SOTAVerified

Program Synthesis

Program synthesis is the process of automatically generating a program or code snippet that satisfies a given specification or set of requirements. This can include generating code from a formal specification, a natural language description, or example inputs and outputs. The primary goal of program synthesis is to minimize human intervention in the coding process, reduce errors, and improve productivity.

Program synthesis often involves the use of advanced algorithms, artificial intelligence, and machine learning techniques to search the space of possible programs that meet the given constraints. This process can be guided by a variety of techniques, such as constraint solving, symbolic execution, and genetic algorithms.

Papers

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Showing 101–125 of 423 papers

TitleStatusHype
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking—0
Adversarial Synthetic Datasets for Neural Program Synthesis—0
Function-constrained Program Synthesis—0
A Neurosymbolic Approach to Adaptive Feature Extraction in SLAM—0
Can Large Language Models Understand Symbolic Graphics Programs?—0
Fully Autonomous Programming with Large Language Models—0
Can humans teach machines to code?—0
Efficient Pragmatic Program Synthesis with Informative Specifications—0
Effective Adaptive Mutation Rates for Program Synthesis—0
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration—0
Functional Code Building Genetic Programming—0
EcoSearch: A Constant-Delay Best-First Search Algorithm for Program Synthesis—0
EgoCoder: Intelligent Program Synthesis with Hierarchical Sequential Neural Network Model—0
Procedural Adherence and Interpretability Through Neuro-Symbolic Generative Agents—0
Dynamic Neural Program Embeddings for Program Repair—0
Dreaming with ARC—0
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation—0
Can LLMs plan paths with extra hints from solvers?—0
A Divide-Align-Conquer Strategy for Program Synthesis—0
Example-based Synthesis of Static Analysis Rules—0
Bayesian Program Learning by Decompiling Amortized Knowledge—0
Execution-Guided Neural Program Synthesis—0
BizBench: A Quantitative Reasoning Benchmark for Business and Finance—0
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis—0
Down-Sampled Epsilon-Lexicase Selection for Real-World Symbolic Regression Problems—0
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All datasetsSPoC TestPSPoC TestWAlgoLisp

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DrRepairSuccess rate @budget 10038.5—Unverified
2Multiclass localizerSuccess rate @budget 10034.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DrRepairSuccess rate @budget 10057—Unverified
2Multiclass localizerSuccess rate @budget 10053.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeTrans-MT-TF-SmallAccuracy90.31—Unverified