The heterogeneity in the organization of software engineering (SE) research historically exists, i.e., funded research model and hands-on model, which makes software engineering become a thriving interdisciplinary field in the last 50 years. However, the funded research model is becoming dominant in SE research recently, indicating such heterogeneity has been seriously and systematically threatened. In this essay, we first explain why the heterogeneity is needed in the organization of SE research, then present the current trend of SE research nowadays, as well as the consequences and potential futures. The choice is at our hands, and we urge our community to seriously consider maintaining the heterogeneity in the organization of software engineering research.
The software engineering researchers from countries with smaller economies, particularly non-English speaking ones, represent valuable minorities within the software engineering community. As researchers from Poland, we represent such a country. We analyzed the ICSE FOSE (Future of Software Engineering) community survey through reflexive thematic analysis to show our viewpoint on key software community issues. We believe that the main problem is the growing research-industry gap, which particularly impacts smaller communities and small local companies. Based on this analysis and our experiences, we present a set of recommendations for improvements that would enhance software engineering research and industrial collaborations in smaller economies.
Software Engineering (SE) faces simultaneous pressure from AI automation (reducing code production costs) and hardware-energy constraints (amplifying failure costs). We position that SE must redefine itself around human discernment-intent articulation, architectural control, and verification-rather than code construction. This shift introduces accountability collapse as a central risk and requires fundamental changes to research priorities, educational curricula, and industrial practices. We argue that Software Engineering, as traditionally defined around code construction and process management, is no longer sufficient. Instead, the discipline must be redefined around intent articulation, architectural control, and systematic verification. This redefinition shifts Software Engineering from a production-oriented field to one centered on human judgment under automation, with profound implications for research, practice, and education.
The use of modern information technologies, as well as elements of distance and blended learning systems, is a crucial task in organizing the educational process in higher education institutions. A strategic direction of modern pedagogy is providing students with the opportunity to pursue an individual educational trajectory. To address this task, high-quality structured distance learning courses serve as a vital component. Courses developed using modern information technologies contribute to improving the structural and logical model of professional competency formation. At the early stages of technical education, positive results can be achieved in developing skills for using modern CAD systems, specifically mastering computer graphics, 3D modeling, and creating construction documentation according to the requirements of the new standardization system. The article presents the core elements of the teaching methodology applied in the «Computer Engineering Graphics» course at Igor Sikorsky Kyiv Polytechnic Institute over a seven-year period. This methodology is utilized in blended learning and is based on a distance course hosted on the «Sikorsky» educational platform. The primary components of the course are video lectures, which cover theoretical material for each topic and provide step-by-step algorithms for completing assignments. Providing students with 24/7 access to course materials for independent cognitive activity, combined with indirect teacher guidance, contributes to high academic achievement. Another component of the methodology is ensuring substantial and rapid updates of reference materials. This issue is highly relevant due to the ongoing harmonization of Ukraine's national standards with International and European standardization systems. Such changes must be promptly reflected in educational resources. The structure of the developed distance course allows for rapid updates, unlike traditional textbooks and manuals, which require significant time for publication and implementation. The advantages of blended learning include direct feedback from the instructor through regular consultations via ZOOM conferences or classroom sessions. The results of this developed and tested methodology allow for the conclusion that it is possible to effectively form the competencies necessary for solving academic and professional tasks. Solutions are proposed for creating a complex of methodical materials based on distance courses that can be scaled to related disciplines. The application of the developed methodology is demonstrated using the «Permanent Joints» topic as an example, providing a case study of assembly unit drawing documentation involving welding, soldering, and adhesive bonding according to updated standards.
Engineering drawings frequently contain conic geometries such as circles, ellipses, parabolas, and hyperbolas, which are fundamental to mechanical design and industrial applications. Accurate identification and classification of these shapes are therefore essential for computer-aided design (CAD) systems, automated inspection, and intelligent design analysis. However, conventional geometry-based or rule-based approaches often perform poorly when drawings are noisy, complex, or partially incomplete. This study proposes a deep learning-based approach using convolutional neural networks (CNNs) to automatically extract features and classify conic shapes in engineering drawings. By learning discriminative visual representations directly from input data, the proposed method enhances classification accuracy, improves robustness, and reduces the need for manual intervention. The study concludes that CNN-based conic shape recognition offers a reliable and efficient solution for engineering and industrial contexts, with practical implications for improving automation and intelligent analysis in design-related applications.
This article explores how design scenarios can support anticipation, collaborative governance, and democratic decision-making across sectors. In focus is the use of scenario building that is communicated through conceptual and process diagrams, as well as contextual situations of people participating with designed artefacts to illustrate how scenario building can encourage community engagement to address challenges like water security and stewardship. By building on established design practices and literature on scenarios in design, the article proposes ‘Anticipative Collaborative Governance’ as a model for creating long-term, systemic solutions through design. It further contributes to cross-sector collaboration by introducing twelve guiding principles to strengthen connections between anticipatory, systemic, and collaborative design.
This letter aims to investigate thermodynamic processes in small systems in the Onsager region by showing that fundamental quantities such as total entropy production can be discretized on the mesoscopic scale. Even thermodynamic variables can conjugate to thermodynamic forces, and thus, Glansdorff–Prigogine’s dissipative variable may be discretized. The canonical commutation rules (CCRs) valid at the mesoscopic scale are postulated, and the measurement process consists of determining the eigenvalues of the operators associated with the thermodynamic quantities. The nature of the quantized quantity <inline-formula>
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</inline-formula>, entering the CCRs, is investigated by a heuristic model for nano-gas and analyzed through the tools of classical statistical physics. We conclude that according to our model, the constant <inline-formula>
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</inline-formula> does not appear to be a new fundamental constant but corresponds to the minimum value.
Mechanical drawing. Engineering graphics, Physical and theoretical chemistry
The article reflects on the cultural, social, and political role of the ‘place’ construct for a meaningful social regeneration of communities within the dynamics of culture, power, and economy. We focus on the role of public spaces in the framework of an action-research project – SMOTIES – to develop civic engagement in remote and semi-rural European contexts through participatory processes. It involved the community of X Village, a town of approximately 500 inhabitants in the XX area (Italy). The research reflects on design as an aesthetic and political language and on making, regenerating, and redefining place-rooted collectives and cultures by rearticulating the area’s social and cultural foundations with its communities to enable all voices to be heard and to make interactions with and through the tangible environment. The research approach is positioned in the interplay between participatory design, foresight methodologies, design for social innovation and relational art.
In this Story, Stefano Gualeni reflects on the cultural and heuristic implications of formulating and communicating philosophical thinking through alternative forms of writing that depart from the academic writing canon. He does so by presenting his two theory-fiction books, The Clouds (Routledge, 2023) and What We Owe the Dead (Set Margins’, 2025), which creatively engage with hybrid forms of textuality. These two experimental pieces play with different forms of philosophical texts, inviting readers to share in and co-participate in the critical speculation designed by the author.
Design driven processes focus on the relationship between people and heritage, crucial to interpreting and understanding urban identity. The approach centers the active role of design in connecting the community to its historical and cultural context, reappropriating historical memory through an ongoing interaction between urbs and civitas. Visual narratives and interaction through workshops and laboratories engage citizens and students, transforming design education into a tool for civic awareness. Through an open dialogue between disciplines and broad participation, the goal is to create 'heritage communities' that recognise and transmit the Exceptional Universal Value expressed through the physical and social fabric.
Large language model-specific inference engines (in short as \emph{LLM inference engines}) have become a fundamental component of modern AI infrastructure, enabling the deployment of LLM-powered applications (LLM apps) across cloud and local devices. Despite their critical role, LLM inference engines are prone to bugs due to the immense resource demands of LLMs and the complexities of cross-platform compatibility. However, a systematic understanding of these bugs remains lacking. To bridge this gap, we present the first empirical study on bugs in LLM inference engines. We mine official repositories of 5 widely adopted LLM inference engines, constructing a comprehensive dataset of 929 real-world bugs. Through a rigorous open coding process, we analyze these bugs to uncover their symptoms, root causes, commonality, fix effort, fix strategies, and temporal evolution. Our findings reveal six bug symptom types and a taxonomy of 28 root causes, shedding light on the key challenges in bug detection and location within LLM inference engines. Based on these insights, we propose a series of actionable implications for researchers, inference engine vendors, and LLM app developers, along with general guidelines for developing LLM inference engines.
Ashis Kumar Mandal, Md Nadim, Chanchal K. Roy
et al.
Research in software engineering is essential for improving development practices, leading to reliable and secure software. Leveraging the principles of quantum physics, quantum computing has emerged as a new computational paradigm that offers significant advantages over classical computing. As quantum computing progresses rapidly, its potential applications across various fields are becoming apparent. In software engineering, many tasks involve complex computations where quantum computers can greatly speed up the development process, leading to faster and more efficient solutions. With the growing use of quantum-based applications in different fields, quantum software engineering (QSE) has emerged as a discipline focused on designing, developing, and optimizing quantum software for diverse applications. This paper aims to review the role of quantum computing in software engineering research and the latest developments in QSE. To our knowledge, this is the first comprehensive review on this topic. We begin by introducing quantum computing, exploring its fundamental concepts, and discussing its potential applications in software engineering. We also examine various QSE techniques that expedite software development. Finally, we discuss the opportunities and challenges in quantum-driven software engineering and QSE. Our study reveals that quantum machine learning (QML) and quantum optimization have substantial potential to address classical software engineering tasks, though this area is still limited. Current QSE tools and techniques lack robustness and maturity, indicating a need for more focus. One of the main challenges is that quantum computing has yet to reach its full potential.
Tim Wittenborg, Ildar Baimuratov, Ludvig Knöös Franzén
et al.
The aerospace industry operates at the frontier of technological innovation while maintaining high standards regarding safety and reliability. In this environment, with an enormous potential for re-use and adaptation of existing solutions and methods, Knowledge-Based Engineering (KBE) has been applied for decades. The objective of this study is to identify and examine state-of-the-art knowledge management practices in the field of aerospace engineering. Our contributions include: 1) A SWARM-SLR of over 1,000 articles with qualitative analysis of 164 selected articles, supported by two aerospace engineering domain expert surveys. 2) A knowledge graph of over 700 knowledge-based aerospace engineering processes, software, and data, formalized in the interoperable Web Ontology Language (OWL) and mapped to Wikidata entries where possible. The knowledge graph is represented on the Open Research Knowledge Graph (ORKG), and an aerospace Wikibase, for reuse and continuation of structuring aerospace engineering knowledge exchange. 3) Our resulting intermediate and final artifacts of the knowledge synthesis, available as a Zenodo dataset. This review sets a precedent for structured, semantic-based approaches to managing aerospace engineering knowledge. By advancing these principles, research, and industry can achieve more efficient design processes, enhanced collaboration, and a stronger commitment to sustainable aviation.
D engineering drawings play an irreplaceable role in mechanical manufacturing area. Engineers need to read such drawings and extract information consistently for cost analysis, quality control, design optimization and some other work. To automate this extracting process while ensuring both efficiency and accuracy, this paper proposes an improved model based on RT-DETR for information detection in 2D drawings. First, a backbone network combining partial convolution (PConv) with efficient multi-scale attention (EMA) is used to reduce model parameters and obtain more detailed image features. Second, deformable attention is used to take the place of multi-head attention in the AIFI of original model to improve recognition accuracy for objects of different sizes. The experiment results show that improved RT-DETR increases precision by $6.43 \%$, increases recall by $14.26 \%$, increase mAP @ 50 by $13.35 \%$ compared to the base model, while requiring less inference time compared to other models. The algorithm demonstrates faster arithmetic speed and higher precision in the real-time detection of 2D engineering drawings.
As the cornerstone of spatial geometry and engineering drawings, three‐view drawing lays the necessary foundation for students to learn geography, graphics, industrial design, geographic information science, and so forth. However, teaching three‐view drawing can be challenging due to its abstraction. Currently, desktop and handheld augmented reality (AR) systems are widely applied to three‐view teaching. However, existing systems suffer from visuo‐tactile inconsistency and contain unfriendly interactions, resulting in a poor learning experience. In this paper, head‐mounted AR is introduced for the first time in the teaching of three‐view drawing. A system was designed for learning three‐view drawing to facilitate students' free exploration and learning in lessons. Additionally, a comparative experiment was designed and conducted to investigate whether multimodal interaction and head‐mounted AR help students to better understand the relationship between concrete three‐dimensional (3D) objects and abstract two‐dimensional planes and the impact on subjective perceptions. The results demonstrated that the proposed system significantly improved learning performance. Furthermore, the proposed system heightened students' interest in learning, made reproducing 3D structures more intuitive, and students were more willing to use such systems in their future studies.
This paper explores a historical innovation created by Henry Muncaster: a stationary steam engine featuring a single-cylinder horizontal design with a crosshead trunk guide. Through the application of engineering graphics techniques, we have elucidated the functioning of this invention by developing a 3D CAD model based on the original drawings published in Model Engineer magazine in 1957. However, the geometric modeling process faced challenges due to missing and erroneous dimensions for several components. Consequently, dimensional, geometric, and movement constraints were applied to ensure the coherence and functionality of the 3D CAD model, alongside conducting an interference analysis. Ultimately, the proper alignment of the cylinder and crosshead was ascertained, which is crucial for maintaining uniform forces and motions within the steam engine. This alignment is pivotal for achieving balanced operation, minimizing vibrations, and enhancing the overall efficiency of the invention.
Kapil Kadam, Shitanshu Mishra, Sridhar Iyer
et al.
ABSTRACT For several engineering disciplines, including civil engineering, mechanical engineering, architectural engineering, and others, engineering drawing (ED) is a mandatory subject. Problem solving in engineering drawing requires a complex integration of knowledge and spatial abilities. However, students don’t automatically learn these problem solving skills within the standard engineering curriculum. Identification of learning difficulties is a primary step in designing teaching-learning aids for students and teachers. While some learning challenges have been reported, there are fewer studies on identifying learning difficulties in solving these from the students’ and teachers’ perspectives. In this paper, we investigate the students’ difficulties in solving the engineering drawing problems. Here we present qualitative studies focusing on students’ learning difficulties in different engineering problem solving contexts, including data collected from five cohorts of novice learners, advanced learners, and ED teachers. The qualitative analysis of the data resulted in identifying the difficulties that students have while performing ED problem solving tasks. The identified difficulties were mainly related to knowledge deficits and challenges in performing higher order cognitive tasks. Data analysis helps to elaborate on these difficulties and discuss the relationships among them. We also discuss the implications of our results on teaching-learning of ED problem solving.
V. I. Vaulin, S. A. Singeev, N. I. Filonchik
et al.
The article examines the process of developing an engineer’s thinking during the study of engineering graphics at a university. Relevance. The working conditions of a modern engineer require professional training. One of the disciplines of engineering training is descriptive geometry and engineering graphics, which develops the thinking of an engineer. The purpose of the study is the process of developing an engineer’s thinking during the study of descriptive geometry and engineering graphics. The research used theoretical methods of analysis, synthesis of module structure, synthesis and generalizations, knowledge control, practical methods of performing graphic tasks, methods of mathematical statistics for evaluating educational achievements, analysis of literary sources and educational literature, experiment. The provisions reached at the beginning of the study determine the theoretical significance and novelty. Thinking has forms and types of thinking. The engineer’s level of thinking is based on knowledge, combining theoretical and practical experience of life activity, which determines his thinking logic. The basis for the development of thinking is mental formations. In this process, it should be important to form the knowledge and quality of the engineer’s knowledge during training. The qualities of a student’s knowledge are revealed as a result of the assimilation and application of knowledge by a person in various types of activities. Engineering graphics develops thinking by means of forming knowledge, skills, and abilities, as a basis for conclusions corresponding to the theoretical level of the student’s specialty training. Descriptive geometry and engineering graphics allows you to develop mental processes: perception, representation, imagination, memory, speech, etc.; qualities of knowledge: com-pleteness, depth, efficiency, flexibility, awareness; develop thinking: implies the development of qualities of thinking, modes of thinking, forms of thinking, levels of thinking. The practical significance is characterized by the conclusions of the study. Descriptive geometry and engineering graphics is an important discipline in the successful training of a future specialist, since as a result of its study, students acquire knowledge of the basics of design documentation, the ability to perform various types of design activities and read drawings, the skills of design documentation when studying other disciplines of the field of training, the competence of an engineer able to read and issue design documents for manufactured products. Descriptive geometry and engineering graphics develop thinking by means of formation of knowledge, skills, and abilities as the basis for conclusions corresponding to the theoretical level of the student’s specialty training. Descriptive geometry and engineering graphics allows you to develop mental processes: perception (in the process of studying theoretical material and practical performance of tasks on engineering graphics), representation (a set of knowledge about the types of projection: central, orthogonal, axonometric) based on the type of task to perform, imagination (to construct figures or details in a drawing, it is advisable to imagine and construct lines of connection in order to correctly construct projections), memory (knowledge of the requirements of the Unified System for Design Documentation allows you to see the depicted types of design documentation, drawings of parts, etc.), speech (characterized by terms specific to a particular specialty or discipline), etc.
The exploration of systems that Georgina Voss proposes engages with their affective dimensions and the complex interplay between visibility, power, and the unknown, reimagined as The Terrifying Mystery of the Cave. This metaphor shifts focus from the expectation of solutions to an acknowledgment of the profound complexity and enigmatic nature of systemic challenges. Drawing on perspectives from cybernetics to design theory, this analysis interrogates the mechanistic metaphors dominating system thinking, situating them within broader socio-political and historical contexts. A central focus lies in the tension between what is visible and what remains hidden — what occurs “backstage” — and the ways these obscured layers shape the visible outcomes of systems. Deterministic framings of systems as controllable entities are critiqued, emphasizing their human-made origins and deeply ingrained ideological structures. The unknown emerges as a generative space, where unknowing becomes a means to rethink complexity and disrupt reductive narratives.