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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 301–325 of 423 papers

TitleStatusHype
Program Synthesis as Dependency Quantified Formula Modulo TheoryCode0
Automated Decision-based Adversarial Attacks—0
Inductive Program Synthesis over Noisy Datasets using Abstraction Refinement Based Optimization—0
Toward Code Generation: A Survey and Lessons from Semantic Parsing—0
Geometry of Program Synthesis—0
Toward Neural-Network-Guided Program Synthesis and VerificationCode0
Program Synthesis Over Noisy Data with Guarantees—0
A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics—0
Refinement Type Directed Search for Meta-Interpretive-Learning of Higher-Order Logic Programs—0
Report of the Workshop on Program Synthesis for Scientific Computing—0
BF++: a language for general-purpose program synthesisCode0
Analysis of Evolutionary Program Synthesis for Card GamesCode0
Learning Differentially Private Mechanisms—0
FCR: Flow Chart Recognition Network for Program Synthesis—0
Visible and Invisible: Causal Variable Learning and its Application in a Cancer Study—0
Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints—0
Representing Partial Programs with Blended Abstract Semantics—0
Tag-based regulation of modules in genetic programming improves context-dependent problem solvingCode0
Latent Programmer: Discrete Latent Codes for Program Synthesis—0
PLANS: Neuro-Symbolic Program Learning from Videos—0
Multi-Plane Program Induction with 3D Box Priors—0
GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts—0
Learning to Execute Programs with Instruction Pointer Attention Graph Neural NetworksCode0
Dreaming with ARC—0
Automated Generation of Executable Cross-Language Background Knowledge—0
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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