Self-supervised contrastive learning for code retrieval and summarization via semantic-preserving transformations

• المؤلفون الرئيسيون: BUI, Duy Quoc Nghi, Yijun Yu, JIANG, Lingxiao
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2021
• الموضوعات: Software and its engineering; Software libraries and repositories; Information systems; Information retrieval; Software Engineering
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/6719; https://ink.library.smu.edu.sg/context/sis_research/article/7722/viewcontent/sigir21corder.pdf
• المؤسسة: Singapore Management University

We propose Corder, a self-supervised contrastive learning framework for source code model. Corder is designed to alleviate the need of labeled data for code retrieval and code summarization tasks. The pre-trained model of Corder can be used in two ways: (1) it can produce vector representation of co...