arxiv: 2604.19970 · v1 · submitted 2026-04-21 · 💻 cs.SE

Recognition: unknown

Automated Quantum Software and AI Engineering

Nazanin Siavash , Armin Moin

Authors on Pith no claims yet

Pith reviewed 2026-05-10 01:33 UTC · model grok-4.3

classification 💻 cs.SE

keywords quantum software engineeringquantum artificial intelligencesystematic literature reviewautomationhybrid quantum-classical systemssoftware developmentAI engineeringquantum computing

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The pith

A systematic review maps (semi-)automated methods that can widen access to quantum software engineering and AI in hybrid systems.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper conducts a systematic literature review to gather existing (semi-)automated techniques for quantum software engineering and quantum artificial intelligence. It notes that few people hold the specialized knowledge needed for quantum computing, making automation especially important for progress on applications that mix quantum and classical components. In such hybrid cases the reviewed methods can guide choices about which parts of a program to place on quantum hardware. This matters because it targets productivity improvements that would let more developers and data scientists build and deploy quantum-enabled systems. The review further extracts trends from the literature and outlines directions for future work on these automation tools.

Core claim

By surveying the literature on (semi-)automated approaches in quantum software engineering and quantum AI, the work shows that these techniques address the shortage of quantum experts and support decisions on hardware placement within hybrid quantum-classical applications, thereby enabling wider development and deployment of such systems while highlighting current trends and open directions.

What carries the argument

The systematic literature review of (semi-)automated approaches to quantum software engineering and quantum AI, with emphasis on their application to hybrid quantum-classical systems.

If this is right

Automation helps determine which parts of an application should run on quantum hardware versus classical hardware in hybrid setups.
The methods support efficiency gains and productivity increases even when used by subject-matter experts.
Trends extracted from the reviewed approaches can guide the creation of additional tools for quantum and hybrid development.
Future work should build on the identified directions to broaden access to quantum software and AI engineering.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

The catalog of methods could be tested in practice by applying one or more reviewed techniques to a concrete hybrid application and measuring development time or error rates.
Parallels with automation successes in classical software engineering might reveal which quantum approaches are extensions of known practices.
Periodic updates to the review could track whether new automation tools close the expertise gap more effectively over time.

Load-bearing premise

The review's search and selection steps captured the full set of relevant (semi-)automated methods from the quantum software engineering and quantum AI literature without major omissions.

What would settle it

Locating multiple important papers on automated quantum software or AI tools that the review overlooked would show the identified trends and future directions are incomplete.

Figures

Figures reproduced from arXiv: 2604.19970 by Armin Moin, Nazanin Siavash.

**Figure 2.** Figure 2: depicts the overlap between QSE and QAI. Note that automated approaches enabling solutions at the intersection of QSE and QAI are the main focus of this study. III. RELATED WORK There exist various surveys on topics related to QC, QAI, QSE, AQAI, and AQSE. However, most studies focused on one of these areas as a silo. For instance, Gyongyosi and Imre [12] outlined the fundamental components essential for … view at source ↗

**Figure 3.** Figure 3: FIGURE 3 [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗

**Figure 4.** Figure 4: FIGURE 4 [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗

**Figure 5.** Figure 5: FIGURE 5 [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗

**Figure 6.** Figure 6: FIGURE 6 [PITH_FULL_IMAGE:figures/full_fig_p006_6.png] view at source ↗

**Figure 7.** Figure 7: FIGURE 7 [PITH_FULL_IMAGE:figures/full_fig_p007_7.png] view at source ↗

**Figure 8.** Figure 8: FIGURE 8 [PITH_FULL_IMAGE:figures/full_fig_p008_8.png] view at source ↗

read the original abstract

In this paper, we conduct a systematic literature review of (semi-) automated approaches to Quantum Software Engineering (QSE) and Quantum Artificial Intelligence (QAI). Prior work in the literature indicated that both Software Engineering (SE) and Artificial Intelligence (AI) practices may become more efficient by using (semi-) automated approaches. This also holds in the Quantum Computing (QC), Quantum Information Science (QIS), and Quantum Engineering (QE) world, as well as in hybrid quantum-classical applications. In fact, automation is even more crucial in such cases since there is a limited number of developers and AI experts (e.g., data scientists) who possess the required knowledge and skills in QC. Moreover, in hybrid setups, automation may help decide what part of the application should be deployed on quantum hardware and on which of the available quantum platforms, if applicable. This can be a significant help to achieve productivity leap and efficiency even for subject matter experts. Unlike prior literature reviews and surveys, this work focuses on automation in SE and AI for quantum and hybrid quantum-classical applications and identifies the recent trends and future directions through a systematic literature review. We are interested in methods and techniques that can enable a broader development and deployment of quantum and hybrid AI-enabled software systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

This is a targeted SLR on (semi-)automated tools for quantum SE and AI that could map useful trends if the search was thorough, but the value rests on whether key papers were missed.

read the letter

The paper's main point is that automation matters more in quantum work because experts are scarce and hybrid systems need help deciding what runs where. It sets out to review existing (semi-)automated methods in QSE and QAI and flag recent trends plus future directions, which is a narrower slice than most general quantum surveys cover. That focus is the clearest new angle here, and it does pull together references that could save time for someone trying to get an overview of productivity tools in this space. The motivation around stretching limited talent and supporting hybrid decisions is straightforward and matches what many in the field already feel. Credit to the authors for sticking to that practical framing instead of overclaiming new techniques. The soft spot is the execution of the review itself. The abstract gives no search strings, databases, date ranges, or inclusion rules, and if the full text does not lay those out clearly with a reproducible process, the identified trends risk being incomplete. Papers on automated circuit synthesis, hybrid partitioning tools, or specific QAI frameworks could easily fall through if the keywords were too narrow. Without that rigor, the synthesis stays descriptive rather than authoritative. No new data, derivations, or experiments appear, so the paper lives or dies by how well it covered the literature. This is for quantum software researchers or teams starting hybrid projects who want a quick map of existing automation work rather than a deep technical dive. A reader already deep in the area might find the references handy but not transformative. It deserves peer review to test whether the search and selection steps were solid enough to support the trends claimed. If the methods check out, the paper could serve as a useful starting reference; if not, it needs a major revision on coverage before publication.

Referee Report

2 major / 1 minor

Summary. The manuscript conducts a systematic literature review of (semi-)automated approaches to Quantum Software Engineering (QSE) and Quantum Artificial Intelligence (QAI). It motivates the work by noting limited expert availability in quantum computing and the potential for automation to assist hybrid quantum-classical deployment decisions, then identifies recent trends and future directions to enable broader development of quantum and hybrid AI-enabled systems.

Significance. If the SLR search and selection are shown to be comprehensive and reproducible, the review could usefully aggregate and trend-map automation techniques across QSE and QAI, providing a reference point for researchers working on productivity tools in a domain with scarce specialized expertise. The emphasis on hybrid partitioning and platform selection is a timely angle not always foregrounded in prior quantum surveys.

major comments (2)

[Methodology] Methodology section: the abstract states that a systematic literature review was performed but supplies no search strings, databases, inclusion/exclusion criteria, time bounds, or screening protocol. Without these details it is impossible to assess whether the reported trends rest on a representative corpus or suffer from systematic omissions (e.g., missing papers on automated quantum circuit synthesis or hybrid partitioning tools).
[Results and Discussion] Results/Discussion: the central claim that automation trends and future directions have been identified for hybrid quantum-classical applications depends on the completeness of the literature base. Absent a PRISMA-style flow diagram, paper counts, or explicit justification that key sub-areas were covered, the trend synthesis and recommendations cannot be evaluated for robustness.

minor comments (1)

[Abstract] Abstract: the phrase 'prior work in the literature indicated' is not accompanied by citations; adding 2-3 key references would clarify the baseline being extended.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thoughtful and constructive review. We agree that greater methodological transparency is essential for a systematic literature review and have revised the manuscript to address both major comments in full.

read point-by-point responses

Referee: [Methodology] Methodology section: the abstract states that a systematic literature review was performed but supplies no search strings, databases, inclusion/exclusion criteria, time bounds, or screening protocol. Without these details it is impossible to assess whether the reported trends rest on a representative corpus or suffer from systematic omissions (e.g., missing papers on automated quantum circuit synthesis or hybrid partitioning tools).

Authors: We agree that the original manuscript did not present these elements with sufficient explicitness. Although a methodology section existed, it omitted the precise search strings, list of databases, formal inclusion/exclusion criteria, time bounds, and screening protocol. In the revised version we have expanded the Methodology section to include: (1) the complete Boolean search strings, (2) the databases queried (IEEE Xplore, ACM DL, SpringerLink, arXiv, and Google Scholar), (3) explicit inclusion/exclusion criteria, (4) the time window 2015–2024, and (5) the two-stage screening protocol with inter-rater agreement statistics. We also added a short paragraph justifying coverage of sub-areas such as automated quantum circuit synthesis and hybrid partitioning tools. revision: yes
Referee: [Results and Discussion] Results/Discussion: the central claim that automation trends and future directions have been identified for hybrid quantum-classical applications depends on the completeness of the literature base. Absent a PRISMA-style flow diagram, paper counts, or explicit justification that key sub-areas were covered, the trend synthesis and recommendations cannot be evaluated for robustness.

Authors: We accept this criticism. The revised manuscript now contains a PRISMA flow diagram that reports the number of records at each stage (identification, screening, eligibility, inclusion). We also state the final corpus size and provide a table that maps the included papers to the key sub-areas (including automated circuit synthesis and hybrid partitioning). These additions allow readers to assess the completeness of the evidence base underlying our trend analysis and recommendations. revision: yes

Circularity Check

0 steps flagged

No circularity: SLR aggregates external sources without internal derivations or self-referential reductions

full rationale

This is a systematic literature review with no equations, fitted parameters, predictions, or derivations. The central contribution rests on standard SLR search/selection from external literature rather than any self-definitional loop, fitted-input renaming, or load-bearing self-citation chain. The paper's claims about automation needs and trends are presented as summaries of cited prior work, with no reduction of outputs to the review's own inputs by construction. Methodological assumptions about search completeness are limitations, not circularity.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

As a literature review, the paper introduces no free parameters, new axioms, or invented entities; it relies entirely on the body of existing published work in QSE and QAI.

pith-pipeline@v0.9.0 · 5513 in / 1006 out tokens · 26570 ms · 2026-05-10T01:33:27.867795+00:00 · methodology

discussion (0)

Reference graph

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