QuanFuzz: Fuzz Testing of Quantum Program

October 16, 2018 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Jiyuan Wang, Ming Gao, Yu Jiang, Jianguang Lou, Yue Gao, Dongmei Zhang, Jiaguang Sun arXiv ID 1810.10310 Category cs.SE: Software Engineering Citations 34 Venue arXiv.org Last Checked 4 months ago
Abstract
Nowadays, quantum program is widely used and quickly developed. However, the absence of testing methodology restricts their quality. Different input format and operator from traditional program make this issue hard to resolve. In this paper, we present QuanFuzz, a search-based test input generator for quantum program. We define the quantum sensitive information to evaluate test input for quantum program and use matrix generator to generate test cases with higher coverage. First, we extract quantum sensitive information -- measurement operations on those quantum registers and the sensitive branches associated with those measurement results, from the quantum source code. Then, we use the sensitive information guided algorithm to mutate the initial input matrix and select those matrices which improve the probability weight for a value of the quantum register to trigger the sensitive branch. The process keeps iterating until the sensitive branch triggered. We tested QuanFuzz on benchmarks and acquired 20% - 60% more coverage compared to traditional testing input generation.
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