Quantum Software Engineering: Landscapes and Horizons
July 14, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jianjun Zhao
arXiv ID
2007.07047
Category
cs.SE: Software Engineering
Cross-listed
cs.PL,
quant-ph
Citations
184
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Quantum software plays a critical role in exploiting the full potential of quantum computing systems. As a result, it has been drawing increasing attention recently. This paper defines the term "quantum software engineering" and introduces a quantum software life cycle. The paper also gives a generic view of quantum software engineering and discusses the quantum software engineering processes, methods, and tools. Based on these, the paper provides a comprehensive survey of the current state of the art in the field and presents the challenges and opportunities we face. The survey summarizes the technology available in the various phases of the quantum software life cycle, including quantum software requirements analysis, design, implementation, test, and maintenance. It also covers the crucial issues of quantum software reuse and measurement.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted