Math and Physics Tools for Quality Quantum Programming

Luciano Marrero, Verena Olsowy, Juan Fernández Sosa +4 more

Ajay Kumar, Prisha Kwatra, Sunita Garhwal

Abstract Software testing is an important activity to ensure the software's quality. Mutation testing is a fault-based technique for checking the effectiveness of test cases for the verification and validation of software. Testing quantum programs is challenging due to the involvement of quantum mechanics concepts (such as superposition and entanglement ) and the probabilistic nature of the outcome. In this paper, We will propose the modified mutation testing approach for quantum program. The proposed approach will help to reduce the cost, time, and effort of performing the mutation testing. Moreover, we also propose a method for determining the equivalent mutant and developing a tool to check whether the mutated and original quantum program behave semantically equivalent or differently.

Jarosław Adam Miszczak

Ajay Kumar, Prisha Kwatra, Sunita Garhwal

Abstract Software testing is an important activity to ensure the software's quality. Mutation testing is a fault-based technique for checking the effectiveness of test cases for the verification and validation of software. Testing quantum programs is challenging due to the involvement of quantum mechanics concepts (such as superposition and entanglement ) and the probabilistic nature of the outcome. In this paper, We will propose the modified mutation testing approach for quantum program. The proposed approach will help to reduce the cost, time, and effort of performing the mutation testing. Moreover, we also propose a method for determining the equivalent mutant and developing a tool to check whether the mutated and original quantum program behave semantically equivalent or differently.

Seung Yeob Shin, Fabrizio Pastore, Domenico Bianculli

Ensuring the quality of quantum programs is increasingly important; however, traditional static analysis techniques are insufficient due to the unique characteristics of quantum computing. Quantum-specific linting tools, such as LintQ, have been developed to detect quantum-specific programming problems; however, they typically rely on manually crafted analysis queries. The manual effort required to update these tools limits their adaptability to evolving quantum programming practices. To address this challenge, this study investigates the feasibility of employing Large Language Models (LLMs) to develop a novel linting technique for quantum software development and explores potential avenues to advance linting approaches. We introduce LintQ-LLM, an LLM-based linting tool designed to detect quantum-specific problems comparable to those identified by LintQ. Through an empirical comparative study using realworld Qiskit programs, our results show that LintQ-LLM is a viable solution that complements LintQ, with particular strengths in problem localization, explanation clarity, and adaptability potential for emerging quantum programming frameworks, thus providing a basis for further research. Furthermore, this study discusses several research opportunities for developing more advanced, adaptable, and feedback-aware quantum software quality assurance methods by leveraging LLMs.

Bettina Heim, Mathias Soeken, Sarah Marshall +5 more