Quantum Pattern Detection: Accurate State- and Circuit-based Analyses

TL;DR

This paper introduces a framework for automatic quantum pattern detection using state- and circuit-based analysis, significantly improving detection accuracy and providing a benchmark dataset for quantum software engineering.

Contribution

It presents a novel framework for quantum pattern detection and a benchmarking dataset, addressing the gap between theoretical patterns and source code implementation.

Findings

Framework detects quantum patterns with high accuracy

Outperforms existing quantum pattern detection methods

Provides a dataset for benchmarking detection approaches

Abstract

Quantum computers have the potential to solve certain problems faster than classical computers by exploiting quantum mechanical effects such as superposition. However, building high-quality quantum software is challenging due to the fundamental differences between quantum and traditional programming and the lack of abstraction mechanisms. To mitigate this challenge, researchers have introduced quantum patterns to capture common high-level design solutions to recurring problems in quantum software engineering. In order to utilize patterns as an abstraction level for implementation, a mapping between the theoretical patterns and the source code is required, which has only been addressed to a limited extent. To close this gap, we propose a framework for the automatic detection of quantum patterns using state- and circuit-based code analysis. Furthermore, we contribute a dataset for benchmarking quantum pattern detection approaches. In an empirical evaluation, we show that our framework is able to detect quantum patterns very accurately and that it outperforms existing quantum pattern detection approaches in terms of detection accuracy.