Adaptive Deep Code Search
Adaptive Deep Code Search is a scholarly work, published in 2020. The main subjects of the publication include test automation, machine learning, word embedding, matching, code, software engineering, natural language processing, computer science, codebase, language model, deep learning, embedding, source code, and artificial intelligence. The authors propose AdaCS, an adaptive deep code search method that can be trained once and transferred to new codebases.