Code Search

Motivation

Software plays a crucial role in the society, influencing various aspects of daily lives. During the development of a software, writing source codes is the core activity for software engineers. However, developing reliable codes is costly because it requires constantly references to documentations and online resources and making sense of the logic behind existing code bases. These are both challenging and could slow down the developing process.

We are motivated by this and would seek to model the relations between natural language queries and source code snippets in order to help increasing the efficiency of software development.

This capstone project is interdisciplinary, that requires us to apply skills or investigate issues across many different Ischool subject areas such as Machine Learning, Natural Language Processing and Web Application. In addition, we hope Code Search to be a user-friendly application, so we will consider not only the model accuracy but the user experience to meet the needs of all kinds of programming users.

Winnie Lee


initiated the idea of modeling the relations between source code and natural language query. In addition, after reading related topics of papers, Winnie mainly set the different stages of goals for this capstone projects, and gained supports from HackMD. Also, Winnie will implement Natural Language Processing algorithms.

Erica Chen


has been focusing on Data Science and generated ideas regarding Machine Learning and Natural Language Processing. Erica will primarily be in charge of either the Information Retrieval design or Natural Language Processing implementation, depending on the further project execution we are going to do.

Yu-Cheng Lin


took more roles in platform or web development, providing examples of several existing or discontinued services of code search for the early-stage discussion. In developing phase, Yu-Cheng will put more effort in building the website along with the functionality and validations of the query services.