brian Hie, Salvatore Candido, Zeming Lin, Ori Kabeli + 4 more
Combining a basic set of building blocks into more complex forms is a universal design principle. Most protein designs have proceeded from a manual bottom-up approach using parts created by nature, but top-down design of proteins is fundamentally hard due to biological complexity. We demonstrate how the modularity and…
Pieter Floris Jacobs, Robert Pollice
Scientists across domains are often challenged to master domain-specific languages (DSLs) for their research, which are merely a means to an end but are pervasive in fields like computational chemistry. Automated code generation promises to overcome this barrier, allowing researchers to focus on their core expertise.…
Shuan Chen, Yousung Jung
Synthetic accessibility prediction is a task to estimate how easily a given molecule might be synthesizable in the laboratory, playing a crucial role in computer-aided molecular design. Although synthesis planning programs can determine synthesis routes, their slow processing times make them impractical for large-scale…
Authors not listed
Computer-aided synthesis planning aims to identify viable synthetic routes from a target compound to readily available building blocks by iteratively decomposing molecules into smaller precursors. Self-play search algorithms, trained with simulated experience, reach state-of-the-art performance. However, these methods…
Authors not listed
Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…
Kathleen S. Dreyer, Anh V. Nguyen, Gauri G. Bora, Lauren E. Redus + 6 more
Genetic programs can direct living systems to perform diverse, pre-specified functions. As the library of parts available for building such programs continues to expand, computation-guided design is increasingly helpful and necessary. Predictive models aid the challenging design process, but iterative simulation and…
Authors not listed
Computer-Assisted Synthesis Programs are increasingly employed by organic chemists. Often, these tools combine neural networks for policy prediction with heuristic search algorithms. We propose two novel enhancements, which we call eUCT and dUCT, to the Monte Carlo tree search (MCTS) algorithm. The enhancements were…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
Anh Phong Tran, Dhruv D. Jatkar, M. Ali Al-Radhawi, Elizabeth A. Ernst + 1 more
Minimal synthesis of Boolean functions is an NP-hard problem, and heuristic approaches typically give suboptimal circuits. However, in the emergent field of synthetic biology, genetic logic designs that use even a single additional Boolean gate can render a circuit unimplementable in a cell. This has led to a renewed…
Tristan Stérin, Abeer Eshra, Janet Adio, Constantine Glen Evans + 1 more
Like life, computers are out-of-equilibrium.^1,2^ Thermodynamically favoured error states are thwarted by energetically-costly processes such as kinetic proofreading of biological polymers, error-correcting codes in computer data storage, and redundancy in molecular programming. Decades of theoretical work shows that…