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About Program Synthesis
Automatically generate programs from examples, specs, or partial code using AI.
Program Synthesis refers to a category of AI and formal methods that automatically generate programs from specifications, examples, or intent. It spans tools that use deep learning, symbolic reasoning, constraint-solving, or hybrid approaches to derive code that satisfies a set of given conditions. Unlike typical code completion or suggestion tools, program synthesizers aim to generate full programs (or program fragments) that are provably correct or aligned with intent. Examples of this approach include Microsoft's PROSE (used in Excel Flash Fill), DeepCoder, Google’s AutoML CodeGen, and tools in academia like Sketch or Rosette. These systems may operate over natural language inputs, input/output examples, formal specifications, or partial code. In practical terms, program synthesis is extremely valuable for repetitive programming tasks, generating data transformation scripts, UI workflows, educational coding tools, and generating test cases. However, most implementations are limited in scale or scope and often require tight specifications to work well. Additionally, some tools are purely academic or part of internal research at large companies, which limits availability or ease of use.
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Example Prompts
Generate a script that transforms CSV data based on these rules.Create a program that outputs Fibonacci numbers based on this spec.Fill in the blanks in this partial sorting function using synthesis.