Archive
Blog - posts for October 2021
Oct 25 2021
CodeMatcher performs fuzzy search
Title: CodeMatcher, Searching Code Based on Sequential Semantics of Important Query Words
Authors: Chao Liu - Xin Xia - David Lo - Zhiwe Liu - Ahmed E. Hassan - Shanping Li
Abstract: To accelerate software development, developers frequently search and reuse existing code snippets from a large-scale codebase, e.g., GitHub. Over the years, researchers proposed many information retrieval (IR)-based models for code search, but they fail to connect the semantic gap between query and code. An early successful deep learning (DL)-based model DeepCS solved this issue by learning the relationship between pairs of code methods and corresponding natural language descriptions.
Two major advantages of DeepCS are the capability of understanding irrelevant/noisy keywords and capturing sequential relationships between words in query and code. In this article, we proposed an IR-based model CodeMatcher that inherits the advantages of DeepCS (i.e., the capability of understanding the sequential semantics in important query words), while it can leverage the indexing technique in the IR-based model to accelerate the search response time substantially.
Oct 08 2021
ISD 2021, Valencia
Date: 8-10/10/2021
Place: Valencia and online
Authors: Extracting knowledge from software artefacts to assist software project stakeholders
Speaker: Miriam Gil, Victoria Torres, Manoli Albert, and Vicente Pelechano (UPV)
ISD 2021
A DECODER presentation and accepted scientific paper were provided at the 29th International Conference on Information Systems Development.