Daniel Rodriguez-Cardenas, Xiaochang Li, Marcos Macedo
et al.
Large language models for code are advancing fast, yet our ability to evaluate them lags behind. Current benchmarks focus on narrow tasks and single metrics, which hide critical gaps in robustness, interpretability, fairness, efficiency, and real-world usability. They also suffer from inconsistent data engineering practices, limited software engineering context, and widespread contamination issues. To understand these problems and chart a path forward, we combined an in-depth survey of existing benchmarks with insights gathered from a dedicated community workshop. We identified three core barriers to reliable evaluation: the absence of software-engineering-rich datasets, overreliance on ML-centric metrics, and the lack of standardized, reproducible data pipelines. Building on these findings, we introduce BEHELM, a holistic benchmarking infrastructure that unifies software-scenario specification with multi-metric evaluation. BEHELM provides a structured way to assess models across tasks, languages, input and output granularities, and key quality dimensions. Our goal is to reduce the overhead currently required to construct benchmarks while enabling a fair, realistic, and future-proof assessment of LLMs in software engineering.
Paloma Guenes, Rafael Tomaz, Maria Teresa Baldassarre
et al.
The Impostor Phenomenon (IP) impacts a significant portion of the Software Engineering workforce, yet it is often viewed primarily through an internal individual lens. In this position paper, we propose framing the prevalence of IP as a form of Human Debt and discuss the relation with the ICSE2026 Pre Survey on the Future of Software Engineering results. Similar to technical debt, which arises when short-term goals are prioritized over long-term structural integrity, Human Debt accumulates due to gaps in psychological safety and inclusive support within socio-technical ecosystems. We observe that this debt is not distributed equally, it weighs heavier on underrepresented engineers and researchers, who face compounded challenges within traditional hierarchical structures and academic environments. We propose cultural refactoring, transparency and active maintenance through allyship, suggesting that leaders and institutions must address the environmental factors that exacerbate these feelings, ensuring a sustainable ecosystem for all professionals.
Mauro Marcelino, Marcos Alves, Bianca Trinkenreich
et al.
[Context] An evidence briefing is a concise and objective transfer medium that can present the main findings of a study to software engineers in the industry. Although practitioners and researchers have deemed Evidence Briefings useful, their production requires manual labor, which may be a significant challenge to their broad adoption. [Goal] The goal of this registered report is to describe an experimental protocol for evaluating LLM-generated evidence briefings for secondary studies in terms of content fidelity, ease of understanding, and usefulness, as perceived by researchers and practitioners, compared to human-made briefings. [Method] We developed an RAG-based LLM tool to generate evidence briefings. We used the tool to automatically generate two evidence briefings that had been manually generated in previous research efforts. We designed a controlled experiment to evaluate how the LLM-generated briefings compare to the human-made ones regarding perceived content fidelity, ease of understanding, and usefulness. [Results] To be reported after the experimental trials. [Conclusion] Depending on the experiment results.
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.
Marc Bruni, Fabio Gabrielli, Mohammad Ghafari
et al.
Prompt engineering reduces reasoning mistakes in Large Language Models (LLMs). However, its effectiveness in mitigating vulnerabilities in LLM-generated code remains underexplored. To address this gap, we implemented a benchmark to automatically assess the impact of various prompt engineering strategies on code security. Our benchmark leverages two peer-reviewed prompt datasets and employs static scanners to evaluate code security at scale. We tested multiple prompt engineering techniques on GPT-3.5-turbo, GPT-4o, and GPT-4o-mini. Our results show that for GPT-4o and GPT-4o-mini, a security-focused prompt prefix can reduce the occurrence of security vulnerabilities by up to 56%. Additionally, all tested models demonstrated the ability to detect and repair between 41.9% and 68.7% of vulnerabilities in previously generated code when using iterative prompting techniques. Finally, we introduce a "prompt agent" that demonstrates how the most effective techniques can be applied in real-world development workflows.
A well-rounded software engineer is often defined by technical prowess and the ability to deliver on complex projects. However, the narrative around the ideal Software Engineering (SE) candidate is evolving, suggesting that there is more to the story. This article explores the non-technical aspects emphasized in SE job postings, revealing the sociotechnical and organizational expectations of employers. Our Thematic Analysis of 100 job postings shows that employers seek candidates who align with their sense of purpose, fit within company culture, pursue personal and career growth, and excel in interpersonal interactions. This study contributes to ongoing discussions in the SE community about the evolving role and workplace context of software engineers beyond technical skills. By highlighting these expectations, we provide relevant insights for researchers, educators, practitioners, and recruiters. Additionally, our analysis offers a valuable snapshot of SE job postings in 2023, providing a scientific record of prevailing trends and expectations.
LI Zheng, CAO Shu-long, ZHU Hai-qin, XIE Ping, JIA Bao-jie
[Objective] Water-level fluctuation zone (WLFZ) represents a key challenge for managing carbon emissions from global reservoirs. The Three Gorges Reservoir (TGR) has become a key focus for investigating the emission of greenhouse gases, such as carbon dioxide (CO2). Previous studies have not yielded consistent findings regarding the correlation between different elevations and soil carbon release — a gap that limits an accurate understanding of carbon cycling mechanisms in the reservoir’s WLFZ and hinders effective carbon emission management. [Methods] This study explored soil carbon emission characteristics in the near-dam WLFZ of TGR under fluctuating water levels. Soil respiration rates were measured using the Li-8100 Automated Soil CO2 Flux System. Two representative WLFZs—Longtanping and Lanlingxi—were selected, and within each area, three elevation intervals were established: below 160 m, 160-170 m, and above 170 m. This design ensured that the data would reflect the impact of water level fluctuations on soil carbon emissions across different WLFZ segments. One-way analysis of variance (ANOVA) in SPSS 25.0 was applied to examine differences in soil respiration across elevations and seasons. [Results] No positive correlation was found between elevation and soil respiration. Instead, as elevation increased, soil respiration across the entire study area exhibited a trend of first rising and then falling, with the maximum rate observed under moderate flooding stress. Specifically, the peak soil respiration rate reached 3.91 μmol/m2/s in Longtanping and 2.69 μmol/m2/s in Lanlingxi, with an average of 3.30 μmol/m2/s. This suggested that moderate flooding created optimal conditions for soil microbial activity and organic matter decomposition—two processes that drove carbon emission—whereas excessive or insufficient flooding inhibited these biological activities, reducing respiration rates. When the two WLFZs were analyzed comprehensively and Lanlingxi individually, no significant difference in soil respiration was found between the below-160 m and above-170 m intervals. However, in Longtanping, soil respiration above 170 m was slightly higher than that below 160 m. This regional discrepancy might be attributed to differences in local environmental factors, such as soil texture, organic matter content, vegetation coverage, or microbial community composition. Soil respiration exhibited significant temporal variability. Overall, the seasonal trend showed rates in July and August being highest, followed by September, June, and May. Minor differences existed between the two WLFZs: Longtanping showed a pattern where rates in July and August were highest, followed by September and June, and then May, while Lanlingxi displayed a pattern where rates in July, August, and September were equal and higher than June and May. Nevertheless, both areas recorded their peak soil respiration in August, with the highest rates occurring in the 160-170 m interval: 6.97 μmol/m2/s in Longtanping and 4.58 μmol/m2/s in Lanlingxi. The elevated summer respiration rates (especially in July and August) were primarily linked to vigorous vegetation growth and metabolic activity during this period. Vegetation contributed to carbon emission by releasing organic matter through root exudation and litterfall (providing substrates for microbes) and enhancing soil aeration via root respiration (facilitating microbial decomposition). [Conclusion] Moderate dry-wet alternation (i.e., moderate flooding stress) maximizes soil carbon emissions in the study area, while extreme flooding (either too high or too low) suppresses emission intensity. Summer, characterized by robust vegetation growth and metabolism, shows significantly higher soil respiration than other seasons—with July and August showing particularly high rates, and the moderately flooded zones in August recording the peak. The findings of this study have both theoretical and practical value. Theoretically, they enhance the understanding of carbon cycling in large reservoir WLFZ and contribute to global carbon cycle research. Practically, they provide a scientific basis for the quantitative analysis of carbon emissions in the Three Gorges Reservoir’s WLFZs and support future studies on carbon cycling following WLFZ ecological restoration. This information can further guide water level management strategies to regulate soil carbon emissions, aiding global carbon neutrality efforts and the sustainable development of the reservoir ecosystem.
River, lake, and water-supply engineering (General)
ABSTRACT Productive agricultural supply chains require the support of functional ecosystems, but intense agricultural practices change local hydrological systems (e.g. river diversion). In this study, the impact of farm dams was assessed for the Verlorenvlei catchment, a sensitive ecosystem currently under a state of hydrological change in South Africa. We developed a new module for the Jena Adaptable Modelling System (JAMS)/J2000 rainfall–runoff model to assess the streamflow impact from the points of abstraction, losses during storage and irrigation. The model achieved a satisfactory streamflow calibration with efficiencies Nash Sutcliffe Efficiency (NSE, logNSE) of 0.52 and 0.51. The irrigated area reduced simulated streamflow by 12 to 19%. The results from the study agree with remote sensed evapotranspiration, measured lake surface water levels and streamflow, but uncertainty remains in the total simulated dam evaporation. While many catchments lack the data required for a detailed irrigation impact assessment, this approach considers total water use, dam storage to area relationships and general farming practices.
Participatory citizen platforms are innovative solutions to digitally better engage citizens in policy-making and deliberative democracy in general. Although these platforms have been used also in an engineering context, thus far, there is no existing work for connecting the platforms to requirements engineering. The present paper fills this notable gap. In addition to discussing the platforms in conjunction with requirements engineering, the paper elaborates potential advantages and disadvantages, thus paving the way for a future pilot study in a software engineering context. With these engineering tenets, the paper also contributes to the research of large socio-technical software systems in a public sector context, including their implementation and governance.
In this paper we address the following question: How can we use Large Language Models (LLMs) to improve code independently of a human, while ensuring that the improved code - does not regress the properties of the original code? - improves the original in a verifiable and measurable way? To address this question, we advocate Assured LLM-Based Software Engineering; a generate-and-test approach, inspired by Genetic Improvement. Assured LLMSE applies a series of semantic filters that discard code that fails to meet these twin guarantees. This overcomes the potential problem of LLM's propensity to hallucinate. It allows us to generate code using LLMs, independently of any human. The human plays the role only of final code reviewer, as they would do with code generated by other human engineers. This paper is an outline of the content of the keynote by Mark Harman at the International Workshop on Interpretability, Robustness, and Benchmarking in Neural Software Engineering, Monday 15th April 2024, Lisbon, Portugal.
Abstract Under warming conditions and with increasing human perturbations, rivers across the globe are facing drastic shifts in their hydrologic regime, resulting in fragmentation and disconnection from the catchment. Subsequently, a dependency on in situ primary productivity as the source of organic matter increases and warrants detailed investigation of the nature of primary production in urbanized river systems. In this study, primary productivity was estimated at multiple locations along the continuum of an engineered (Sabarmati) and a free flowing (Mahi) river systems in India using 13C tracer incubation method. Significantly enhanced primary productivity in the riverfront (engineered construction along the Sabarmati that holds water supplied by a canal) and polluted downstream of the Sabarmati compared to free flowing Mahi was observed. It was also observed that water stagnancy, temperature, and nutrient availability were the key factors regulating the rates of primary productivity in the urban river system. The study highlights the salient features of riverine primary productivity associated with engineered modifications, which needs to be considered for future river development projects.
Oceanography, River, lake, and water-supply engineering (General)
Since the 20th century, earth-rockfill dam instability accidents have occurred frequently all over the world. In order to systematically summarize the current status and hotspots of research on earth-rockfill dam stability and analyze the future development trend of earth-rockfill dam stability, this paper sorted out the factors of earth-rockfill dam instability found by Chinese and foreign scholars and carried out a comparative analysis. Since The instability modes of earth-rockfill dams are complex and varied, the research on the different instability modes of earth-rockfill dams by Chinese and foreign scholars was summarized. In terms of theoretical calculation, the calculation models developed by Chinese and foreign scholars for the instability of earth-rockfill dams were systematically sorted out, and the applicability of different calculation models was compared. In order to quantitatively and visually analyze the research hotspots and trends of Chinese and foreign scholars on the instability of earth-rockfill dam, CiteSpace was used to analyze 1 197 papers on the stability of earth-rockfill dam in CNKI and Web of Science in the past 15 years from 2009 to 2023, and the research dynamics of the field in the past 15 years were comprehensively and visually analyzed according to the author groups, research institutions, and keyword clustering. The development trend of the existing research, as well as the related problems and future research work, were discussed and prospected from a macro perspective. The future research direction of the stability of earth-rockfill dams, as well as the difficulties and hotspots of the current research were summarized.
River, lake, and water-supply engineering (General)
Water control dikes, as an important infrastructure for national economic and social development, play an important supporting and guaranteeing role in flood control, irrigation, power generation, water supply, tourism, and other aspects. Jiangxi is a major province in water conservancy, with dense rivers and lakes, and it owns tens of thousands of water control dikes of various types. Most of the water control dikes exhibit structural aging, continuous medical risks, and reduced benefits, which urgently require efficient maintenance and standardized management. Management is a complex task, and the level of management directly affects the functional efficiency and service life of dikes. In view of these issues, this study takes dikes as essential and typical water conservancy engineering objects and analyzes the evaluation criteria of safe production and the demands of engineering management. It establishes an evaluation index system suitable for normalized management. The Analytic Hierarchy Process (AHP) model is utilized to determine indicator weights, and a neural network water conservancy engineering evaluation algorithm is constructed to match the evaluation model. Finally, an improved algorithm for the GA (genetic algorithm)-BP (backpropagation) neural network is proposed, incorporating additional momentum factors and considering adaptive learning rates. The developed model is validated through a case study in Jiangxi, China, and the results demonstrate its accuracy and comprehensiveness in reflecting the actual situation. This research is relevant to designers, contractors, and governments seeking solutions to achieve standardized management in water control dikes.
Stop words, which are considered non-predictive, are often eliminated in natural language processing tasks. However, the definition of uninformative vocabulary is vague, so most algorithms use general knowledge-based stop lists to remove stop words. There is an ongoing debate among academics about the usefulness of stop word elimination, especially in domain-specific settings. In this work, we investigate the usefulness of stop word removal in a software engineering context. To do this, we replicate and experiment with three software engineering research tools from related work. Additionally, we construct a corpus of software engineering domain-related text from 10,000 Stack Overflow questions and identify 200 domain-specific stop words using traditional information-theoretic methods. Our results show that the use of domain-specific stop words significantly improved the performance of research tools compared to the use of a general stop list and that 17 out of 19 evaluation measures showed better performance. Online appendix: https://zenodo.org/record/7865748
We adapt the post-Newtonian gravitational-radiation methods developed within general relativity by Epstein and Wagoner to the gravitation theory with torsion, recently proposed by Hehl et al., and show that the two theories predict in this approximation the same gravitational radiation losses. Since they agree also on the first post-Newtonian level, they are at the present time - observationally - indistinguishable.
Studying the spatial management scope of the river ecological corridor is a crucial step in effectively managing river health problems. For various purposes and needs, human beings intervene excessively in the river, resulting in the problems of unclear spatial scope, unclear ownership, and unreasonable functional utilization of the river ecological corridor. However, there is scarce research on the management scope of the river ecological corridor at present, and on the coordination relationship with territorial spatial protection planning. Therefore, in order to solve this key problem, this paper reviews and summarizes the current research status and development trends in terms of the concept, components, and other basic theories of the river ecological corridor, as well as relevant policy regulations. The relationship between the spatial scope of the river ecological corridor and the territorial spatial control line is analyzed, including the relationship with the river shoreline, aquatic ecological redline, “three control lines” and other control lines. Accordingly, this study reviewed the spatial management and control scope of the river ecological corridor. It also determined that the boundary line of the river shoreline management is the minimum line, the aquatic ecological redline, and the “three control lines” are the outermost boundary lines, in which the aquatic ecological redline has priority over other control lines. It also points out the thinking of determining the management scope in the protection and restoration of the river ecological corridor in the future. Our findings can provide a decision-making basis for the management of river ecological space.
Model-Based Systems Engineering aims at creating a model of a system under development, covering the complete system with a level of detail that allows to define and understand its behavior and enables to define any interface and workpackage based on the model. Once such a model is established, further benefits can be reaped, such as the analysis of complex technical correlations within the system. Various insights can be gained by displaying the model as a formal graph and querying it. To enable such queries, a graph schema needs to be designed, which allows to transfer the model into a graph database. In the course of this paper, we discuss the design of a graph schema and MBSE modelling approach, enabling deep going system analysis and anomaly resolution in complex embedded systems. The schema and modelling approach are designed to answer questions such as what happens if there is an electrical short in a component? Which other components are now offline and which data cannot be gathered anymore? Or if a condition cannot be met, which alternative routes can be established to reach a certain state of the system. We build on the use case of qualification and operations of a small spacecraft. Structural and behavioral elements of the MBSE model are transferred to a graph database where analyses are conducted on the system. The schema is implemented by an adapter for MagicDraw to Neo4j. A selection of complex analyses are shown on the example of the MOVE-II space mission.
Raffaele G. Cestari, Andrea Castelletti, Simone Formentin
The optimal operation of regulated lakes is a challenging task involving conflicting objectives, ranging from controlling lake levels to avoid floods and low levels to water supply downstream. The traditional approach to operation policy design is based on an offline optimization, where a feedback control rule mapping lake storage into daily release decisions is identified over a set of observational data. In this paper, we propose a receding-horizon policy for a more frequent, online regulation of the lake level, and we discuss its tuning as compared to benchmark approaches. As side contributions, we provide a daily alternative based on the same rationale, and we show that this is still valid under some assumptions on the water inflow. Numerical simulations are used to show the effectiveness of the proposed approach. We demonstrate the approach on the regulated lake Como, Italy.
The rain-sewage diversion project in the dense housing area of urban villages involves a large amount of trench excavation,which leads to prominent safety problems in construction.The safety monitoring and analysis of trench excavation are characterized by high requirements,complex data association,and poor data conditions,and thus we propose a theoretical method of organic integration of land subsidence mechanisms and data analysis process.The intelligent analysis method for land subsidence in trench excavation is based on digital twin technology,which integrates data and knowledge to realize visualized real-time monitoring,prediction,and control of land subsidence in urban villages.The method extracts and expresses the scenes,processes,objects,problems,and knowledge of the whole life cycle of land subsidence in survey and design,trial excavation,and formal excavation construction,and a big data analysis model of land subsidence based on data-knowledge fusion is developed.The research results can provide a scientific basis for the safety decision-making of excavation construction in the dense housing area of urban villages.
River, lake, and water-supply engineering (General)