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.
The adoption of Generative AI (GenAI) suggests major changes for software engineering, including technical aspects but also human aspects of the professionals involved. One of these aspects is how individuals perceive themselves regarding their work, i.e., their work identity, and the processes they perform to form, adapt and reject these identities, i.e., identity work. Existent studies provide evidence of such identity work of software professionals triggered by the adoption of GenAI, however they do not consider differences among diverse roles, such as developers and testers. In this paper, we argue the need for considering the role as a factor defining the identity work of software professionals. To support our claim, we review some studies regarding different roles and also recent studies on how to adopt GenAI in software engineering. Then, we propose a research agenda to better understand how the role influences identity work of software professionals triggered by the adoption of GenAI, and, based on that, to propose new artifacts to support this adoption. We also discuss the potential implications for practice of the results to be obtained.
The article explores the revitalization of Italy's "inner areas" - —fragile territories facing challenges such as depopulation, abandonment, and a lack of essential services, primarily due to limited mobility. The enhancement of secondary and disused railways is proposed as a tool for territorial rebalancing, to be achieved through multilevel governance that integrates spatial planning, interinstitutional cooperation, and the strategic allocation of financial and economic resources. This approach aims to move beyond sectoral perspectives on infrastructure networks.
The Axis Contract is introduced as an integrated framework linking urban planning and mobility, centered on the right to mobility and the empowerment of local communities.
The article is structured into three parts: the first examines the relationship between territory, mobility, and infrastructure policies; the second analyzes the French Contrat d’axe model and its applicability in Italy; and the third presents the results of an interdisciplinary study on the reactivation of the Civitavecchia -Capranica - Orte railway line.
The findings confirm that the Axis Contract is an effective tool for integrating urban and mobility planning, addressing accessibility needs, and promoting the sustainable rebalancing of territories.
Transportation engineering, Urbanization. City and country
Saber Hadj Abdallah, Motab Turki Almousa, Fatma Ben Salem
et al.
This paper presents a comparative study between two permanent magnet motor structures, one with trapezoidal waveforms and the other with sinusoidal waveforms, from the perspective of production cost, dynamic characteristic performance, and energy economy. The novel element of the research is also in using an electromagnetic converter to reduce the vehicle’s overall energy consumption and to push the multiple disadvantages of using the insolated bipolar transistors. This study is based on the sizing of the electromagnetic converter and the two motor structures using the method of combined analytical finite elements. The program for sizing is coupled with two control laws relating to the motor types in order to choose the top performers according to good dynamic characteristics and energy saving. The simulation results show, on the one hand, the equivalence of these structures from a dynamic characteristic point of view and, on the other hand, that the trapezoidal waveform motor structure is more economical. The design of an excitation system optimizing the consumed energy equipped by a hybrid excitation motor is also developed.
Refactoring is the process of restructuring existing code without changing its external behavior while improving its internal structure. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and can automate or semi-automate this process to enhance code readability, reduce complexity, and improve the maintainability of software products. Similar to traditional software systems such as compilers, refactoring engines may also contain bugs that can lead to unexpected behaviors. In this paper, we propose a novel approach called RETESTER, a LLM-based framework for automated refactoring engine testing. Specifically, by using input program structure templates extracted from historical bug reports and input program characteristics that are error-prone, we design chain-of-thought (CoT) prompts to perform refactoring-preserving transformations. The generated variants are then tested on the latest version of refactoring engines using differential testing. We evaluate RETESTER on two most popular modern refactoring engines (i.e., ECLIPSE, and INTELLIJ IDEA). It successfully revealed 18 new bugs in the latest version of those refactoring engines. By the time we submit our paper, seven of them were confirmed by their developers, and three were fixed.
Large Language Models are transforming software engineering, yet prompt management in practice remains ad hoc, hindering reliability, reuse, and integration into industrial workflows. We present Prompt-with-Me, a practical solution for structured prompt management embedded directly in the development environment. The system automatically classifies prompts using a four-dimensional taxonomy encompassing intent, author role, software development lifecycle stage, and prompt type. To enhance prompt reuse and quality, Prompt-with-Me suggests language refinements, masks sensitive information, and extracts reusable templates from a developer's prompt library. Our taxonomy study of 1108 real-world prompts demonstrates that modern LLMs can accurately classify software engineering prompts. Furthermore, our user study with 11 participants shows strong developer acceptance, with high usability (Mean SUS=73), low cognitive load (Mean NASA-TLX=21), and reported gains in prompt quality and efficiency through reduced repetitive effort. Lastly, we offer actionable insights for building the next generation of prompt management and maintenance tools for software engineering workflows.
Introduction. The theoretical basis for the development of indicators for improving the training and retraining of road transport personnel is aimed, first of all, at ensuring the results of transportation and technical operation activities corresponding to the output in road transport. The studied indicators should take into account the amount of labor costs of all types of workers ensuring the operation of rolling stock. Training and retraining of personnel largely determine the safety of the transportation process and must comply with the existing operating conditions of rolling stock. The purpose of this article is to theoretically substantiate the indicators for improving the training and retraining of specialists and personnel of road transport, as an element of the “personnel-bus-road-operating environment” (PADS) system to ensure the planned production of rolling stock in accordance with the requirements of the municipal contract for regular passenger transportation and luggage, taking into account operating conditions.Materials and methods. The theoretical basis for the development of indicators for improving the training and retraining of personnel is based on a systematic analysis of professional and qualification requirements, as well as the theory of current planning of the work of motor transport enterprises, taking into account the probabilistic nature of operating conditions under the influence of the external environment. As a result, structural connections between the driver, mechanic and technical condition inspector were identified as elements of the new PADS system.The parameters of the developed mathematical model of personnel activities and the costs of their training and retraining are determined using methods of mathematical statistics and expert assessments. The content of the new approach is to integrate the production of rolling stock with professional and qualification requirements for personnel.Results. This study focuses on fulfilling the municipal contract for regular transportation of passengers and luggage, i.e. to obtain the planned mileage, it is necessary to take into account the joint activities of groups of personnel and in each group of an individual employee.Discussion and conclusion. The scientific novelty and main results of the study consist in the theoretical substantiation of indicators for improving the training and retraining of passenger road transport personnel, as an element of the PADS system, to ensure the planned production of rolling stock, taking into account operating conditions.Based on the results of the study, the indicators of training and retraining of personnel of automobile passenger transport, ensuring the fulfillment of the contract, are grouped in accordance with their levels and periods of formation.A mathematical model that determines the planning of the results of fulfilling the terms of the contract by each employee has been developed. Further research will be aimed at experimentally determining the values of the identified indicators.
The conquest of new public spaces is one of the main options in processes of urban regeneration. It seems essential in contemporary cities, since our life occurs more and more indoors and in private contexts, reducing the role of public and outdoor activities. Among cultural-based urban regeneration projects that operate within those spaces waiting for an improvement of the existing public functions, schools can play a particularly prominent role, as well spread and symbolic institutions with an educational mission for young people. From this perspective, the paper discusses how school squares, namely the urban areas close to the entrance of schools, can be designed and regenerated to produce a real public space where the city meets the school and vice versa. The paper presents a methodology to classify different typologies of school squares, based on an extensive analysis on over 600 school squares, located in the provinces of Milan, Turin and Varese. On the basis of such classification, some guidelines are discussed in order to propose a strategy to redesign these symbolic spaces and to conquer them as public areas.
Transportation engineering, Urbanization. City and country
[Objective] The large-diameter shield section on Shanghai City Railway Airport Link Line is parallel to the existing Shanghai-Hangzhou High-speed Railway. Due to strict deformation control requirements of high-speed railway subgrade, it is necessary to conduct in-depth research on the influence law of subgrade deformation caused by large-diameter shield parallel construction on existing high-speed railway. [Method] Based on Shanghai City Railway Airport Link Line engineering, in the process of large-diameter shield parallel construction, through field-monitoring of the existing high-speed railway subgrade, the land subsidence and the high-speed railway subgrade base plate displacement are monitored respectively. Based on field measurement data, the influence law of large-diameter shield parallel construction reinforced with portal isolation piles on soil disturbance and high-speed railway subgrade deformation is analyzed. [Result & Conclusion] Upon completion of shield construction, the maximum land subsidence occurs right above the tunnel, with ground heave at far end from the high-speed subgrade and land subsidence at the closer end. The maximum total land subsidence during and after the shield construction process is 21.14 mm and 20.32 mm, respectively, meeting control requirements. The effect of shield construction on ground vertical displacement is mainly concentrated within 20 m before the cutterhead reaching the section and within 50 m after it passes the section. Portal isolation piles can effectively restrict the displacement of the soil mass outside piles, control high-speed railway subgrade deformation, thus providing good isolation effects. After the completion of shield construction, the maximum horizontal and vertical displacements of Shanghai-Hangzhou High-speed Railway subgrade are both 1.9 mm, indicating that the parallel shield construction did not affect the normal operation of Shanghai-Hangzhou High-speed Railway.
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.
With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models, by leveraging the power of deep learning and massive amounts of data, have demonstrated an unprecedented capacity to understand, generate, and operate programming languages. They can assist developers in completing a broad spectrum of software development activities, encompassing software design, automated programming, and maintenance, which potentially reduces huge human efforts. Integrating LLMs within the SE landscape (LLM4SE) has become a burgeoning trend, necessitating exploring this emergent landscape's challenges and opportunities. The paper aims at revisiting the software development life cycle (SDLC) under LLMs, and highlighting challenges and opportunities of the new paradigm. The paper first summarizes the overall process of LLM4SE, and then elaborates on the current challenges based on a through discussion. The discussion was held among more than 20 participants from academia and industry, specializing in fields such as software engineering and artificial intelligence. Specifically, we achieve 26 key challenges from seven aspects, including software requirement & design, coding assistance, testing code generation, code review, code maintenance, software vulnerability management, and data, training, and evaluation. We hope the achieved challenges would benefit future research in the LLM4SE field.
Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.
This paper integrates the Internet of Things (IoT) technology and a smart grid to build an electric power IoT architecture and analyzes the intelligent sensing technology and wireless communication technology in this electric power IoT. Through the multi-channel data collection technology in power IoT technology and an orthogonal discrete multiwavelet transform algorithm of edge computing technology, the high-voltage transmission line status data of the smart grid are collected and processed. Then, the high-voltage transmission line condition monitoring system is designed using the node design of the high-voltage transmission line condition monitoring sensing network and the optimal sensor configuration for droop monitoring. The performance of the monitoring system is simulated and examined. The experimental results show that as the number of burst data nodes increases, the acceptance rate of the ODMT algorithm decreases from 99% to 98%, and the network survival time is over 2000. When the current exceeds 20% of the rated current, the overall measurement error is controlled at approx. 3%. At a height of 4 m, the ratio of the difference between the input voltage and output voltage sensing monitoring is approx. 5%. The error range of temperature sensing monitoring is within ±1 °C. The error rate of communication distance within 200 m is 0, and over 200 m, the error rate is approx. 7%. This system can monitor the transmission status of high-voltage lines very well.
Starting from the relationship between urban planning and mobility management, TeMA has gradually expanded the view of the covered topics, always following a rigorous scientific in-depth analysis. This section of the Journal, Review Notes, is a continuous update about emerging topics concerning relationships among urban planning, mobility, and environment, thanks to a collection of short scientific papers written by young researchers. The Review Notes are made up of five parts. Each section examines a specific aspect of the broader information storage within the main interests of the TeMA Journal. In particular: the Town Planning International Rules and Legislation. Section aims at presenting the latest updates in the territorial and urban legislative sphere. The current challenges that today's cities have to face, from climate change to environmental and social ones, have led to urban planning being accompanied by the mobility system from a sustainable point of view. In turn, sustainable mobility constitutes that important link in the chain of development of cities. In this direction, the contribution explores in the first part how the scientific community is addressing the issue of sustainable mobility and what the new paradigms are, however, in the second part it focuses on the urban policies issued by the Italian government.
Transportation engineering, Urbanization. City and country