In this study, Ti64 titanium alloy samples were fabricated under environmental pressures of 0.1 MPa (ambient pressure) and 0.4 MPa (high pressure) using a self-developed high-voltage arc wire additive manufacturing system. The effects of pressure on the microstructural evolution and anisotropy of a titanium alloy were comparatively investigated using characterization techniques such as SEM, EBSD, and TEM. The results indicate that differences in the thermal history dominated by the deposition path lead to significant anisotropy in the Ti64 samples (XY plane > XZ plane > YZ plane). Under high pressure, the altered molten pool morphology and expanded remelting zone prolong the residence time in the medium-to-low temperature range, thus reducing the β-phase fraction in all directions to a lower level and thereby weakening the anisotropy. In terms of grain growth, β-phase grains tend to grow preferentially along the deposition direction (Z-direction) under ambient pressure. In a high-pressure environment, the synergistic effect of pressure and thermal deformation induced by the horizontal extension of the molten pool enhances the growth of β-phase grains within the horizontal plane and suppresses preferential orientation. At the microscopic level, thermal deformation promotes twin formation and leads to dislocation concentration at primary β-phase grain boundaries, consequently influencing the mechanical properties of the Ti64 samples.
Oleksandr Kosenkov, Ehsan Zabardast, Jannik Fischbach
et al.
Implementing privacy by design (PbD) according to the General Data Protection Regulation (GDPR) is met with a growing number of requirements engineering (RE) approaches. However, the question of which RE method for PbD fits best the goals of organisations remains a challenge. We report our endeavor to close this gap by synthesizing a goal-centric approach for PbD methods assessment. We used literature review, interviews, and validation with practitioners to achieve the goal of our study. As practitioners do not approach PbD systematically, we suggest that RE methods for PbD should be assessed against organisational goals, rather than process characteristics only. We hope that, when further developed, the goal-centric approach could support the development, selection, and tailoring of RE practices for PbD.
Mohammadali Sohrabizadeh, Hassan Elmkhah, Meisam Nouri
et al.
Studying wear mechanisms is crucial in industry as wear significantly shortens the lifespan of equipment and components. This study investigated the effect of annealing temperatures on the wear mechanisms of CrN/CrTiSiN multilayer coatings. The coatings were annealed in air at temperatures ranging from 500 to 1000 °C for 1 h. XRD, SEM, FESEM, EDS, and ball-on-disk wear testing techniques were used. In the as-deposited and 500 °C annealed samples, the primary observed wear mechanism is plastic deformation, which results in the gradual detachment of particles (debris) from the substrate metal and the deformation of these particles along the wear path. Oxidative wear is characterized by fragmented debris and the retention of wear particles along the wear path. In contrast, annealing at temperatures between 700 °C and 1000 °C leads to the occurrence of oxidative wear, characterized by the oxidation of the metal surface and the abrasion of the oxides surface. The signs of oxidative wear include fragmented debris and the persistence of wear debris along the wear path, which are attributed to surface oxidation and the diffusion of oxygen into the coating. The factors influencing oxidative wear include increased surface oxides, debris fragmentation, and the retention of these particles along the wear path. This study recommends that CrN/CrTiSiN multilayer nanocomposite coatings should avoid exposure to operating temperatures exceeding 800 °C. To achieve optimal wear behavior, it is suggested to anneal the coating at 600 °C for 1 h in air atmosphere.
To save energy and reduce CO2 emissions, the lightweight design of structural components has recently become a global issue. Fe–Mn–Al–C based alloys with a low mass density have received considerable attention as structural materials enabling such lightweight designs. However, typical strength-ductility trade-off dilemma appears in Fe–Mn–Al–C lightweight steels. Dispersion of nano-sized Fe3AlC-type κ-carbides achieves excellent tensile properties of high strength (∼1 GPa) and large elongation (∼50 %). However, further increase in strength (∼1.2 GPa) caused by κ-carbide coarsening reduces elongation significantly (<10 %), limiting the potential applications of lightweight steels in structural parts that require ultrahigh strength and high ductility, such as wear-resistant components. Here, we resolve this drawback of lightweight steels by reinforcing the surface layer through 3D printing. The composition of base steel plate is Fe–30Mn–8Al-0.7C (wt%), and a lightweight steel powder with a relatively higher Al and C contents (Fe–30Mn-9.5Al-1.0C (wt%)) was then deposited on the surface of base steel plate through laser powder bed fusion (L-PBF). After L-PBF, an aging treatment led to more precipitation of κ-carbides in the surface layer, producing a functionally graded hard surface layer. A developed surface-hardened ductile lightweight steel thus has the potential to replace conventional wear-resistant steels, as it has excellent tensile ductility (51 %), high surface hardness (410 HV), high wear resistance, and 12 % lower mass density.
Sebastian Baltes, Florian Angermeir, Chetan Arora
et al.
Large Language Models (LLMs) are now ubiquitous in software engineering (SE) research and practice, yet their non-determinism, opaque training data, and rapidly evolving models threaten the reproducibility and replicability of empirical studies. We address this challenge through a collaborative effort of 22 researchers, presenting a taxonomy of seven study types that organizes the landscape of LLM involvement in SE research, together with eight guidelines for designing and reporting such studies. Each guideline distinguishes requirements (must) from recommended practices (should) and is contextualized by the study types it applies to. Our guidelines recommend that researchers: (1) declare LLM usage and role; (2) report model versions, configurations, and customizations; (3) document the tool architecture beyond the model; (4) disclose prompts, their development, and interaction logs; (5) validate LLM outputs with humans; (6) include an open LLM as a baseline; (7) use suitable baselines, benchmarks, and metrics; and (8) articulate limitations and mitigations. We complement the guidelines with an applicability matrix mapping guidelines to study types and a reporting checklist for authors and reviewers. We maintain the study types and guidelines online as a living resource for the community to use and shape (llm-guidelines$.$org).
Allysson Allex Araújo, Marcos Kalinowski, Maria Teresa Baldassarre
In recent years, Software Engineering (SE) scholars and practitioners have emphasized the importance of integrating soft skills into SE education. However, teaching and learning soft skills are complex, as they cannot be acquired passively through raw knowledge acquisition. On the other hand, hackathons have attracted increasing attention due to their experiential, collaborative, and intensive nature, which certain tasks could be similar to real-world software development. This paper aims to discuss the idea of hackathons as an educational strategy for shaping SE students' soft skills in practice. Initially, we overview the existing literature on soft skills and hackathons in SE education. Then, we report preliminary empirical evidence from a seven-day hybrid hackathon involving 40 students. We assess how the hackathon experience promoted innovative and creative thinking, collaboration and teamwork, and knowledge application among participants through a structured questionnaire designed to evaluate students' self-awareness. Lastly, our findings and new directions are analyzed through the lens of Self-Determination Theory, which offers a psychological lens to understand human behavior. This paper contributes to academia by advocating the potential of hackathons in SE education and proposing concrete plans for future research within SDT. For industry, our discussion has implications around developing soft skills in future SE professionals, thereby enhancing their employability and readiness in the software market.
Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that span the entire development lifecycle. Although software engineering research has extensively studied AI tools in software development, the specific types of interactions between developers and these AI-powered tools have only recently begun to receive attention. Understanding and improving these interactions has the potential to enhance productivity, trust, and efficiency in AI-driven workflows. In this paper, we propose a taxonomy of interaction types between developers and AI tools, identifying eleven distinct interaction types, such as auto-complete code suggestions, command-driven actions, and conversational assistance. Building on this taxonomy, we outline a research agenda focused on optimizing AI interactions, improving developer control, and addressing trust and usability challenges in AI-assisted development. By establishing a structured foundation for studying developer-AI interactions, this paper aims to stimulate research on creating more effective, adaptive AI tools for software development.
Jonathan Ullrich, Matthias Koch, Andreas Vogelsang
With the advent of generative LLMs and their advanced code generation capabilities, some people already envision the end of traditional software engineering, as LLMs may be able to produce high-quality code based solely on the requirements a domain expert feeds into the system. The feasibility of this vision can be assessed by understanding how developers currently incorporate requirements when using LLMs for code generation-a topic that remains largely unexplored. We interviewed 18 practitioners from 14 companies to understand how they (re)use information from requirements and other design artifacts to feed LLMs when generating code. Based on our findings, we propose a theory that explains the processes developers employ and the artifacts they rely on. Our theory suggests that requirements, as typically documented, are too abstract for direct input into LLMs. Instead, they must first be manually decomposed into programming tasks, which are then enriched with design decisions and architectural constraints before being used in prompts. Our study highlights that fundamental RE work is still necessary when LLMs are used to generate code. Our theory is important for contextualizing scientific approaches to automating requirements-centric SE tasks.
Redouane Oubah, Latifa Ouadif, Youssef Zerradi
et al.
Among surface mining methods, strip mining is a widely used technique for extracting mineral resources. This method is suitable for most near-surface stratiform sedimentary deposits and has historically been linked to surface mining of deposits such as coal, phosphates, and other natural substances. Given the significant economic interest that strip mining represents, it is in the best interest of mining companies to exploit as much of the reserves as possible using this technique, as it offers many advantages compared to open-pit or underground methods, particularly regarding safety and ore recovery rates. Today, the exploited deposits have become deeper, making the strip mining process more complex. Hence, there is a need for certain adaptations and the introduction of new techniques to address these geological conditions that threaten the feasibility of this method. This article explores the challenges that strip mining faces in contexts of thick overburden and subsequently presents the various techniques proposed by researchers worldwide aimed at overcoming these difficulties. The paper is based on an in-depth review of existing literature that deals with case studies of open-cast mines in different contexts. The examination of various approaches and techniques used for optimizing exploitation under thick overburden conditions by strip mining, along with their limitations, is presented.
Transition metal borides have emerged as pivotal players in various fields. In addition to their exceptional properties such as high hardness, a high melting point, and corrosion resistance, certain compounds exhibit remarkable characteristics including superconductivity, magnetism, electrical conductivity, and catalytic activity. Among these compounds, ZrB<sub>12</sub> has garnered significant attention due to its unique physicochemical properties. However, previous research on ZrB<sub>12</sub> has predominantly focused on its mechanical behavior while overlooking the electron-electron interactions of the superconducting state. In this paper, resistance characterization of ZrB<sub>12</sub> under high-pressure conditions was conducted to further investigate its superconductivity. Our research findings indicate that ZrB<sub>12</sub> maintains its superconductivity within a pressure range of 0 to 1.5 GPa and is classified as a type 2 superconductor. Additionally, the results confirm the anisotropic nature of ZrB<sub>12</sub>’s superconductivity. As the pressure increases, the superconducting transition temperature undergoes a gradual decrease. Remarkably, ZrB<sub>12</sub> exhibits metallic behavior under pressures up to 31.4 GPa. The observed decline in superconductivity in ZrB<sub>12</sub> can be ascribed to the intensified influence of Zr’s movement on phonon dispersion, ultimately leading to a reduction in carrier concentration.
Electrode wear during electrical discharge machining (EDM) is inevitable, and tool electrodes of different materials exhibit different wear rates. Unlike a single-material tool electrode, for a laminated electrode consisting of various material foils (LE-VMF), the components suffer from significantly different amounts of wear and also influence each other in EDM, however, the form and cause of the wear are not clear. Thus, the LE-VMFs including symmetric and asymmetric LE-VMFs were prepared and used in EDM in this paper. The wear of foils in LE-VMFs and their mutual influence during the EDM process were investigated through experiments. The wear forms of a single foil electrode and a foil of the same material in the LE-VMF were also compared. The experimental results show that copper foil with a lower wear rate had a protective effect on an adjacent brass foil with a larger wear rate in the LE-VMF, while the protective effect of the brass foil in the symmetric LE-VMF was larger than that in the asymmetric LE-VMF. The closer the distance from the copper foil, the stronger was the protection effect and the smaller was the wear. In addition, the working surface of the brass foil in the LE-VMF did not show any concavity-like wear in the middle region of its thickness after EDM, as was the case for the single brass foil electrode, even if the thickness of the brass foil was greater than 150 μm.
Grain growth of magnesium (Mg) and its hydride is one of the main reasons for kinetic and capacity degradation during the hydrogen absorption and desorption cycles. To solve this problem, herein we propose a novel method involving synergistic effect of inside embedded metals and outside coated graphene to limit the growth of Mg and its hydride grains. The graphene coated Mg‒Y‒Al alloys were selected as a model system for demonstrating this positive effect where the Mg91Y3Al6 alloy was first prepared by rapidly solidified method and then high-pressure milled with 5 wt% graphene upon 5 MPa hydrogen gas for obtaining in-situ formed YAl2 and YH3 embedded in the MgH2 matrix with graphene shell (denoted as MgH2-Y-Al@GR). In comparison to pure MgH2, the obtained MgH2-Y-Al@GR composites deliver much better kinetics and more stable cyclic performance. For instance, the MgH2-Y-Al@GR can release about 6.1 wt% H2 within 30 min at 300°C but pure MgH2 only desorbs ∼1.5 wt% H2. The activation energy for desorption of MgH2-Y-Al@GR samples is calculated to be 75.3±9.1 kJ/mol that is much lower than approximately 160 kJ/mol for pure MgH2. Moreover, its capacity retention is promoted from ∼57% of pure MgH2 to ∼84% after 50th cycles without obvious particle agglomeration and grain growth. The synergistic effect of outside graphene coating with inside embedded metals which could provide a huge number of active sites for catalysis as well as inhibit the grain growth of Mg and its hydride is believed to be responsible for these.
Software practitioners discuss problems at work with peers, in-person and online. These discussions can be technical (e.g., how to fix a bug?) and social (e.g., how to assign work fairly?). While there is a growing body of knowledge exploring fairness problems and solutions in the human and social factors of software engineering, most focus has been on specific problems. This study provides fairness discussions by software practitioners on Stack Exchange sites. We present an exploratory study presenting the fairness experience of software practitioners and fairness expectations in software teams. We also want to identify the fairness aspects software practitioners talk about the most. For example, do they care more about fairness in income or how they are treated in the workplace? Our investigation of fairness discussions on eight Stack Exchange sites resulted in a list of 136 posts (28 questions and 108 answers) manually curated from 4,178 candidate posts. The study reveals that the majority of fairness discussions (24 posts) revolve around the topic of income suggesting that many software practitioners are highly interested in matters related to their pay and how it is fairly distributed. Further, we noted that while not discussed as often, discussions on fairness in recruitment tend to receive the highest number of views and scores. Interestingly, the study shows that unfairness experiences extend beyond the protected attributes. In this study, only 25 out of 136 posts mention protected attributes, with gender mainly being discussed.