Stuart M. Allen, Neil Chue Hong, Stephan Druskat
et al.
Research Software Engineering (RSEng) is a key success factor in producing high-quality research software, which in turn enables and improves research outcomes. However, as a principal investigator or leader of a research group you may not know what RSEng is, where to get started with it, or how to use it to maximize its benefit for your research. RSEng also often comes with technical complexity, and therefore reduced accessibility to some researchers. The ten simple rules presented in this paper aim to improve the accessibility of RSEng, and provide practical and actionable advice to PIs and leaders for integrating RSEng into their research group. By following these rules, readers can improve the quality, reproducibility, and trustworthiness of their research software, ultimately leading to better, more reproducible and more trustworthy research outcomes.
Matthieu Sineau, Manuel Hellot, Robin Mafféïs
et al.
Railway transportation contributes to the objectives of decarbonization but also generates negative externalities, including noise. Energy noise indicators used to characterize population exposure do not adequately reflect the repetitive nature of railway noise peaks. The GENIFER pilot study aims to test a protocol designed to characterize railway noise events according to the instantaneous perceived annoyance when the train is passing, in order to improve understanding of the influence of acoustic factors on annoyance. The first phase of the survey was carried out in 2023 among 62 residents of a pilot site. An electronic device was used to collect around 5,000 ratings, ranging from 1 to 10, assessing the instantaneous annoyance induced by railway noise at passing trains. The site instrumentation included sixteen sound level meters and two video recording systems, enabling annoyance ratings to be associated with the acoustic characteristics of railway noise events. A questionnaire aimed at identifying co-determinants of long-term annoyance was also administered to participants. Feedback on the field implementation of this survey and initial results concerning acoustic measurements, instantaneous annoyance ratings and questionnaire responses will be presented.
This short paper explores how a maritime company develops and integrates large-language models (LLM). Specifically by looking at the requirements engineering for Retrieval Augmented Generation (RAG) systems in expert settings. Through a case study at a maritime service provider, we demonstrate how data scientists face a fundamental tension between user expectations of AI perfection and the correctness of the generated outputs. Our findings reveal that data scientists must identify context-specific "retrieval requirements" through iterative experimentation together with users because they are the ones who can determine correctness. We present an empirical process model describing how data scientists practically elicited these "retrieval requirements" and managed system limitations. This work advances software engineering knowledge by providing insights into the specialized requirements engineering processes for implementing RAG systems in complex domain-specific applications.
Chaos Engineering is a discipline which enhances software resilience by introducing faults to observe and improve system behavior intentionally. This paper presents a design proposal for a customized Chaos Engineering framework tailored for Softtech, a leading software development company serving the financial sector. It outlines foundational concepts and activities for introducing Chaos Engineering within Softtech, while considering financial sector regulations. Building on these principles, the framework aims to be iterative and scalable, enabling development teams to progressively improve their practices. The study addresses two primary questions: how Softtech's unique infrastructure, business priorities, and organizational context shape the customization of its Chaos Engineering framework and what key activities and components are necessary for creating an effective framework tailored to Softtech's needs.
Benjamin Hope, Jayden Bracey, Sahar Choukir
et al.
Large language models (LLMs) such as OpenAI's ChatGPT hold potential for automating engineering analysis, yet their reliability in solving multi-step statics problems remains uncertain. This study evaluates the performance of ChatGPT-4o and ChatGPT-o1-preview on foundational statics tasks, from simple calculations of Newton's second law of motion to beam and truss analyses and compares their results to first-year engineering students on a typical statics exam. To enhance accuracy, we developed a Custom GPT, embedding refined prompts directly into its instructions. This optimized model achieved an 82% score, surpassing the 75% student average, demonstrating the impact of tailored guidance. Despite these improvements, LLMs continued to exhibit errors in nuanced or open-ended problems, such as misidentifying tension and compression in truss members. These findings highlight both the promise and current limitations of AI in structural analysis, emphasizing the need for improved reasoning, multimodal capabilities, and targeted training data for future AI-driven automation in civil and mechanical engineering.
Within the project management context, project scheduling serves as an indispensable component, functioning as a fundamental tool for planning, monitoring, controlling, and managing projects more broadly. Although the resource-constrained project scheduling problem (RCPSP) lies at the core of project management activities, it remains largely disconnected from the broader literature on model-based systems engineering (MBSE), thereby limiting its integration into the design and management of complex systems. The original contribution of this paper is twofold. First, the paper seeks to reconcile the RCPSP with the broader literature and vocabulary of model-based systems engineering and hetero-functional graph theory (HFGT). A concrete translation pipeline from an activity-on-node network to a SysML activity diagram, and then to an operand net is constructed. Using this representation, it specializes the hetero-functional network minimum-cost flow (HFNMCF) formulation to the RCPSP context as a systematic means of HFGT for quantitative analysis and proves that the RCPSP is recoverable as a special case of a broader model. Secondly, on an illustrative instance with renewable and non-renewable operands, the specialized HFNMCF, while producing similar schedules, yields explicit explanations of the project states that enable richer monitoring and control. Overall, the framework preserves the strengths of the classical RCPSP while accommodating real-world constraints and enterprise-level decision processes encountered in large, complex megaprojects.
Digital Engineering currently relies on costly and often bespoke integration of disparate software products to assemble the authoritative source of truth of the system-of-interest. Tools not originally designed to work together become an acknowledged system-of-systems, with their own separate feature roadmaps, deprecation, and support timelines. The resulting brittleness and conglomeration of disparate interfaces in the Digital Engineering Ecosystem of an organization drains resources and impairs efficiency and efficacy. If Model-Based Systems Engineering were applied to this problem, a complete system architecture model would be defined, and a purpose-built computing system-of-systems would be constructed to satisfy stakeholder needs. We have decades of research in computer science, cybersecurity, software and systems engineering, and human-computer interaction from which to draw that informs the design of a Seamless Digital Engineering tooling system, but it would require starting from a clean slate while carefully adopting existing standards. In this paper, this problem space and solution space are characterized, defining and identifying Seamless Digital Engineering as a grand challenge in Digital Engineering research.
Saara Tenhunen, Tomi Männistö, Matti Luukkainen
et al.
Tertiary education institutions aim to prepare their computer science and software engineering students for working life. While much of the technical principles are covered in lower-level courses, team-based capstone projects are a common way to provide students with hands-on experience and teach soft skills. This paper explores the characteristics of software engineering capstone courses presented in the literature. The goal of this work is to understand the pros and cons of different approaches by synthesising the various aspects of software engineering capstone courses and related experiences. In a systematic literature review for 2007-2022, we identified 127 primary studies. These studies were analysed based on their presented course characteristics and the reported course outcomes. The characteristics were synthesised into a taxonomy consisting of duration, team sizes, client and project sources, project implementation, and student assessment. We found out that capstone courses generally last one semester and divide students into groups of 4-5 where they work on a project for a client. For a slight majority of courses, the clients are external to the course staff and students are often expected to produce a proof-of-concept level software product as the main end deliverable. The courses also offer versatile assessments for students throughout the project. This paper provides researchers and educators with a classification of characteristics of software engineering capstone courses based on previous research. We further synthesise insights on the reported outcomes of capstone courses. Our review study aims to help educators to identify various ways of organising capstones and effectively plan and deliver their own capstone courses. The characterisation also helps researchers to conduct further studies on software engineering capstones.
Eriks Klotins, Michael Unterkalmsteiner, Tony Gorschek
Context: Start-up companies have become an important supplier of innovation and software-intensive products. The flexibility and reactiveness of start-ups enables fast development and launch of innovative products. However, a majority of software start-up companies fail before achieving any success. Among other factors, poor software engineering could be a significant contributor to the challenges experienced by start-ups. However, the state-of-practice of software engineering in start-ups, as well as the utilization of state-of-the-art is largely an unexplored area. Objective: In this study we investigate how software engineering is applied in start-up context with a focus to identify key knowledge areas and opportunities for further research. Method: We perform a multi-vocal exploratory study of 88 start-up experience reports. We develop a custom taxonomy to categorize the reported software engineering practices and their interrelation with business aspects, and apply qualitative data analysis to explore influences and dependencies between the knowledge areas. Results: We identify the most frequently reported software engineering (requirements engineering, software design and quality) and business aspect (vision and strategy development) knowledge areas, and illustrate their relationships. We also present a summary of how relevant software engineering knowledge areas are implemented in start-ups and identify potentially useful practices for adoption in start-ups. Conclusions: The results enable a more focused research on engineering practices in start-ups. We conclude that most engineering challenges in start-ups stem from inadequacies in requirements engineering. Many promising practices to address specific engineering challenges exists, however more research on adaptation of established practices, and validation of new start-up specific practices is needed.
Abstract The acoustic characteristics of bluff-body burners play a critical role in the combustion stability for combustors using this type of burners. The acoustic modelling of an axisymmetric bluff-body burner entails properly capturing the sound-vortex interaction for the flow through the annular aperture of the burner. Such a problem pertaining to annular apertures can also be of relevance to other engineering applications, such as acoustic dampers or turbofan duct systems. The methodology of combining suitable acoustic Green’s functions with a vortex sheet model has been applied extensively in previous theoretical studies of the acoustic response of a short circular orifice with a mean flow passing through it. In this work, the Green’s function and vortex sheet model theory is generalised in order to efficiently predict the acoustic characteristics of thin annular apertures sustaining a mean flow, which effectively emulate the typical axisymmetric bluff-body burner configurations in realistic combustors. This requires the incorporation of multiple Kutta conditions for modelling the vortex shedding and multiple vortex sheets for modelling the interaction of the shed vorticity and the acoustics. A high-resolution compressible Large Eddy Simulation (LES) of a simplified representative geometry is performed for validation; the analytical prediction and numerical findings show very good agreement, and the LES further provides key insights into the speed with which vortical disturbances convect downstream.
The Roadmap is performed in the context of a Ph.D. research in collaboration between the Experimental Software Engineering Group, from the Systems Engineering and Computing Program of the Federal University of Rio de Janeiro (COPPE/UFRJ) and the Laboratory of Industrial and Human Automation Control, Mechanical engineering and Computer Science (LAMIH UMR CNRS 8201) in the Universitè Polytechnique Hauts-de-France (UPHF). The Roadmap resulted from an investigation on the particularities of IoT applications. It is the concrete organization of the concepts and evidence gathered from different experimental studies. It comes to support the definition of IoT software systems, with specific items for the project team to discuss and define the essential aspects related to the specifying, designing, and implementing an IoT application.
Patent data have long been used for engineering design research because of its large and expanding size, and widely varying massive amount of design information contained in patents. Recent advances in artificial intelligence and data science present unprecedented opportunities to develop data-driven design methods and tools, as well as advance design science, using the patent database. Herein, we survey and categorize the patent-for-design literature based on its contributions to design theories, methods, tools, and strategies, as well as the types of patent data and data-driven methods used in respective studies. Our review highlights promising future research directions in patent data-driven design research and practice.
Homing behavior for autonomous underwater vehicles (AUVs) is vital for autonomous docking and indispensable for recovery of vehicles in logistically difficult or hazardous conditions. Homing to a single acoustic beacon is a low-logistics solution to this engineering challenge. A homing application has been developed in C++ that applies a multilateration-based localization algorithm to estimate transponder location for homing. Mission oriented operating suite interval programming (MOOS-IvP) was implemented as a backseat driver on a Teledyne Gavia AUV to enhance the AUV with adaptive maneuvering capabilities; thus, enabling mission waypoints to be dynamically updated by the homing application (pHomeToBeacon) through the MOOS database and a developed iGavia crewmember. To demonstrate MOOS-IvP-GAVIA and homing capabilities using this first-principles approach to localization, field trials were undertaken in Kópavogur, Iceland, in June 2015 and proved consistent homing to a single beacon within 15 m accuracy. These trials were an industry-first of deploying a user-developed application on MOOS-IvP-GAVIA and of having a Gavia enhanced with adaptive maneuvering capabilities for homing. This new capability enables Gavia AUV to be used as a platform for future developer-led autonomy and applications. Ultimately, pHomeToBeacon will enable any AUV enhanced with MOOS-IvP to use acoustics to home to a surface vessel (stationary or underway) in preparation for autonomous subsea docking and recovery.
The inclusive education method has substantial contributions to hearing-impaired individuals’ education and socialization. However, the poor physical environment and acoustic comfort conditions negatively affect speech intelligibility at such places and therefore, the quality of education. Upon determining that there are very few subjective evaluation studies, we conducted a study regarding the impact of acoustic comfort conditions on speech intelligibility at inclusive education places. Within the scope of the study, first, a classroom was determined, and the current acoustic conditions of the class were evaluated objectively by field acoustic measurements. A calibrated model was created in the simulation software of the relevant class and then two more models with optimum reverberation time values of 0.4 s and 0.8 s as suggested in the literature, and auralizations were performed for the models. For subjective evaluation, a subject group of hearing-impaired and normal hearing individuals fulfilling equal conditions were tested by speech discrimination test in real-time in the classroom and from auralization recordings in a laboratory setting. Regarding the results obtained, it was observed that speech intelligibility percentage of normal hearing individuals increased as expected while in hearing-impaired individuals, contrary to the expectations, percentage differed from one another, and there was no increase. Following the discussions with experts, it was concluded that different hearing aids used by hearing-impaired individuals might lead to this situation. Accordingly, it occurs that the possibility to achieve a good speech intelligibility for hearing-impaired individuals even if optimum acoustic values suggested are fulfilled in education places remains unclear.
The periodontal biomechanical environment is very difficult to investigate. By the complex geometry and composition of the periodontal ligament, its mechanical behavior is very dependent on the type of loading (compressive vs. tensile loading; static vs. cyclic loading; uniaxial vs. multiaxial) and the location around the root (cervical, middle, or apical). These different aspects of the periodontal ligament make it difficult to develop a functional biomaterial to treat periodontal attachment due to periodontal diseases. This review aims to describe the structural and biomechanical properties of the periodontal ligament. Particular importance is placed in the close interrelationship that exists between structure and biomechanics: the periodontal ligament structural organization is specific to its biomechanical environment, and its biomechanical properties are specific to its structural arrangement. This balance between structure and biomechanics can be explained by a mechanosensitive periodontal cellular activity. These specifications have to be considered in the further tissue engineering strategies for the development of an efficient biomaterial for periodontal tissues regeneration.
Cristiano Politowski, Fabio Petrillo, João Eduardo Montandon
et al.
Game engines help developers create video games and avoid duplication of code and effort, like frameworks for traditional software systems. In this paper, we explore open-source game engines along three perspectives: literature, code, and human. First, we explore and summarise the academic literature on game engines. Second, we compare the characteristics of the 282 most popular engines and the 282 most popular frameworks in GitHub. Finally, we survey 124 engine developers about their experience with the development of their engines. We report that: (1) Game engines are not well-studied in software-engineering research with few studies having engines as object of research. (2) Open-source game engines are slightly larger in terms of size and complexity and less popular and engaging than traditional frameworks. Their programming languages differ greatly from frameworks. Engine projects have shorter histories with less releases. (3) Developers perceive game engines as different from traditional frameworks. Generally, they build game engines to (a) better control the environment and source code, (b) learn about game engines, and (c) develop specific games. We conclude that open-source game engines have differences compared to traditional open-source frameworks although this differences do not demand special treatments.
Software engineering has long studied how software developers work, building a body of work which forms the foundation of many software engineering best practices, tools, and theories. Recently, some developers have begun recording videos of themselves engaged in programming tasks contributing to open source projects, enabling them to share knowledge and socialize with other developers. We believe that these videos offer an important opportunity for both software engineering research and education. In this paper, we discuss the potential use of these videos as well as open questions for how to best enable this envisioned use. We propose creating a central repository of programming videos, enabling analyzing and annotating videos to illustrate specific behaviors of interest such as asking and answering questions, employing strategies, and software engineering theories. Such a repository would offer an important new way in which both software engineering researchers and students can understand how software developers work.