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

Showing 401423 of 423 papers

TitleStatusHype
Neural Program Search: Solving Data Processing Tasks from Description and Examples0
Dynamic Neural Program Embeddings for Program Repair0
Code Synthesis with Priority Queue Training0
Dynamic Neural Program Embedding for Program RepairCode0
Selecting Representative Examples for Program SynthesisCode0
Glass-Box Program Synthesis: A Machine Learning Approach0
A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selectionCode0
Learning to Infer Graphics Programs from Hand-Drawn ImagesCode0
P-Tree ProgrammingCode0
LoopInvGen: A Loop Invariant Generator based on Precondition Inference0
Learning Disjunctions of Predicates0
Towards Synthesizing Complex Programs from Input-Output Examples0
RobustFill: Neural Program Learning under Noisy I/OCode1
Synthesizing Imperative Programs from Examples Guided by Static Analysis0
Summary - TerpreT: A Probabilistic Programming Language for Program Induction0
Sampling for Bayesian Program Learning0
Time Series Structure Discovery via Probabilistic Program Synthesis0
Latent Attention For If-Then Program Synthesis0
Differentiable Functional Program InterpretersCode0
DeepCoder: Learning to Write ProgramsCode0
Neuro-Symbolic Program Synthesis0
TerpreT: A Probabilistic Programming Language for Program Induction0
Unsupervised Learning by Program Synthesis0
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Benchmark Results

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