Ambiguity Resolution with Human Feedback for Code Writing Tasks

Aditey Nandan, Viraj Kumar
8/18/2025
cs.SEcs.AI

No official code found. Best implementation: Nandan-Aditey/ARHF (1 star, MIT, last commit 2025-09-26). 1 more below.

Abstract

Specifications for code writing tasks are usually expressed in natural language and may be ambiguous. Programmers must therefore develop the ability to recognize ambiguities in task specifications and resolve them by asking clarifying questions. We present and evaluate a prototype system, based on a novel technique (ARHF: Ambiguity Resolution with Human Feedback), that (1) suggests specific inputs on which a given task specification may be ambiguous, (2) seeks limited human feedback about the code's desired behavior on those inputs, and (3) uses this feedback to generate code that resolves these ambiguities. We evaluate the efficacy of our prototype, and we discuss the implications of such assistive systems on Computer Science education.

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Code Implementations(2)

Nandan-Aditey/ARHFCommunity73%
MIT

Repository containing code for ARHF: Ambiguity Resolution with Human Feedback for Code Writing Tasks

10CSS, HTMLAug 26, 20251 years agoMIT
MIT

This repository contains the prompts, problems, and figures related to the paper: Ambiguity Resolution with Human Feedback for Code Writing Tasks

00PythonAug 16, 20251 years agoMIT

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Cite this paper

@article{nandan2025ambiguity,
  title  = {Ambiguity Resolution with Human Feedback for Code Writing Tasks},
  author = {Aditey Nandan and Viraj Kumar},
  year   = {2025},
  eprint = {2508.14114},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.14114v1}
}

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