Quantum Tests

Xinyi Wang, Paolo Arcaini, Tao Yue +1 more

The inherent complexity of quantum programs, due to features such as superposition and entanglement, makes their testing particularly challenging. To tackle these challenges, we present a search-based approach, called Quantum Search-Based Testing (QuSBT), for automatically generating test suites of a given size that possibly expose failures of the quantum program under test. QuSBT encodes a test suite as a search individual, and tries to maximize the objective function that counts the number of failing tests in the test suite. Due to non-deterministic nature of quantum programs, the approach repeats the execution of each test multiple times, and uses suitable statistical tests to assess if a test passes or fails. QuSBT employs a genetic algorithm to perform the search. Experiments on 30 faulty quantum programs show that QuSBT is statistically better than random search, and is able to efficiently generate maximal failing test suites.

Anonymous

Peixun Long, Jianjun Zhao

Errors in quantum programs are challenging to track down due to the uncertainty of quantum programs. Testing is, therefore, an indispensable method for assuring the quality of quantum software. Existing testing methods focus only on testing quantum programs with quantum circuits or single subroutines and, therefore, cannot effectively test quantum programs with multi-subroutines. In this paper, we first discuss several critical issues that must be considered when testing multi-subroutine quantum programs and point out the limitations and problems with existing testing methods. We then present a novel framework for testing multi-subroutine quantum programs that allow for both unit and integration testing. Our framework includes two novel test coverage criteria for the equivalent class partition of quantum variables to guide our testing tasks and techniques to test quantum programs with several common patterns. We also discuss how to generate test cases based on our framework. To evaluate the effectiveness of our testing framework, we implemented a tool called QSharpTester for testing Q\# programs with multiple subroutines. We used it to conduct experiments on hundreds of mutation programs deriving from seven original Q\# programs. The experimental results show that our testing methods can deal with broader types of quantum programs than existing ones and perform well on almost all faulty mutation programs.

Nguyen Ba An

Peixun Long, Jianjun Zhao

Quantum computing has emerged as a promising field with the potential to revolutionize various domains by harnessing the principles of quantum mechanics. As quantum hardware and algorithms continue to advance, developing high-quality quantum software has become crucial. However, testing quantum programs poses unique challenges due to the distinctive characteristics of quantum systems and the complexity of multi-subroutine programs. This article addresses the specific testing requirements of multi-subroutine quantum programs. We begin by investigating critical properties by surveying existing quantum libraries and providing insights into the challenges of testing these programs. Building upon this understanding, we focus on testing criteria and techniques based on the whole testing process perspective, spanning from unit testing to integration testing. We delve into various aspects, including IO analysis, quantum relation checking, structural testing, behavior testing, integration of subroutine pairs, and test case generation. We also introduce novel testing principles and criteria to guide the testing process. We conduct comprehensive testing on typical quantum subroutines, including diverse mutants and randomized inputs, to evaluate our proposed approach. The analysis of failures provides valuable insights into the effectiveness of our testing methodology. Additionally, we present case studies on representative multi-subroutine quantum programs, demonstrating the practical application and effectiveness of our proposed testing principles and criteria.

Christopher R. Monroe, Robert J. Schoelkopf, Mikhail D. Lukin