On the Use of Context in Recommending Exception Handling Code Examples

TL;DR

This paper presents a context-aware code recommendation system for exception handling, leveraging GitHub code examples and multiple features to improve developer support and code quality.

Contribution

It introduces a novel approach that combines structural, lexical, and heuristic features to recommend exception handling code snippets from open source repositories.

Findings

Outperforms four existing approaches in recommending exception handling code.

Successfully evaluated with 4,400 code examples and 65 scenarios.

Shows high promise in improving exception handling practices.

Abstract

Studies show that software developers often either misuse exception handling features or use them inefficiently, and such a practice may lead an undergoing software project to a fragile, insecure and non-robust application system. In this paper, we propose a context-aware code recommendation approach that recommends exception handling code examples from a number of popular open source code repositories hosted at GitHub. It collects the code examples exploiting GitHub code search API, and then analyzes, filters and ranks them against the code under development in the IDE by leveraging not only the structural (i.e., graph-based) and lexical features but also the heuristic quality measures of exception handlers in the examples. Experiments with 4,400 code examples and 65 exception handling scenarios as well as comparisons with four existing approaches show that the proposed approach is highly promising.