As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective—key qualities of any industry-grade software—mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software Engineering (QSE) as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyze in depth the current state of QSE research. From this analysis, the key areas of QSE are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing QSE.

Quantum computing is the latest revolution in computing and will probably come to be seen as an advance as important as the steam engine or the information society. In the last few decades, our understanding of quantum computers has expanded and multiple efforts have been made to create languages, libraries, tools, and environments to facilitate their programming. Nonetheless, quantum computers are complex systems at the bottom of a stack of layers that programmers need to understand. Hence, efforts towards creating quantum programming languages and computing environments that can abstract low-level technology details have become crucial steps to achieve a useful quantum computing technology. However, most of these environments still lack many of the features that would be desirable, such as those outlined in The Talavera Manifesto for Quantum Software Engineering and Programming. For advancing quantum computing, we will need to develop quantum software engineering techniques and tools to ensure the feasibility of this new type of quantum software. To contribute to this goal, this paper provides a review of the main quantum software components and platforms. We also propose a set of quality requirements for the development of quantum software platforms and the conduct of their quality assessment.

Developers of the many promising quantum computing applications that currently exist are urging companies in many different sectors seriously consider integrating this new technology into their business. For these applications to function, not only are quantum computers required, but quantum software also. Accordingly, quantum software engineering has become an important research field, in that it attempts to apply or adapt existing methods and techniques (or propose new ones) for the analysis, design, coding, and testing of quantum software, as well as playing a key role in ensuring quality in large-scale productions. The design of quantum software nevertheless poses two main challenges: the modelling of software quantum elements must be done in high-level modelling languages; and the need to further develop so-called “hybrid information systems”, which combine quantum and classical software. To address these challenges, we first propose a quantum UML profile for analysing and designing hybrid information systems; we then demonstrate its applicability through various structural and behavioural diagrams such as use case, class, sequence, activity, and deployment. In comparison to certain other quantum domain-specific languages, this UML profile ensures compliance with a well-known international standard that is supported by many tools and is followed by an extensive community.

Energy efficiency and other sustainability issues are common concerns in the material production industries but rarely addressed in software development efforts. Instead, traditional software development life cycles and methodologies place an emphasis on maintainability and other intrinsic software quality features. One standard practice is to improve maintainability by detecting bad smells in a system's architecture and then applying refactoring transformations to deal with those smells. The refactoring research area is sufficiently mature for most techniques to achieve more maintainable system architectures, but the authors argue that they can also lead to both decreased sustainability and increased power consumption. Accordingly, this article analyzes the relationship between architecture sustainability and maintainability by providing empirical evidence of how power consumption increases after refactoring.

As information systems age they become legacy information systems (LISs), embedding business knowledge not present in other artefacts. LISs must be modernised when their maintainability falls below acceptable limits but the embedded business knowledge is valuable information that must be preserved to align the modernised versions of LISs with organisations' real-world business processes. Business process mining permits the discovery and preservation of all meaningful embedded business knowledge by using event logs, which represent the business activities executed by an information system. Event logs can be easily obtained through the execution of process-aware information systems (PAISs). However, several non-process-aware information systems also implicitly support organisations' business processes. This article presents a technique for obtaining event logs from traditional information systems (without any in-built logging functionality) by statically analysing and modifying LISs. The technique allows the modified systems to dynamically record event logs. The approach is validated with a case study involving a healthcare information system used in Austrian hospitals, which shows the technique obtains event logs that effectively and efficiently enable the discovery of embedded business processes. This implies the techniques provided within the process mining field, which are based on event logs, may also be applied to traditional information systems.