咨询与建议

看过本文的还看了

相关文献

该作者的其他文献

文献详情 >Programming by Example Made Ea... 收藏
arXiv

Programming by Example Made Easy

作     者:Wu, Jiarong Wei, Lili Jiang, Yanyan Cheung, Shing-Chi Ren, Luyao Xu, Chang 

作者机构:Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Department of Electrical and Computer Engineering McGill University Montreal Canada State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China Key Lab of High Confidence Software Technologies Ministry of Education Department of Computer Science and Technology EECS Peking University Beijing China 

出 版 物:《arXiv》 (arXiv)

年 卷 期:2023年

核心收录:

主  题:Problem oriented languages 

摘      要:Programming by example (PBE) is an emerging programming paradigm that automatically synthesizes programs specified by user-provided input-output examples. Despite the convenience for end-users, implementing PBE tools often requires strong expertise in programming language and synthesis algorithms. Such a level of knowledge is uncommon among software developers. It greatly limits the broad adoption of PBE by the industry. To facilitate the adoption of PBE techniques, we propose a PBE framework called Bee, which leverages an entity-action model based on relational tables to ease PBE development for a wide but restrained range of domains. Implementing PBE tools with Bee only requires adapting domain-specific data entities and user actions to tables, with no need to design a domain-specific language or an efficient synthesis algorithm. The synthesis algorithm of Bee exploits bidirectional searching and constraint-solving techniques to address the challenge of value computation nested in table transformation. We evaluated Bee’s effectiveness on 64 PBE tasks from three different domains and usability with a human study of 12 participants. Evaluation results show that Bee is easier to learn and use than the state-of-the-art PBE framework, and the bidirectional algorithm achieves comparable performance to domain-specifically optimized synthesizers. Copyright © 2023, The Authors. All rights reserved.

读者评论 与其他读者分享你的观点

用户名:未登录
我的评分