TPGen: A Self-Stabilizing GPU-Based Method for Prime and Test Paths Generation

TL;DR

TPGen is a highly efficient, self-stabilizing GPU-based method for generating prime and test paths in complex software, significantly outperforming existing approaches in speed and memory usage.

Contribution

It introduces TPGen, a novel GPU-based approach with a hierarchical memory allocation and self-stabilizing design for efficient path generation in complex programs.

Findings

Outperforms existing methods in time and space efficiency

Capable of handling programs with high cyclomatic and Npath complexity

Operates without atomic instructions in an asynchronous, order-oblivious manner

Abstract

This paper presents a novel scalable GPU-based method for Test Paths (TPs) and Prime Paths (PPs) Generation, called TPGen, used in structural testing and in test data generation. TPGen outperforms existing methods for PPs and TPs generation in several orders of magnitude, both in time and space efficiency. Improving both time and space efficiency is made possible through devising a new non-contiguous and hierarchical memory allocation method, called Three-level Path Access Method (TPAM), that enables efficient storage of maximal simple paths in memory. In addition to its high time and space efficiency, a major significance of TPGen includes its self-stabilizing design where threads execute in a fully asynchronous and order-oblivious way without using any atomic instructions. TPGen can generate PPs and TPs of structurally complex programs that have an extremely high cyclomatic and Npath complexity.