Efficient Call Path Detection for Android-OS Size of Huge Source Code

TL;DR

This paper introduces an efficient bidirectional search algorithm for detecting call paths in extremely large Android source codebases, significantly reducing path extraction time compared to traditional methods.

Contribution

It proposes a novel bidirectional search algorithm that uses referenced information to optimize call path detection in huge source code, enabling faster analysis.

Findings

Reduces call path extraction time by 8%

Handles source code too large to fit in memory

Uses referenced information to improve search efficiency

Abstract

Today most developers utilize source code written by other parties. Because the code is modified frequently, the developers need to grasp the impact of the modification repeatedly. A call graph and especially its special type, a call path, help the developers comprehend the modification. Source code written by other parties, however, becomes too huge to be held in memory in the form of parsed data for a call graph or path. This paper offers a bidirectional search algorithm for a call graph of too huge amount of source code to store all parse results of the code in memory. It refers to a method definition in source code corresponding to the visited node in the call graph. The significant feature of the algorithm is the referenced information is used not in order to select a prioritized node to visit next but in order to select a node to postpone visiting. It reduces path extraction time by 8% for a case in which ordinary path search algorithms do not reduce the time.