[Paper Review] QDLC -- The Quantum Development Life Cycle

Nivedita Dey, Mrityunjay Ghosh+2 more|arXiv (Cornell University)|Oct 15, 2020

Cloud Computing and Resource Management4 citations

TL;DR

This paper proposes a Quantum Development Life Cycle (QDLC) model—structured as a Quantum Waterfall model—to systematize quantum software development, addressing the lack of standardized methodologies for quantum application development. It outlines distinct phases from feasibility study to quality management, enabling structured, cost-effective development of quantum applications despite hardware limitations and noise in near-term quantum systems.

ABSTRACT

The magnificence grandeur of quantum computing lies in the inherent nature of quantum particles to exhibit true parallelism, which can be realized by indubitably fascinating theories of quantum physics. The possibilities opened by quantum computation (QC) is no where analogous to any classical simulation as quantum computers can efficiently simulate the complex dynamics of strongly correlated inter-facial systems. But, unfolding mysteries and leading to revolutionary breakthroughs in quantum computing are often challenged by lack of research and development potential in developing qubits with longer coherence interval, scaling qubit count, incorporating quantum error correction to name a few. Putting the first footstep into explorative quantum research by researchers and developers is also inherently ambiguous - due to lack of definitive steps in building up a quantum enabled customized computing stack. Difference in behavioral pattern of underlying system, early-stage noisy device, implementation barriers and performance metric cause hindrance in full adoption of existing classical SDLC suites for quantum product development. This in turn, necessitates to devise systematic and cost-effective techniques to quantum software development through a Quantum Development Life Cycle (QDLC) model, specifying the distinguished features and functionalities of quantum feasibility study, quantum requirement specification, quantum system design, quantum software coding and implementation, quantum testing and quantum software quality management.

Motivation & Objective

• Address the absence of standardized development methodologies for quantum software, which hinders systematic progress in quantum computing research and application development.
• Overcome the limitations of classical SDLC models in handling quantum-specific challenges such as qubit coherence, noise, and measurement collapse.
• Provide a systematic framework for quantum software development that spans feasibility analysis, requirement specification, system design, coding, testing, and quality management.
• Facilitate the transition from theoretical quantum algorithms to deployable quantum applications by integrating quantum error correction and optimization techniques.
• Support near-term quantum development in the Noisy Intermediate-Scale Quantum (NISQ) era by offering a scalable, modular, and cost-effective development lifecycle.

Proposed method

• Proposes a Quantum Waterfall model as a structured, phase-gated approach to quantum software development, analogous to classical SDLC but adapted for quantum-specific constraints.
• Introduces dedicated phases: quantum feasibility study, quantum requirement specification (hardware and software), quantum system design, quantum coding and implementation, quantum testing via state reconstruction, and quantum software quality management (QSQM).
• Emphasizes quantum state reconstruction and verification tools for testing, replacing classical debugging by enabling non-collapsing state analysis where possible.
• Incorporates optimization techniques at compilation and hardware mapping levels to reduce circuit depth and width, minimizing runtime and resource overhead.
• Integrates quantum error correction (QEC) analysis into the development lifecycle to estimate overheads and guide design decisions for future fault-tolerant quantum computers (FTQC).
• Supports iterative refinement of quantum circuits through post-QEC performance analysis and trade-off evaluation between resource usage and operational accuracy.

Experimental results

Research questions

• RQ1 How can a systematic, scalable, and cost-effective development lifecycle be established for quantum software, given the unique constraints of quantum hardware?
• RQ2 What are the key differences between classical SDLC and a quantum-specific development model that accommodate quantum-specific challenges like qubit decoherence and measurement collapse?
• RQ3 How can quantum feasibility and requirement analysis be structured to guide hardware-software co-design in the NISQ era?
• RQ4 What techniques enable effective testing and verification of quantum programs without collapsing the quantum state?
• RQ5 How can quantum software quality management be implemented across abstraction layers—from algorithm compilation to full hardware deployment?

Key findings

• The proposed QDLC model provides a structured, phase-wise framework for quantum software development that addresses the lack of standardized methodologies in quantum R&D.
• Quantum testing is enabled through quantum state reconstruction and verification tools, circumventing the limitations of classical debugging due to wavefunction collapse.
• Optimization techniques during compilation and circuit mapping significantly reduce circuit depth and width, improving runtime efficiency and reducing resource overhead.
• Post-quantum error correction (QEC) performance analysis allows for informed trade-offs between logical qubit fidelity and physical resource costs.
• The QDLC model supports both near-term NISQ applications and long-term fault-tolerant quantum computing (FTQC) development by integrating error resilience and scalability considerations early.
• The model enables a systematic transition from algorithm design to deployment, strengthening research and development in quantum computing through standardized, repeatable processes.