QuanFuzz: Fuzz Testing of Quantum Program
October 16, 2018 Β· Declared Dead Β· π 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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