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 251–275 of 423 papers

TitleStatusHype
Explainable Natural Language to Bash Translation using Abstract Syntax TreeCode0
Scaling Neural Program Synthesis with Distribution-based SearchCode1
Neural-guided, Bidirectional Program Search for Abstraction and Reasoning—0
Synthesizing Optimal Parallelism Placement and Reduction Strategies on Hierarchical Systems for Deep Learning—0
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems—0
Solving the Families In the Wild Kinship Verification Challenge by Program Synthesis—0
AutoCoder: Leveraging Transformers for Automatic Code Synthesis—0
Are Transformers All That Karel Needs?—0
Adversarial Robustness of Program Synthesis Models—0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking—0
AutumnSynth: Synthesis of Reactive Programs with Structured Latent State—0
Towards Physical, Imperceptible Adversarial Attacks via Adversarial Programs—0
Learning logic programs through divide, constrain, and conquerCode0
Parallel Constraint-Driven Inductive Logic Programming—0
Multi-modal Program Inference: a Marriage of Pre-trainedLanguage Models and Component-based Synthesis—0
Learning to Synthesize Programs as Interpretable and Generalizable PoliciesCode1
Recent Developments in Program Synthesis with Evolutionary Algorithms—0
Program Synthesis with Large Language ModelsCode1
Autoencoders as Tools for Program SynthesisCode0
SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life ApplicationsCode0
MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem SolvingCode1
Unsupervised Learning of Neurosymbolic EncodersCode1
Satisfiability and Synthesis Modulo Oracles—0
A Reinforcement Learning Environment for Mathematical Reasoning via Program SynthesisCode1
Latent Execution for Neural Program SynthesisCode1
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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