Quantum Software Engineering

Preface
	Overview
	Organization
	Target Readership
	References
Acknowledgments
Contents
List of Contributors
List of Abbreviations
Chapter 1: Quantum Computing Foundations
	1.1 Introduction
		1.1.1 Problems Quantum Computing Can Address and Some Applications
	1.2 Models of Quantum Computing
		1.2.1 Gate-Based Quantum Computers
		1.2.2 Adiabatic Quantum Computers and Quantum Annealers
		1.2.3 Measurement-Based Quantum Computers
	1.3 Elements of the Quantum Circuit Model
		1.3.1 Qubits
		1.3.2 Measurements
		1.3.3 Quantum Gates
		1.3.4 Quantum Circuits
	1.4 Some Quantum Algorithms
		1.4.1 Generating Random Bits with a Quantum Circuit
		1.4.2 Creating Entanglement
		1.4.3 Deutsch´s Algorithm
		1.4.4 Advanced Algorithms
	1.5 Quantum Adiabatic Computing and Quantum Annealing
	1.6 Conclusions
	References
Chapter 2: Quantum Software Engineering Landscape and Challenges
	2.1 Introduction
	2.2 Software Engineering Evolution
	2.3 The Talavera Manifesto
	2.4 Software Engineering Techniques
	2.5 Software Engineering Environments
	2.6 Lack of Standardization
	2.7 Software Engineering Education
	2.8 Collaboration Between Industry and Academia
	2.9 Conclusions
	References
Chapter 3: Quantum Information Technology Governance System
	3.1 Quantum Technology and IT Governance
	3.2 Quantum Information Technology Governance System Design
		3.2.1 Step 1: Understand the Enterprise Context and Strategy
			3.2.1.1 Enterprise Strategy
			3.2.1.2 Enterprise Goals
			3.2.1.3 Risk Category
			3.2.1.4 Quantum Information Technology: Related Issues
		3.2.2 Step 2: Determine the Initial Scope of the QITGS
		3.2.3 Step 3: Refine the Scope of the QITGS
			3.2.3.1 Threat Landscape
			3.2.3.2 Compliance Requirements
			3.2.3.3 Role of Technology
			3.2.3.4 Sourcing Model for Technology
			3.2.3.5 Technology Implementation Methods
			3.2.3.6 Technology Adoption Strategy
		3.2.4 Step 4: Conclude the QITGS
			3.2.4.1 Refine the Scope of the Governance System
	3.3 Quantum Information Technology Governance System
	3.4 Limitations
	3.5 Conclusions
	References
Chapter 4: Quantum Software Development Lifecycle
	4.1 Introduction
	4.2 Hybrid Quantum Applications
	4.3 Quantum Software Development Lifecycle
		4.3.1 Interwoven Lifecycles
		4.3.2 Enclosing Lifecycle
			4.3.2.1 Requirement Analysis
			4.3.2.2 Quantum-Classical Splitting
			4.3.2.3 Architecture and Design
			4.3.2.4 Implementation
			4.3.2.5 Testing
			4.3.2.6 Deployment
			4.3.2.7 Observability
			4.3.2.8 Analysis
		4.3.3 Quantum Workflow Lifecycle
			4.3.3.1 Modeling
			4.3.3.2 Quantum-Classical Splitting
			4.3.3.3 IT Refinement
			4.3.3.4 Deployment
			4.3.3.5 Observability
			4.3.3.6 Analysis
		4.3.4 Quantum Circuit Lifecycle
			4.3.4.1 Quantum-Classical Splitting
			4.3.4.2 Hardware-Independent Implementation
			4.3.4.3 Testing and Verification
			4.3.4.4 Quantum Circuit Enrichment
			4.3.4.5 Quantum Hardware Selection
			4.3.4.6 Optimization and Compilation
			4.3.4.7 Execution
			4.3.4.8 Error Mitigation
		4.3.5 Operations Lifecycle
			4.3.5.1 Topology Modeling
			4.3.5.2 Packaging
			4.3.5.3 Policy Specification
			4.3.5.4 Deployment
			4.3.5.5 Observability
	4.4 Discussion
	4.5 Related Work
	4.6 Conclusion and Outlook
	References
Chapter 5: Formal Methods for Quantum Software Engineering
	5.1 Introduction
	5.2 Overture to Formal Methods
	5.3 The Z Specification Language
	5.4 An Introduction to the Quantum Computing Observable
		5.4.1 Formalizing the Observable
		5.4.2 The Observable Operators
	5.5 A Practical Example of F-QSE: Programming the Deutsch Algorithm from Specifications
	5.6 Another Practical Example of F-QSE: The Quantum Teleportation Protocol
	5.7 Conclusions and Outlooks
	Appendix
		A.1 Coding of Typical Quantum Operators
			A.1.1 QO for the Deutsch Algorithm
			A.1.2 QO for the Quantum Teleportation Protocol
	References
Chapter 6: A Quantum Software Modeling Language
	6.1 Introduction
	6.2 Fundamental Axiom of Quantum Software Engineering
	6.3 Design Principles for a Quantum Software Modeling Language
	6.4 Q-UML
		6.4.1 UML
		6.4.2 Q-UML Extensions
			6.4.2.1 Class and Object Diagrams
		6.4.3 Activity and State Diagrams
		6.4.4 Sequence Diagrams
		6.4.5 Discussion and Further Reading
	References
Chapter 7: Quantum Software Models: Density Matrix for Universal Software Design
	7.1 Introduction
		7.1.1 Bipartite Graph and Its Laplacian Matrix
		7.1.2 From Laplacian to Density Matrix
		7.1.3 Density Matrix for Universal Software Design
		7.1.4 Chapter Organization
	7.2 Quantum-Wise Universal Software Design Theory
		7.2.1 Modules as Sub-spaces of the Software System State Space
		7.2.2 Number and Components of Software Modules
		7.2.3 Quantum Modularization Procedure
		7.2.4 Universality of Software Design
	7.3 Quantum Software Design
		7.3.1 From Quantum Circuit to Density Matrix
		7.3.2 First Quantum Case Study: Deutsch Algorithm
			7.3.2.1 Key Points: Deutsch Algorithm
		7.3.3 Second Quantum Case Study: Grover Search
			7.3.3.1 Key Points: Grover Search
	7.4 Classical Software Design
		7.4.1 From Class Diagram to Density Matrix
		7.4.2 First Classical Case Study: Command Design Pattern
			7.4.2.1 Key Points: Command Design Pattern
		7.4.3 Second Classical Case Study: Firefox for iOS
	7.5 Hybrid Software System Design
		7.5.1 Hybrid Architecture: ``Quantum Data, Classical Control´´
		7.5.2 First Hybrid Case Study: Teleportation Protocol
			7.5.2.1 Key Points: Teleportation Protocol
		7.5.3 Second Hybrid Case Study: Quantum Co-processor
			7.5.3.1 Key Points: Quantum Co-processor
	7.6 Related Work
		7.6.1 Modularity: Laplacian and Density Matrix
		7.6.2 Hybrid Software Systems: Architecture and Formalization
		7.6.3 Design Universality
	7.7 Discussion
		7.7.1 Universality of Quantum, Classical, and Hybrid Design
		7.7.2 Classical Software Systems as Classical Limit of Quantum Systems
		7.7.3 Software Duality as State and Operator
		7.7.4 Future Work
		7.7.5 Main Contribution
	References
Chapter 8: Quantum Service-Oriented Architectures: From Hybrid Classical Approaches to Future Stand-Alone Solutions
	8.1 Introduction
	8.2 Background
	8.3 Current Status of Quantum Microservices: The Amazon Braket Case Study
		8.3.1 Main Quantum Computing Approaches
			8.3.1.1 Prime Factoring
			8.3.1.2 Traveling Salesperson Problem (TSP)
		8.3.2 Limitations of Getting Service-Oriented Computing Benefits in Quantum Computing Environments
	8.4 Directions for a Future QSOC
	8.5 Related Works
	8.6 Conclusion
	References
Chapter 9: Quantum Software Testing: Current Trends and Emerging Proposals
	9.1 Introduction
	9.2 Current Trends on Quantum Software Testing
		9.2.1 Overview Proposals
		9.2.2 Frameworks
		9.2.3 Probabilistic Testing and Verification
		9.2.4 Hoare Logic Applications
		9.2.5 Reversible Circuits Testing
		9.2.6 Analysis of the Current State of the Art
	9.3 From Classic to Quantum Software Testing: Redefining the Mutation Technique
		9.3.1 Introduction
		9.3.2 Quantum Specific Errors and Operators
	9.4 Quantum Mutation Support Tool
		9.4.1 Description of the Prototype
		9.4.2 Quantum Software Mutation Example
			9.4.2.1 Killed Mutants
			9.4.2.2 Alive Mutants
			9.4.2.3 Injured Mutants
			9.4.2.4 Showing the Analysis Results in QuMu
	9.5 Conclusions and Future Work
	References
Chapter 10: Quantum Software Measurement
	10.1 Introduction
	10.2 Background
		10.2.1 Quantum Instruction Sets
		10.2.2 High-Level Quantum Programming Languages
		10.2.3 Quantum Software Practices
		10.2.4 Quantum Software Metrics
	10.3 Some Similarities and Differences
		10.3.1 Software Artifacts in Quantum Software Engineering
		10.3.2 Diverging Programming Models
		10.3.3 Interpretations of Modularity and Separation of Concerns
		10.3.4 Specificities of Hardware Constraints and Error Correction
		10.3.5 Software Processes in Quantum Software Engineering
		10.3.6 Software Resources in Quantum Software Engineering
	10.4 Research Directions
		10.4.1 Software Size
		10.4.2 Software Structure
		10.4.3 Software Quality
		10.4.4 Resources
		10.4.5 Processes
	10.5 Conclusions and Outlook
	References
Chapter 11: Quantum Software Modernization
	11.1 Introduction
	11.2 Hybrid Information Systems
		11.2.1 Classical-Quantum Information Systems
		11.2.2 Challenges of Hybrid Information Systems
	11.3 Quantum Software Modernization
		11.3.1 Traditional Reengineering
		11.3.2 Architecture-Driven Modernization
		11.3.3 Software Modernization of Hybrid Information Systems
	11.4 Running/Application Example
		11.4.1 Reverse Engineering
		11.4.2 Restructuring
		11.4.3 Forward Engineering
	11.5 Conclusions
	References
Chapter 12: Quantum Software Tools Overview
	12.1 Quantum Software
		12.1.1 Quantum Software Layers
	12.2 Quantum Software Technologies
		12.2.1 Quantum Programming Languages
			12.2.1.1 Quantum Imperative Programming Languages
			12.2.1.2 Quantum Functional Programming Languages
			12.2.1.3 Other Quantum Programming Languages
		12.2.2 Quantum Software Simulators and Design Environments
		12.2.3 Quantum Tools and Libraries
		12.2.4 Quantum Annealing Environments
		12.2.5 Full-Stack Software of Main Quantum Computing Vendors
		12.2.6 Quantum Software Development and Run Platforms
	12.3 Current Limitations and Future Trends
	References
Chapter 13: Quantum Software Development with QuantumPath
	13.1 Introduction
	13.2 QPath Principles and Functionalities
		13.2.1 Management of Solutions and Their Assets
		13.2.2 Tools for the Design of Quantum Assets
			13.2.2.1 Circuit Editor
			13.2.2.2 Annealer Compositor
			13.2.2.3 Flow Editor
			13.2.2.4 Direct Code Editor
		13.2.3 Connection Points and qSOA
		13.2.4 Enterprise Backend
	13.3 QPath Advantages
		13.3.1 QPath Facilitates Quantum Workforce Development
		13.3.2 QPath Solves the Quality Problems of Quantum Computing Platforms
	13.4 Example of Quantum Development with QPath
	13.5 Conclusions and Future Work
	References
Chapter 14: Quantum Software Development with Classiq
	14.1 The Hardware Race Is On, But What About Software?
	14.2 The Limitations of Today´s Software Development Tools
	14.3 The Unfortunate Side Effect of Gate-Level Development Tools
	14.4 Finding a Historical Analogy
	14.5 What Is Quantum Algorithm Design?
	14.6 What Does Classiq Do?
	14.7 Where Does Quantum Algorithm Design Fit in the Quantum Software Stack?
	14.8 How Is QAD Different from a Compiler?
	14.9 What Are Constraints in the QAD Context?
	14.10 Can the Constraints Always Be Met?
	14.11 What Are the Advantages of Quantum Algorithm Design?
	14.12 If QAD Is an Abstraction Layer, Are We Losing Optimization Capabilities?
	14.13 Don´t Some Existing Tools Already Provide Building Blocks?
	14.14 The Quantum Future Is Bright
Chapter 15: Quantum Software Frameworks for Deep Learning
	15.1 Introduction
	15.2 Quantum Computing Background
	15.3 Deep Learning Background
		15.3.1 Generative Adversarial Neural Networks
		15.3.2 Convolutional Neural Networks
		15.3.3 Frameworks and Tools for Hybrid Deep Learning
	15.4 Methods and Materials
		15.4.1 Generative Adversarial Network
		15.4.2 Convolutional Neural Network
	15.5 Results and Discussion
		15.5.1 Main Take-Aways
	15.6 Conclusion
	References