Program Synthesis
138 papers with code • 3 benchmarks • 5 datasets
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.
Benchmarks
These leaderboards are used to track progress in Program Synthesis
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Libraries
Use these libraries to find Program Synthesis models and implementations
CONCODE
SPoC
SketchGraphs
xCodeEval
Subtasks
Most implemented papers
Knowledge-Driven Robot Program Synthesis from Human VR Demonstrations
Aging societies, labor shortages and increasing wage costs call for assistance robots capable of autonomously performing a wide array of real-world tasks.
Differentiable Functional Program Interpreters
ethancaballero/neural-engineers-first-attempt
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Recent work on differentiable interpreters relaxes the discrete space of programs into a continuous space so that search over programs can be performed using gradient-based optimization.
P-Tree Programming
From this prototype tree we form program instances which we evaluate on a given problem.
Learning to Infer Graphics Programs from Hand-Drawn Images
These drawing primitives are like a trace of the set of primitive commands issued by a graphics program.
A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection
Lexicase selection is a parent selection method that considers training cases individually, rather than in aggregate, when performing parent selection.
Selecting Representative Examples for Program Synthesis
evanthebouncy/icml2018_selecting_representative_examples
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ICML 2018
Program synthesis is a class of regression problems where one seeks a solution, in the form of a source-code program, mapping the inputs to their corresponding outputs exactly.
Dynamic Neural Program Embedding for Program Repair
keowang/dynamic-program-embedding
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Evaluation results show that our new semantic program embedding significantly outperforms the syntactic program embeddings based on token sequences and abstract syntax trees.
Recent Advances in Neural Program Synthesis
In recent years, deep learning has made tremendous progress in a number of fields that were previously out of reach for artificial intelligence.
Neural Program Synthesis from Diverse Demonstration Videos
shaohua0116/demo2program
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ICML 2018
To empower machines with this ability, we propose a neural program synthesizer that is able to explicitly synthesize underlying programs from behaviorally diverse and visually complicated demonstration videos.
NAPS: Natural Program Synthesis Dataset
We present a program synthesis-oriented dataset consisting of human written problem statements and solutions for these problems.
