How the Sando Search Tool Recommends Queries

TL;DR

This paper discusses the integration of query recommendation techniques into the Sando local code search tool to assist developers in formulating effective search queries, addressing the challenge of unfamiliarity with their codebase.

Contribution

It introduces query recommendation methods within Sando to improve search effectiveness for developers unfamiliar with their codebase.

Findings

Developed query recommendation techniques for Sando

Empirical data shows developers often lack familiarity with codebase terms

Enhanced search assistance reduces query formulation difficulty

Abstract

Developers spend a significant amount of time searching their local codebase. To help them search efficiently, researchers have proposed novel tools that apply state-of-the-art information retrieval algorithms to retrieve relevant code snippets from the local codebase. However, these tools still rely on the developer to craft an effective query, which requires that the developer is familiar with the terms contained in the related code snippets. Our empirical data from a state-of-the-art local code search tool, called Sando, suggests that developers are sometimes unacquainted with their local codebase. In order to bridge the gap between developers and their ever-increasing local codebase, in this paper we demonstrate the recommendation techniques integrated in Sando.