Clone-based code method usage pattern mining

TL;DR

This paper introduces LUPIN, a method that mines usage patterns of code methods by leveraging cloned code, enabling better understanding of methods with limited usage information.

Contribution

LUPIN is a novel approach that extracts usage patterns from cloned code to assist in understanding methods with scarce usage examples.

Findings

LUPIN achieves an average precision of 0.65 in pattern mining.

It successfully mines four categories of usage patterns.

The approach enhances understanding of code methods with limited usage data.

Abstract

When programmers retrieve a code method and want to reuse it, they need to understand the usage patterns of the retrieved method. However, it is difficult to obtain usage information of the retrieved method since this method may only have a brief comment and few available usage examples. In this paper, we propose an approach, called LUPIN (cLone-based Usage Pattern mIniNg), to mine the usage patterns of these methods, which do not widely appeared in the code repository. The key idea of LUPIN is that the cloned code of the target method may have a similar usage pattern, and we can collect more usage information of the target method from cloned code usage examples. From the amplified usage examples, we mine the usage pattern of the target method by frequent subsequence mining after program slicing and code normalization. Our evaluation shows that LUPIN can mine four categories of usage patterns with an average precision of 0.65.