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.
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.
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.
Nasir U. Eisty, Jeffrey C. Carver, Johanna Cohoon
et al.
In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs, proactively initiating and nurturing collaborations, and engaging within each other's professional environments. They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another. Additionally, the guidelines highlight the necessity of vigilance in monitoring collaboration dynamics, securing institutional support, and defining clear, shared objectives. By adhering to these principles, RSEs and SERs can build synergistic relationships that enhance the quality and impact of research outcomes.
This paper explores how generative AI can help automate and improve key steps in systems engineering. It examines AI's ability to analyze system requirements based on INCOSE's "good requirement" criteria, identifying well-formed and poorly written requirements. The AI does not just classify requirements but also explains why some do not meet the standards. By comparing AI assessments with those of experienced engineers, the study evaluates the accuracy and reliability of AI in identifying quality issues. Additionally, it explores AI's ability to classify functional and non-functional requirements and generate test specifications based on these classifications. Through both quantitative and qualitative analysis, the research aims to assess AI's potential to streamline engineering processes and improve learning outcomes. It also highlights the challenges and limitations of AI, ensuring its safe and ethical use in professional and academic settings.
The study of behavioral and social dimensions of software engineering (SE) tasks characterizes behavioral software engineering (BSE);however, the increasing significance of human-AI collaboration (HAIC) brings new directions in BSE by presenting new challenges and opportunities. This PhD research focuses on decision-making (DM) for SE tasks and collaboration within human-AI teams, aiming to promote responsible software engineering through a cognitive partnership between humans and AI. The goal of the research is to identify the challenges and nuances in HAIC from a cognitive perspective, design and optimize collaboration/partnership (human-AI team) that enhance collective intelligence and promote better, responsible DM in SE through human-centered approaches. The research addresses HAIC and its impact on individual, team, and organizational level aspects of BSE.
Lokot Zein Nasution, Hermanto Siregar, Rifki Ismal
et al.
This paper is motivated by the still weak bargaining position of Islamic finance in the development policy constellation. In fact, Islamic finance has a variety of advantages compared to conventional, and has a variety of instruments that can be developed. One of the innovations in the development of Islamic financial instruments is the combination of sukuk and waqf or called sukuk linked waqf. The development of waqf-linked sukuk is one of the innovations and a manifestation of the importance of formulating objectives derived from religious and divine values or known as the Tawhidi String Relation (TSR). The TSR approach emphasizes the truth that comes from God, while at the same time emphasizing the importance of trying to achieve the benefit of the world. The principle of TSR is the oneness of Allah SWT which is known as Tawhid which acts as the main method for the development of Islamic finance. The oneness of Allah SWT is represented in the Al-Qur'an which is then juxtaposed with As-Sunnah. Based on the TSR approach, this paper suggests that there are many arguments or basic arguments for the importance of returning the financial sector back to the sharia economy which originates from the Al-Qur'an and As-Sunnah. This weak correlation causes the innovation results in the ecosystem for the development of waqf-linked sukuk to be weak. Therefore, it is necessary to strengthen the Islamic financial conclusion which must truly base its ecosystem on the basis of the Al-Qur'an and As-Sunnah as the foundation for the development of sukuk linked waqf.
Sulistyorini Anita, Izzalqurny Tomy Rizky, Utomo Muhammad Andry Prio
et al.
The 2021 eruption of Mount Semeru caused 61 deaths and the displacement of thousands people, exposed major shortcomings in community preparedness. One key factor contributing to these gaps is the limited availability of educational media that is accessible and relevant to the local context. This study addresses this issue by developing and validating a digital educational platform that was co-designed with local residents. The research offers two main novelties. Firstly, it combines comprehensive volcanic and geological information with practical preparedness guidelines that are presented on website. Secondly, the participatory co-design approach involving the local community contrasts with the usual top-down approach to disaster ICT initiatives. An educational website was produced and iteratively tested for feasibility with 34 individuals directly affected by the Semeru eruption, guided by a research and development (R&D) framework. Initial small-group testing (n = 10) yielded a 70% feasibility score, prompting significant revisions. Subsequent large-group testing (n = 24) demonstrated increased feasibility of over 92%, classifying the final product as ’highly feasible’. This research delivers a validated, context-specific digital tool that bridges the gap between government mitigation plans and grassroots needs, positioning the website as both a product and a model for interventions that strengthen community resilience.
Adrian Bajraktari, Michelle Binder, Andreas Vogelsang
Modern science is relying on software more than ever. The behavior and outcomes of this software shape the scientific and public discourse on important topics like climate change, economic growth, or the spread of infections. Most researchers creating software for scientific purposes are not trained in Software Engineering. As a consequence, research software is often developed ad hoc without following stringent processes. With this paper, we want to characterize research software as a new application domain that needs attention from the Requirements Engineering community. We conducted an exploratory study based on 8 interviews with 12 researchers who develop software. We describe how researchers elicit, document, and analyze requirements for research software and what processes they follow. From this, we derive specific challenges and describe a vision of Requirements Engineering for research software.
This paper analyzes the impact of the macroeconomic environment on Pakistan’s manufacturing sector, emphasizing in particular the role of fiscal and monetary policies in shaping incentives for industrial investment. Arguably, Pakistan’s macroeconomic fundamentals in the last two decades have remained fragile, resulting in severe macroeconomic imbalances that have contributed to macroeconomic instability and hampered private investment in aggregate as well as in the manufacturing sector. Furthermore, macroeconomic stabilization policies have often failed to produce the desired results owing to the lack of coordination between monetary and fiscal policies. Pakistan’s economy has thus lived on borrowed money and time and on rent-seeking behavior. Although some recent
macroeconomic indicators have improved slightly, fundamental weaknesses remain. In particular, the recent improvement in the current account deficit was driven largely by the high inflow of remittances, coupled with financial engineering such as loan payments from the International Monetary Fund, “friendly” money, European Union bonds, and Islamic sukuk. It is imperative to think about the consequences of a leveraged reliance on remittances in the aftermath of falling oil prices and global deflation. Prudent macroeconomic management aimed at consolidating public finances and controlling inflationary pressures is essential to boost industrial investment and yield sustainable growth.
Corporate greenwashing in response to carbon neutrality strategies has received substantial academic attention. Distinct from previous studies, this paper establishes a differential game model incorporating both green and brown enterprise types. The model compares greenness and total profits under two government scenarios: subsidies for green enterprises and the regulation of brown enterprises. It further analyzes the mechanism behind brown enterprise greenwashing formation. The results show that subsidies alone encourage brown enterprises to engage in greenwashing. However, government regulation inhibits such behaviors, with the inhibition effect positively correlated to regulatory intensity. Consumers’ green perception of enterprises also significantly drives brown enterprise greenwashing degrees. Higher green enterprise perception coefficients reduce greenwashing, while higher brown enterprise perception coefficients increase it. Differential game and simulation analyses reveal that greenwashing governance should consider both direct policy effects on brown enterprises and indirect subsidy effects on green enterprises.
This review paper explores the integration of phase change materials (PCMs) in building insulation systems to enhance energy efficiency and thermal comfort. Through an extensive analysis of existing literature, the thermal performance of PCM-enhanced building envelopes is evaluated under diverse environmental conditions. This review highlights that PCMs effectively moderate indoor temperatures by absorbing and releasing heat during phase transitions, maintaining a stable indoor climate. This paper also delves into the detailed concepts of PCMs, including their classification and various applications within building insulation. It is noted that different types of PCMs have unique thermal properties and potential uses, which can be tailored to specific building requirements and climatic conditions. Furthermore, cost–benefit and environmental assessments presented in the reviewed studies suggest that incorporating PCMs into building materials offers significant potential for reducing energy consumption and mitigating environmental impacts. These assessments indicate that PCMs can lead to substantial energy savings by decreasing the reliance on heating and cooling systems, thereby lowering overall energy costs and carbon emissions. However, despite the promising outlook, this review identifies a need for further research to optimize PCM formulations and integration methods. This optimization is essential for overcoming current challenges and facilitating the widespread adoption of PCMs in the construction industry. Addressing issues such as long-term durability, compatibility with existing building materials, and cost-effectiveness will be crucial for maximizing the benefits of PCMs in enhancing energy efficiency and sustainability in buildings. Overall, this review underscores the transformative potential of PCMs in building insulation practices. By providing a comprehensive overview of PCM classifications, applications, and their impacts on energy efficiency and environmental sustainability, this paper lays the groundwork for future advancements and research directions in the field of PCM-enhanced building technologies.
For decades, much software engineering research has been dedicated to devising automated solutions aimed at enhancing developer productivity and elevating software quality. The past two decades have witnessed an unparalleled surge in the development of intelligent solutions tailored for software engineering tasks. This momentum established the Artificial Intelligence for Software Engineering (AI4SE) area, which has swiftly become one of the most active and popular areas within the software engineering field. This Future of Software Engineering (FoSE) paper navigates through several focal points. It commences with a succinct introduction and history of AI4SE. Thereafter, it underscores the core challenges inherent to AI4SE, particularly highlighting the need to realize trustworthy and synergistic AI4SE. Progressing, the paper paints a vision for the potential leaps achievable if AI4SE's key challenges are surmounted, suggesting a transition towards Software Engineering 2.0. Two strategic roadmaps are then laid out: one centered on realizing trustworthy AI4SE, and the other on fostering synergistic AI4SE. While this paper may not serve as a conclusive guide, its intent is to catalyze further progress. The ultimate aspiration is to position AI4SE as a linchpin in redefining the horizons of software engineering, propelling us toward Software Engineering 2.0.
The increasing pressure within VUCA (volatility, uncertainty, complexity and ambiguity) driven environments causes traditional, plan-driven Systems Engineering approaches to no longer suffice. Agility is then changing from a "nice-to-have" to a "must-have" capability for successful system developing organisations. The current state of the art, however, does not provide clear answers on how to map this need in terms of processes, methods, tools and competencies (PMTC) and how to successfully manage the transition within established industries. In this paper, we propose an agile Systems Engineering (SE) Framework for the automotive industry to meet the new agility demand. In addition to the methodological background, we present results of a pilot project in the chassis development department of a German automotive manufacturer and demonstrate the effectiveness of the newly proposed framework. By adopting the described agile SE Framework, companies can foster innovation and collaboration based on a learning, continuous improvement and self-reinforcing base.
Irina-Carmen ANDREI, Gabriela-Liliana STROE, Sorin BERBENTE
et al.
This paper presents a study dedicated to the development of Digital and Smart Tools, based on solved applications of design engineering and reverse engineering. This approach is justified by the fact as well as the need for preparations prior to Composite Additive Manufacturing. Future integration of Digital Smart Tools with Composite Additive Manufacturing will significantly contribute to the efficient and effective support of the green economy, the active, responsible, safe and resilient protection of environment, life and climate. The research involved in this paper contributes to develop Digital and Smart Tools Applications, intended for integrated digital design, development, manufacturing and further predictive maintenance and services, based on robotic systems, extended automatic control, Artificial Intelligence and Machine Learning, including Mathematical Modeling and Numerical Simulations for Performance Prediction at Design Regime and Off-Design Regimes for jet engines, with the best capabilities to generate and integrate improvements, optimizations and potential innovative solutions. This paper presents significant applications of design, concept engineering development and reverse engineering design, as: 1/ the design of a transonic axial compressor rotor blade, 2/ the design of a swept axial compressor rotor, 3/ concept design engineering developments in case of a swept fan rotor blade, 4/ concept design developments and reverse engineering in case of a HP axial compressor rotor blade, part of Spey 512-14 DW turbofan engine, 5/ reverse engineering design of a Cessna 182 Skylane N223IF
light aircraft wheel cover. In line with Europe´s vision for sustainable aviation, this research study and INCAS´ TGA Project "Technological Development Platform for "Green" Technologies in Aviation and Ecological Manufacturing with Superior Added Value; TGA - Technologies for Green Aviation" will significantly contribute to the Green Deal, as a production center using "Green" Technologies in aviation and ecological manufacturing, as well as collaborative developer of Digital and Smart Tools for Composite Additive Manufacturing.