We explore the concept of folklore within software engineering, drawing from folklore studies to define and characterize narratives, myths, rituals, humor, and informal knowledge that circulate within software development communities. Using a literature review and thematic analysis, we curated exemplar folklore items (e.g., beliefs about where defects occur, the 10x developer legend, and technical debt). We analyzed their narrative form, symbolic meaning, occupational relevance, and links to knowledge areas in software engineering. To ground these concepts in practice, we conducted semi-structured interviews with 12 industrial practitioners in Sweden to explore how such narratives are recognized or transmitted within their daily work and how they affect it. Synthesizing these results, we propose a working definition of software engineering folklore as informally transmitted, traditional, and emergent narratives and heuristics enacted within occupational folk groups that shape identity, values, and collective knowledge. We argue that making the concept of software engineering folklore explicit provides a foundation for subsequent ethnography and folklore studies and for reflective practice that can preserve context-effective heuristics while challenging unhelpful folklore.
Dragica Chamovska, Aleksandra Porjazoska Kujundziski
Electrochemical capacitors, also known as supercapacitors or ultracapacitors, due to their excellent electrochemical performances, attract significant interest as renewable energy storage devices, mainly when carbon-based materials are used as electrode components. Their low cost, availability, and sustainability are among the main benefits of activated carbons. This study reviews various biomass precursors, including coffee grounds, shells, husks, and other biomaterials. Processing methods of biomass precursors, e.g., pyrolysis, hydrothermal treatment, and chemical activation, affect the electrode porosity and surface area, as well as their electrochemical behaviour. According to the literature data, activated carbons obtained from coffee ground carbonisation achieve specific capacitances of 350 F g −1 , energy densities of around 34–39 Wh kg −1 , and show excellent cycling stability with the rate capability higher than 85% after 7000–9000 cycles. This study aims to highlight the potential of renewable waste-based carbons as promising electrode materials for next-generation energy storage systems.
The rapid advancement of AI-assisted software engineering has brought transformative potential to the field of software engineering, but existing tools and paradigms remain limited by cognitive overload, inefficient tool integration, and the narrow capabilities of AI copilots. In response, we propose Compiler.next, a novel search-based compiler designed to enable the seamless evolution of AI-native software systems as part of the emerging Software Engineering 3.0 era. Unlike traditional static compilers, Compiler.next takes human-written intents and automatically generates working software by searching for an optimal solution. This process involves dynamic optimization of cognitive architectures and their constituents (e.g., prompts, foundation model configurations, and system parameters) while finding the optimal trade-off between several objectives, such as accuracy, cost, and latency. This paper outlines the architecture of Compiler.next and positions it as a cornerstone in democratizing software development by lowering the technical barrier for non-experts, enabling scalable, adaptable, and reliable AI-powered software. We present a roadmap to address the core challenges in intent compilation, including developing quality programming constructs, effective search heuristics, reproducibility, and interoperability between compilers. Our vision lays the groundwork for fully automated, search-driven software development, fostering faster innovation and more efficient AI-driven systems.
While mastered by some, good scientific writing practices within Empirical Software Engineering (ESE) research appear to be seldom discussed and documented. Despite this, these practices are implicit or even explicit evaluation criteria of typical software engineering conferences and journals. In this pragmatic, educational-first document, we want to provide guidance to those who may feel overwhelmed or confused by writing ESE papers, but also those more experienced who still might find an opinionated collection of writing advice useful. The primary audience we had in mind for this paper were our own BSc, MSc, and PhD students, but also students of others. Our documented advice therefore reflects a subjective and personal vision of writing ESE papers. By no means do we claim to be fully objective, generalizable, or representative of the whole discipline. With that being said, writing papers in this way has worked pretty well for us so far. We hope that this guide can at least partially do the same for others.
امروزه با افزایش نیاز بشر به تأمین انرژی و مشتقات نفتی، استخراج این ماده روزبهروز در حال افزایش است. بااینوجود مخازنی که ازنظر عملیات حفاری و پایداری چاه پیچیدگی و مشکلات اندکی داشتند، در حال اتمام هستند. مهندسان برای پاسخ به این نیاز باید به استخراج منابعی که دارای پیچیدگی و مشکلات بیشتری در حفاری و پایداری نسبت به قبل هستند بپردازند. لذا مبحث پایداری چاه، وزن بهینه و پنجره ایمن سیال حفاری بیشازپیش مورد اهمیت قرار میگیرد. در این پژوهش با تعمیم و اصلاح منحنی اندرکنش زمین که یکی از مهمترین روشها در تحلیل پایداری فضاهای زیرزمینی است، به تحلیل پایداری چاه و انتخاب وزن بهینه سیال حفاری با استفاده از روش حل تحلیلی و عددی پرداخته میشود. در ابتدا منحنی اندرکنش زمین برای پنج حفره دایرهای شکل در میدان تنشهای هیدرواستاتیک و ناهمسانگرد رسم شده و تأثیر پارامترهایی همچون فشار منفذی، نسبتهای مختلف تنشهای افقی به قائم و شعاع حفره روی منحنی اندرکنش زمین برسی میشود. مشخص شد تغییرات این پارامترها با میزان همگرایی دیواره حفره رابطه مستقیم داشته و با افزایش آنها میزان همگرایی دیواره حفره افزایش مییابد. سپس با استفاده از روابط تحلیلی مور-کلمب و روش منحنی اندرکنش زمین در مدلسازی عددی تفاضل محدود، حدود پنجره ایمن سیال حفاری محاسبه گردید. طبق نتایج بهدستآمده در روش عددی با استفاده از منحنی اندرکنش زمین حد پایین و بالای فشار سیال حفاری به ترتیب کمتر و بیشتر از حد پایین و بالای فشار سیال حفاری با استفاده از روش تحلیلی مور-کلمب بوده و روش عددی مبتنی بر منحنی اندرکنش زمین پنجره ایمن بزرگتری نسبت به روش تحلیلی مور-کلمب ارائه میدهد.
In this study, a NiCoCrW (K447A) superalloy was fabricated using selective laser melting (SLM). The hot-corrosion behaviour of the SLM-fabricated NiCoCrW (K447A) was investigated in Na<sub>2</sub>SO<sub>4</sub> at 900 °C. Microstructural analysis and hot-corrosion testing revealed its anisotropic behaviour in different build directions. The corrosion resistance along the build direction (XOY plane) was superior to that perpendicular to the build direction (YOZ plane). The stability of grain boundaries in the XOY plane is enhanced by the fine grains and a larger carbide area fraction, effectively hindering the diffusion of S and O<sub>2</sub> at grain boundaries. Furthermore, the more uniform distribution of carbides in the XOY plane reduces the local stress concentration, contributing to the stability of the protective oxide film. The enhanced hot-corrosion resistance is attributed to the formation of a more continuous and dense corrosion layer on the XOY surface.
Nikolai Buktukov, Rustem Igizbaev, Gulnaz Moldabayeva
et al.
This analytical review is aimed at identifying and analysing a variety of factors affecting the low oil recovery factor. The study covers a wide range of parameters, from the mining and geological conditions of deposits to the physical and mechanical properties of rocks and hydrocarbons. Attention is also paid to such important aspects as geological features, including fracturing of rocks, waterlogging of formations and folding of deposits, which can significantly complicate oil production. Statistical data on current oil recovery rates from different regions and countries were collected and analysed, which helped to identify the most common problems and typical oil recovery rates. The review highlights that, along with well-known factors such as high oil viscosity and low rock permeability, oil recovery factor is significantly influenced by resistance to extraction by gravity, and complex tectonic conditions such as the presence of folds and faults. In addition, the problems related to the modelling and representation of the oil reservoir are considered, which can lead to errors in the assessment of oil reserves and, consequently, to an underestimated oil recovery factor. In conclusion, the review suggests possible areas for the development of oil production technologies that can help to overcome the identified obstacles. Suggestions are given for improving methods of increasing oil recovery, such as the introduction of new technologies, improvement of existing methods, and conducting more accurate geological studies.
Phillip Stothard, Peter Ryan, Takeshi Kurata
et al.
Access to persistent computer-generated virtual worlds may provide a powerful tool for conceptualising the mining cycle and managing the domains of exploration, feasibility, planning, design, construction, operations, rehabilitation, decommissioning and closure. Each domain presents a significant challenge to mine operations. Realisation of persistent virtual worlds that can be accessed by many simultaneously may be possible by leveraging Metaverse technologies to produce an ‘always on’ Mining Metaverse based on International Standards and industry collaboration. The realisation of a Mining Metaverse is a complex task because the Metaverse itself has many components and domains that must be managed effectively for it to be sustainable. This article introduces the complexity of the Metaverse components as a taxonomy and was inspired from collaborative work completed by the Standards Australia IT-031 Modelling and Simulation Committee and International Standards Organisation ISO/IEC JTC 1/SC 24 Committee. It is intended as a starting point for the mining industry towards understanding what the Mining Metaverse may be, and effectively embracing and managing this complex emerging technology in the future.
Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software Engineering (LLM4SE) area. However, limited attention has been paid to developing efficient LLM4SE techniques that demand minimal computational cost, time, and memory resources, as well as green LLM4SE solutions that reduce energy consumption, water usage, and carbon emissions. This paper aims to redirect the focus of the research community towards the efficiency and greenness of LLM4SE, while also sharing potential research directions to achieve this goal. It commences with a brief overview of the significance of LLM4SE and highlights the need for efficient and green LLM4SE solutions. Subsequently, the paper presents a vision for a future where efficient and green LLM4SE revolutionizes the LLM-based software engineering tool landscape, benefiting various stakeholders, including industry, individual practitioners, and society. The paper then delineates a roadmap for future research, outlining specific research paths and potential solutions for the research community to pursue. While not intended to be a definitive guide, the paper aims to inspire further progress, with the ultimate goal of establishing efficient and green LLM4SE as a central element in the future of software engineering.
Ethnography has become one of the established methods for empirical research on software engineering. Although there is a wide variety of introductory books available, there has been no material targeting software engineering students particularly, until now. In this chapter we provide an introduction to teaching and learning ethnography for faculty teaching ethnography to software engineering graduate students and for the students themselves of such courses. The contents of the chapter focuses on what we think is the core basic knowledge for newbies to ethnography as a research method. We complement the text with proposals for exercises, tips for teaching, and pitfalls that we and our students have experienced. The chapter is designed to support part of a course on empirical software engineering and provides pointers and literature for further reading.
Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel
et al.
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 as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyse in depth the current state of quantum software engineering research. From this analysis, the key areas of quantum software engineering 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 Quantum Software Engineering.
Ranim Khojah, Mazen Mohamad, Philipp Leitner
et al.
Large Language Models (LLMs) are frequently discussed in academia and the general public as support tools for virtually any use case that relies on the production of text, including software engineering. Currently there is much debate, but little empirical evidence, regarding the practical usefulness of LLM-based tools such as ChatGPT for engineers in industry. We conduct an observational study of 24 professional software engineers who have been using ChatGPT over a period of one week in their jobs, and qualitatively analyse their dialogues with the chatbot as well as their overall experience (as captured by an exit survey). We find that, rather than expecting ChatGPT to generate ready-to-use software artifacts (e.g., code), practitioners more often use ChatGPT to receive guidance on how to solve their tasks or learn about a topic in more abstract terms. We also propose a theoretical framework for how (i) purpose of the interaction, (ii) internal factors (e.g., the user's personality), and (iii) external factors (e.g., company policy) together shape the experience (in terms of perceived usefulness and trust). We envision that our framework can be used by future research to further the academic discussion on LLM usage by software engineering practitioners, and to serve as a reference point for the design of future empirical LLM research in this domain.
Rosalia Tufano, Antonio Mastropaolo, Federica Pepe
et al.
Large Language Models (LLMs) have gained significant attention in the software engineering community. Nowadays developers have the possibility to exploit these models through industrial-grade tools providing a handy interface toward LLMs, such as OpenAI's ChatGPT. While the potential of LLMs in assisting developers across several tasks has been documented in the literature, there is a lack of empirical evidence mapping the actual usage of LLMs in software projects. In this work, we aim at filling such a gap. First, we mine 1,501 commits, pull requests (PRs), and issues from open-source projects by matching regular expressions likely to indicate the usage of ChatGPT to accomplish the task. Then, we manually analyze these instances, discarding false positives (i.e., instances in which ChatGPT was mentioned but not actually used) and categorizing the task automated in the 467 true positive instances (165 commits, 159 PRs, 143 issues). This resulted in a taxonomy of 45 tasks which developers automate via ChatGPT. The taxonomy, accompanied with representative examples, provides (i) developers with valuable insights on how to exploit LLMs in their workflow and (ii) researchers with a clear overview of tasks that, according to developers, could benefit from automated solutions.
Heusler alloys, which were unintentionally discovered at the start of the 20th century, have become intriguing materials for many extraordinary functional applications in the 21st century, including smart devices, spintronics, magnetic refrigeration and the shape memory effect. With this review article, we would like to provide a comprehensive review on the recent progress in the development of Heusler alloys, especially Ni-Mn based ones, focusing on their structural crystallinity, order-disorder atoms, phase changes and magnetic ordering atoms. The characterization of the different structures of these types of materials is needed, where a detailed exploration of the crystal structure is presented, encompassing the influence of temperature and compositional variations on the exhibited phases. Hence, this class of materials, present at high temperatures, consist of an ordered austenite with a face-centered cubic (FCC) superlattice as an L2<sub>1</sub> structure, or body-centered cubic (BCC) unit cell as a B2 structure. However, a low-temperature martensite structure can be produced as an L10, 10M or 14M martensite structures. The crystal lattice structure is highly dependent on the specific elements comprising the alloy. Additionally, special emphasis is placed on phase transitions within Heusler alloys, including martensitic transformations ranging above, near or below room temperature and magnetic transitions. Therefore, divers’ crystallographic defects can be presented in such types of materials affecting their structural and magnetic properties. Moreover, an important property of Heusler compounds, which is the ability to regulate the valence electron concentration through element substitution, is discussed. The possible challenges and remaining issues are briefly discussed.
Reaction characteristics in pyrometallurgical treatment for aluminum dross were studied qualitatively and quantitatively by thermal analysis. The transformation of aluminum nitride (AlN), volatilization of chlorides and fluorides in two kinds of dross under both argon (Ar) and Ar-Oxygen (O2) atmospheres were in detail analyzed and compared. Gas species including water vapor (H2O(g)), ammonia (NH3), nitrogen (N2), nitric oxide (NO), and carbon dioxide (CO2) were clearly identified. The study indicated that N2 and small amount of NO were produced from AlN–O2 reaction while NH3 from AlN–H2O(g) reaction, and H2O(g) and CO2 were necessarily from thermal decomposition of hydroxides and carbonates. Calculation indicated that the AlN–O2 reaction, AlN–H2O(g) reaction, and volatilization of chlorides or fluorides were remarkably slow, for around 30 mg raw material with taking about 37 min to finish the AlN–O2 reaction in 500–1000°C, 60 min to the AlN–H2O(g) reaction in 130–500 °C, and 30 min to the volatilization of chlorides or fluorides in 760–1000°C. Kinetics study indicated that the Ginstling-Brounshtein's diffusion model and Jander's diffusion model were most appropriate for describing the kinetics, respectively with an apparent activation energy of 273.2 kJ mol−1 and 307.4 kJ mol−1 for the AlN–O2 reaction, and with that of 182.0 kJ mol−1 and 194.0 kJ mol−1 for AlN–H2O(g) reaction. The study will be beneficial for design, optimization of pyrometallurgical routes of aluminum dross treatment and for evaluating its environmental effect.
This is an article in the field of ceramics and composites. In order to study the early rheological properties of alkali-activated fly ash-slag cementitious system, the composite pastes with different mass ratios of fly ash (FA) to slag (GGBS) and alkaline activator content were prepared. The fluidity and rheological properties of the pastes were tested by mini-cone slump cone, Brookfield DV3T rheometer,respectively. Finally, the hydration exothermic rate of composite pastes with each ratio was tested by isothermal calorimeter. Results show that when FA/GGBS ratio is 3∶7, the fluidity of paste with 4% NaOH content is the lowest. With the increase of FA mass ratio and NaOH molar mass, the fluidity of alkali-activated FA-GGBS cementitious system increased, and the yield stress and plastic viscosity decreased. The growth of FA content decreases the early hydration rate significantly, while the increase of alkali activator content remarkably increases the peak rate of hydration heat release.