Hasil untuk "Harbors and coast protective works. Coastal engineering. Lighthouses"

Fuyuan Chen, Jian Zeng, Zhiyong Zhang et al.

In tidal estuarine regions, toe scour and deposition at seawalls, which are influenced by runoff and tidal flow, present complexities not found in inland rivers and wave-dominated coasts. Existing methods for predicting toe scour at seawalls are often inaccurate in estuarine environments and can be computationally demanding, limiting their practical application. Hence, there is a need for a simplified, reliable approach tailored to these dynamic settings. This study investigated the characteristics of toe scour and deposition through a case study in the Qiantang River Estuary on the basis of field data. We analyzed continuous monthly riverbed topography data from five cross-sections collected between 2011 and 2018 to examine riverbed profiles and their temporal variations in front of the seawall. In addition, we elucidated the underlying scour and deposition mechanisms. The results indicate that the riverbed slope at the seawall toe ranges from 14° to 27° over 50 m, whereas the riverbed flattens and significantly fluctuates between 50 and 100 m. Toe scour frequently occurs when the maximum daily average runoff discharge exceeds 5000 m3/s or when the average daily runoff discharge surpasses 2200 m3/s. Conversely, deposition is primarily observed with larger tidal ranges and lower runoff conditions. Furthermore, we developed a process-based prediction method (PPM) based on the sediment transport capacity to predict scour depths during various flood events. This method achieves a relative error within 20 %, showing improved accuracy over existing approaches. This study provides a reliable method to predict toe scour at seawalls in tidal estuaries, supporting safer seawall design and more effective maintenance strategies.

Mark Looi

The rapid advance of Generative AI into software development prompts this empirical investigation of perceptual effects on practice. We study the usage patterns of 147 professional developers, examining perceived correlates of AI tools use, the resulting productivity and quality outcomes, and developer readiness for emerging AI-enhanced development. We describe a virtuous adoption cycle where frequent and broad AI tools use are the strongest correlates of both Perceived Productivity (PP) and quality, with frequency strongest. The study finds no perceptual support for the Quality Paradox and shows that PP is positively correlated with Perceived Code Quality (PQ) improvement. Developers thus report both productivity and quality gains. High current usage, breadth of application, frequent use of AI tools for testing, and ease of use correlate strongly with future intended adoption, though security concerns remain a moderate and statistically significant barrier to adoption. Moreover, AI testing tools' adoption lags that of coding tools, opening a Testing Gap. We identify three developer archetypes (Enthusiasts, Pragmatists, Cautious) that align with an innovation diffusion process wherein the virtuous adoption cycle serves as the individual engine of progression. Our findings reveal that organizational adoption of AI tools follows such a process: Enthusiasts push ahead with tools, creating organizational success that converts Pragmatists. The Cautious are held in organizational stasis: without early adopter examples, they don't enter the virtuous adoption cycle, never accumulate the usage frequency that drives intent, and never attain high efficacy. Policy itself does not predict individuals' intent to increase usage but functions as a marker of maturity, formalizing the successful diffusion of adoption by Enthusiasts while acting as a gateway that the Cautious group has yet to reach.

Jingyue Li, André Storhaug

With the advancement of Agentic AI, researchers are increasingly leveraging autonomous agents to address challenges in software engineering (SE). However, the large language models (LLMs) that underpin these agents often function as black boxes, making it difficult to justify the superiority of Agentic AI approaches over baselines. Furthermore, missing information in the evaluation design description frequently renders the reproduction of results infeasible. To synthesize current evaluation practices for Agentic AI in SE, this study analyzes 18 papers on the topic, published or accepted by ICSE 2026, ICSE 2025, FSE 2025, ASE 2025, and ISSTA 2025. The analysis identifies prevailing approaches and their limitations in evaluating Agentic AI for SE, both in current research and potential future studies. To address these shortcomings, this position paper proposes a set of guidelines and recommendations designed to empower reproducible, explainable, and effective evaluations of Agentic AI in software engineering. In particular, we recommend that Agentic AI researchers make their Thought-Action-Result (TAR) trajectories and LLM interaction data, or summarized versions of these artifacts, publicly accessible. Doing so will enable subsequent studies to more effectively analyze the strengths and weaknesses of different Agentic AI approaches. To demonstrate the feasibility of such comparisons, we present a proof-of-concept case study that illustrates how TAR trajectories can support systematic analysis across approaches.

Da Liu, Hui Lin, Xiangju Cheng et al.

Foam pollution in the tailwater discharge from coastal power plants poses a significant challenge. However, the mechanisms underlying foam formation and stability remain understudied, which hinders the development of effective control strategies. This study investigated the impacts of temperature and algal concentration on foam stability in tailwater discharge from coastal power plants through simulation experiments to elucidate mechanisms of foam stability. A laboratory simulation device was developed to adjust temperature and algal concentration and measure foam layer height, half-life, bubble diameter, surface tension, and viscosity. This device was used to replicate foam scenarios typical of coastal power plant tailwater discharge to analyze the effects of temperature and algal concentration on foam stability through comprehensive data collection and analysis across various operational conditions. The findings revealed that foam stability decreased with increasing temperatures (15–45 °C). However, during hot summer months, higher temperatures (range of 30–40 °C) hindered foam dissipation owing to algal blooms and the release of surface-active substances. The functional relationship between foam stability index (half-life, foam layer height, bubble diameter) and temperature and algae concentration was established, which provides a scientific basis for predicting foam stability under different conditions. This research elucidates the complex dynamics of foam in the tailwater discharge from coastal power plants and provides insights for developing more effective foam control strategies, potentially mitigating adverse impacts on the marine ecosystem. In future research, by adding experimental conditions such as pH, ionic strength, and different types of protein polysaccharides, a more comprehensive understanding of the mechanism of bubble generation can be achieved, providing more accurate foam suppression optimization solutions for future engineering practices.

Luis Valderrama-Landeros, Iliana Pérez-Espinosa, Edgar Villeda-Chávez et al.

The city of Acapulco was impacted by two near-consecutive hurricanes. On 25 October 2023, Hurricane Otis made landfall, reaching the highest Category 5 storm on the Saffir–Simpson scale, causing extensive coastal destruction due to extreme winds and waves. Nearly one year later (23 September 2024), Hurricane John—a Category 2 storm—caused severe flooding despite its lower intensity, primarily due to its unusual trajectory and prolonged rainfall. Digital shoreline analysis of PlanetScope images (captured one month before and after Hurricane Otis) revealed that the southern coast of Acapulco, specifically Zona Diamante—where the major seafront hotels are located—experienced substantial shoreline erosion (94 ha) and damage. In the northwestern section of the study area, the Coyuca Bar experienced the most dramatic geomorphological change in surface area. This was primarily due to the complete disappearance of the bar on October 26, which resulted in a shoreline retreat of 85 m immediately after the passage of Hurricane Otis. Sentinel-1 Synthetic Aperture Radar (SAR) showed that Hurricane John inundated 2385 ha, four times greater than Hurricane Otis’s flooding (567 ha). The retrofitted QGIS methodology demonstrated high reliability when compared to limited in situ local reports. Given the increased frequency of intense hurricanes, these methods and findings will be relevant in other coastal areas for monitoring and managing local communities affected by severe climate events.

Salika Thilakarathne, Hesamodin Enayatighadikolaei, Md Shofiqul Islam et al.

We analyse a 36-year hydrodynamic and morphological dataset from the Hasaki coast, Japan, comprising 501 wave storm events (405 individual and 96 clustered events) to investigate the impact of storm dynamics and clustering on beach erosion. Focusing on the wave component of storms, events are identified using wave height thresholds. Daily and weekly beach profile measurements from the Hasaki Oceanographic Research Station are used to quantify erosion. The study examines the seasonal influences on Hasaki beach, the characteristics and temporal evolution of storms, and their associated erosional impacts. Moreover, we test two supervised machine learning (ML) algorithms, support vector regression (SVR), and deep neural network (DNN), in predicting shoreline change using 16 wave, storm, and morphological features. SVR showed reasonable accuracy on the training dataset but underperformed on testing, while DNN failed to produce reliable predictions on both. With SVR yielding an R2 of 0.18 and DNN 0.27 on the testing dataset, we conclude that, given the limited data and available features, such ML models may not generalise well. However, separate analyses using observed data reveal clear seasonal variations in wave storm dynamics and distinct behaviours of clustered events associated with beach erosion, highlighting important insights beyond the ML results.

Layla Poubel Tunala, Frederico Tapajós de Souza Tâmega, Ricardo Coutinho

Sediment is highly related to coral reef degradation worldwide, and sedimentation is considered a critical cause of stress for coral communities. The current study focused on the Arraial do Cabo Marine Extractive Reserve (ACMER), recognized as a coralline oasis in the southwest Atlantic, which is facing multiple environmental pressures. Among them, mass tourism stands out, which enhances sedimentation. To address the scientific question of how sediment characteristics and rates vary across different sites, local sedimentation was monitored for about one year through sedimentation rates, granulometric composition, and the percentage of calcium carbonate (%CaCO3) at five sampling sites, each exposed to varying levels of natural and anthropogenic activities. The results revealed distinct patterns linked to these activities and natural agents. For instance, Forno's Cove exhibited the highest percentage of fine sediment (about 70%) among all the other sampled points, suggesting the sedimentation to be strongly related to anthropogenic action. Although the overall sedimentation rates in Arraial do Cabo Bay were not high, the current findings highlight the sedimentation related to the increase in tourist activities and the need for continuous monitoring of ACMER. Such vigilance is crucial for ensuring the environmental health of coral environments and supporting the local human community's livelihoods.

Meysam Nouri, Rasoul Ilkhanipour, Amir Hossein Azimi

This paper presents the results of experimental investigation on the local erosion and mound formation induced by slurry turbulent circular wall jets in crossflow and with the presence of a secondary current. The trajectory of the slurry jets with different intensities on the bed formation was measured with an accurate laser scanner with a resolution of ±1 mm. Other data such as scour, and mound areas and volumes were measured to study the effects of sediment concentration and jet’s intensity on deformation of erodible bed at the vicinity and downstream of the crossflow. Experimental results indicated that the mass flux of sediment in slurry wall jets increased the width and spreading rate of sediment mound while increasing the intensity of the jet reduced the mound width and stretched it along the flow direction. The correlation between non-dimensional geometry parameters with the jet’s Reynolds number indicated a distinct behavior on the development and direction of mounds with a threshold Reynolds number of approximately 36,000. For turbulent slurry wall jets with Reynolds number smaller than the threshold value, most of the sediments settled at the vicinity of the nozzle and reduced the scour depth while for stronger jets, sediment dunes were formed in the curved region of the flume and scour depth was almost the same as the scour depth formed by the corresponding clear water turbulent wall jets. A linear correlation was found between the peak scour depth and jet’s Reynolds number, while peak scour depth, area, and volume decreased with increasing the initial sand concentration of slurry jets. Empirical formulas were proposed for prediction of bed deformation and jet’s trajectory, the accuracies of the proposed models were evaluated using statistical analysis, and the performance of the proposed models were compared with the existing models from the literature.

Catherine N. Janda, Jonathan A. Warrick, Daniel Buscombe et al.

Shoreline measurement techniques using satellite-derived imagery can provide decades of observations of shoreline change. Here we apply these techniques to the western south shore of Long Island, New York, which has three distinct beaches, Rockaway Peninsula, Long Beach, and Jones Beach Island, which are 18, 15, and 24 km in length, respectively. These beaches are recreation areas for millions of regional residents and include several groin fields, sediment dredging and nourishment operations, and a coastal wave climate that includes winter northeasterly storms and summer hurricanes. The shorelines along the western ends of these three beaches have been accreting at ~4 m/yr during the observation record (1984–2022) resulting from net westward longshore drift. The central 10–12 km of the beaches have lower shoreline change rates, and these rates are generally lowest within the groin fields (0.5–1.5 m/yr). Shoreline change observations also provide evidence for westward propagating accretion and erosion sediment waves that have durations of several years. Beach nourishment projects are shown to significantly influence rates of shoreline accretion, and this is commonly followed by significant shoreline retreat during the subsequent years.

Colin D. Woodroffe, Niki Evelpidou, Irene Delgado-Fernandez et al.

It is often inferred that rising sea levels will result in widespread coastal recession. Erosion appeared prevalent in a worldwide compilation of evidence derived from maps and aerial photographs undertaken in the 1980s by the Commission on the Coastal Environment. Eric Bird, chair of the commission, inferred that >70% of sandy coastlines had retreated, a generalisation that has been widely cited. We reconsider these findings in respect of subsequent advances in shoreline mapping, including greater precision possible using geographical information systems and more frequent remote sensing imagery with increased spatial, spectral and temporal resolution. Satellite-derived shorelines now enable broad global and regional generalisations about shoreline position. Beaches fluctuate over a range of timescales, meaning that trends in their position are highly dependent on techniques and temporal scales adopted for monitoring. Recent global- and regional-scale shoreline assessments indicate that many sandy shorelines have been stable, and that detectable retreat has occurred on fewer beaches than previously inferred. Accretion is apparent on some coasts, particularly where engineering interventions protect or have reclaimed land. There is considerable variability in the behaviour of monitored beaches, and it is not yet possible to decipher a response to the gradual centimetre-scale rise in sea level of recent decades. Instead, we re-emphasise the several other factors that were considered to contribute to recession by the Commission, many of which relate to a change in sediment budget. To provide insights into future coastline behaviour, a better understanding of the multiple drivers on individual beaches is needed to discriminate between erosional events and longer-term trends in shoreline position.

Rafael Schroeder, Lucas Gavazzoni, Carlos E. N. de Oliveira et al.

Recreational diving depends on healthy marine ecosystems, yet it can harm biodiversity through species displacement and habitat damage. Bombinhas, a biodiverse diving hotspot in southern Brazil, faces growing threats from human activity and climate change. This study assessed the ecological structure of Sepultura Beach (2018) for potential diving trails, comparing it with historical data from Porto Belo Island. Using visual censuses, transects, and photo-quadrats across six sampling campaigns, researchers documented 2419 organisms from five zoological groups, identifying 14 dominant species, including <i>Haemulon aurolineatum</i> and <i>Diplodus argenteus</i>. Cluster analysis revealed three ecological zones, with higher biodiversity at the site’s edges (Groups 1 and 3), but these areas also hosted endangered species like <i>Epinephelus marginatus</i>, complicating trail planning. A major concern was the widespread bleaching of the zoanthid <i>Palythoa caribaeorum</i>, a key ecosystem engineer, likely due to rising sea temperatures (+1.68 °C from 1961–2018) and declining chlorophyll-a levels post-2015. Comparisons with past data showed a 0.33 °C increase in species’ thermal preferences over 17 years, alongside lower trophic levels and greater ecological vulnerability, indicating tropicalization from the expanding Brazil Current. While Sepultura Beach’s biodiversity supports diving tourism, conservation efforts must address coral bleaching and endangered species protection. Long-term monitoring is crucial to track warming impacts, and adaptive management is needed for sustainable trail development. The study highlights the urgent need to balance ecotourism with climate resilience in subtropical marine ecosystems.

Roberto Verdecchia, Justus Bogner

From its first adoption in the late 80s, qualitative research has slowly but steadily made a name for itself in what was, and perhaps still is, the predominantly quantitative software engineering (SE) research landscape. As part of our regular column on empirical software engineering (ACM SIGSOFT SEN-ESE), we reflect on the state of qualitative SE research with a focus group of experts. Among other things, we discuss why qualitative SE research is important, how it evolved over time, common impediments faced while practicing it today, and what the future of qualitative SE research might look like. Joining the conversation are Rashina Hoda (Monash University, Australia), Carolyn Seaman (University of Maryland, United States), and Klaas Stol (University College Cork, Ireland). The content of this paper is a faithful account of our conversation from October 25, 2025, which we moderated and edited for our column.

Ziyue Liu, Meredith L. Carr, Norberto C. Nadal-Caraballo et al.

Bayesian networks (BN) have advantages in visualizing causal relationships and performing probabilistic inference analysis, making them ideal tools for coastal hazard analysis and characterizing the compound mechanisms of coastal hazards. Meanwhile, the Joint Probability Method (JPM) has served as the primary probabilistic assessment approach used to develop hazard curves for tropical cyclone (TC) induced coastal hazards in the past decades. To develop hazard curves that can capture the breadth of TC-induced coastal hazards, a large number of synthetic TCs need to be simulated, which is computationally expensive. Given that low exceedance probability (LEP) coastal hazards are likely to result in the most significant damage to coastal communities, it is practical to focus efforts on identifying and understanding TC scenarios that are dominant contributors to LEP coastal hazards. This study developed a BN-based framework incorporating existing JPM for multiple TC-induced coastal hazards deaggregation. Copula-based models capture dependence among TC atmospheric parameters and generate CPTs for corresponding BN nodes. Machine learning surrogates model the relationship between TC parameters and coastal hazards, providing conditional probability tables (CPTs) for hazard nodes. Case studies are applied to the Greater New Orleans region in Louisiana (USA). Deaggregation is a method for identifying dominant scenarios for a given hazard, which was first established in the field of probabilistic seismic hazard analysis. The objective of this study is to leverage BN to develop a deaggregation method of multiple LEP coastal hazards to better understand the dominant drivers of coastal hazards to refine storm parameter set selection to more comprehensively represent multiple forcings.

Xun Cai, Qubin Qin, Matthew Kirwan et al.

Saltwater intrusion is a critical challenge to coastal ecosystems, impacting freshwater resources, biogeochemical cycles, and habitat stability. While relevant studies often focus on the long-term trends of salinity, its episodic variability and resulting ecological disturbance remains underexplored. Here, we introduce the concept of "coastal salt waves" - periods of elevated salinity anomalies, akin to heat waves - to better characterize extreme salinity events and emphasize their significance. Using cases studies, we show that coastal salt waves exhibit significant spatial and temporal variability based on their duration, intensity, frequency, cumulation, and timing, with drivers and impacts that may differ from gradual saltwater intrusion. In years with similar average salinity, salt waves may still vary greatly in characteristics like intensity, resulting in varying environmental impacts. Furthermore, systems without rising average salinity may still face more frequent or intense salt waves. This framework supports monitoring and management strategies to mitigate coastal salinization risks.

Mohammed Latif Siddiq, Arvin Islam-Gomes, Natalie Sekerak et al.

Reproducibility is a cornerstone of scientific progress, yet its state in large language model (LLM)-based software engineering (SE) research remains poorly understood. This paper presents the first large-scale, empirical study of reproducibility practices in LLM-for-SE research. We systematically mined and analyzed 640 papers published between 2017 and 2025 across premier software engineering, machine learning, and natural language processing venues, extracting structured metadata from publications, repositories, and documentation. Guided by four research questions, we examine (i) the prevalence of reproducibility smells, (ii) how reproducibility has evolved over time, (iii) whether artifact evaluation badges reliably reflect reproducibility quality, and (iv) how publication venues influence transparency practices. Using a taxonomy of seven smell categories: Code and Execution, Data, Documentation, Environment and Tooling, Versioning, Model, and Access and Legal, we manually annotated all papers and associated artifacts. Our analysis reveals persistent gaps in artifact availability, environment specification, versioning rigor, and documentation clarity, despite modest improvements in recent years and increased adoption of artifact evaluation processes at top SE venues. Notably, we find that badges often signal artifact presence but do not consistently guarantee execution fidelity or long-term reproducibility. Motivated by these findings, we provide actionable recommendations to mitigate reproducibility smells and introduce a Reproducibility Maturity Model (RMM) to move beyond binary artifact certification toward multi-dimensional, progressive evaluation of reproducibility rigor.

Nicola Cantasano, Vincenzo Di Martino, Gaetano Pellicone

<i>Caulerpa cylindracea</i>, Indo-Pacific and thermophilic macroalgal species, have spread in Italian coastal waters, especially in the western Mediterranean Sea. Also, along the Calabria coastline, this Invasive Alien Species (IAS) was able to colonize most of the western and eastern seasides of the region. This research was conducted between 1999 and 2021 through a detailed cost-effective citizen science program. The novelty of this research was to determine the overall distribution of <i>Caulerpa cylindracea</i> along Calabria seawaters from the Tyrrhenian to the Ionian coasts. The results of the monitoring survey highlighted the presence of <i>Caulerpa cylindracea</i> in 45 collecting stations throughout the Calabrian coastline. This regional assessment showed the extensive adaptability of the species to different environmental conditions: from exposed to sheltered sites, in shaded and sunny coastal areas and also throughout pristine and polluted waters. The rapid and increasing spread of the species could affect the structure of Mediterranean biota or, otherwise, could lead in time to new ecological niches. As highlighted in the most recent literature, it is necessary to update monitoring and mapping plans for the protection of marine biodiversity through close coordination between scientists, citizens and policy makers, all engaged to ensure effective management of invasive processes.

Imane Meziane, Marc Robin, Paul Fattal et al.

This article presents a diachronic study of evolution along the coastline of Noirmoutier Island in France, a sandy shore particularly susceptible to erosion and submersion risks, which are exacerbated by climate change due to two-thirds of its territory being below sea level. The study is based on an analysis of aerial images covering a period of 72 years, divided into five distinct periods: 1950–1974, 1974–1992, 1992–2000, 2000–2010, and 2010–2022. The methodology used combines two complementary approaches: the Digital Shoreline Analysis System (DSAS) for taking linear measurements of the erosion and accretion that have taken place along various shorelines, and the surface method to evaluate the amount of surface lost or gained between different shorelines while calculating the uncertainties associated with the obtained results. The overall trend observed between 1950 and 2022 indicates that the Noirmoutier coastline studied has gained surface area (81 hectares) at an average rate of +0.57 ± 0.06 m per year. The article then presents an application of the method developed by Durand and Heurtefeux in 2006 to estimate the future position of the shoreline. A map of the local area is also provided, identifying the areas susceptible to coastal erosion by 2052 and by 2122, in accordance with the provisions of the Climate and Resilience Law adopted in France on 22 August 2021. The results reveal that there are many sources of uncertainty in predicting the future evolution of the shoreline using this methodology. Therefore, it is crucial to consider these uncertainties when planning future coastal management actions and adopting appropriate adaptation methods to counteract unforeseen developments.

Joshua Kiesel, Arne Knies, Athanasios T. Vafeidis

The capacity of river mouths to reduce storm surge water levels upstream, referred to as along-estuary attenuation, has been assessed by several studies. The coastal protection function of semi-enclosed water bodies such as lagoons and channels with narrow inlets remains less explored and generalization is hampered by differences in morphology and hydrodynamic forcing. Here we use a hydrodynamic model to investigate surge attenuation along a microtidal channel with a narrow inlet at the Baltic Sea coast of Germany called The Schlei. We quantify the importance of wind and the contribution of the barrier spit system, which is constricting the inlet, to the reduction of water levels at the landward end of the channel. In addition, we explore the role of dikes in the region for the reduction of peak water levels and coastal flooding. We find effective along-channel attenuation inside The Schlei in its current state, which is mostly a result of the channel’s narrows. However, reduction rates decrease under simplified sea-level rise scenarios. Furthermore, along-channel attenuation is highly variable and can change to substantial amplification depending on hydrometeorological forcing. The barrier spit contributes to along-channel attenuation whereas the effect of existing dikes (or their removal) for along-channel attenuation is negligible.

Qikun Xing, Samuel J. Kim, Charles Yarish

“Blue carbon” refers to the carbon sequestered by the world’s oceanic and coastal ecosystems, particularly through coastal vegetation such as mangroves, salt marshes, seagrasses, and marine macroalgae. These ecosystems play a crucial role in the global carbon cycle by serving as significant carbon sinks, absorbing carbon dioxide from the atmosphere and storing it in biomass and sediments over long periods. This study explores the use of environmental DNA (eDNA) to detect marine macrophytes and microalgae assemblages contributing to blue carbon in sediments across various coastal ecosystems. The research addresses the challenges of traditional monitoring methods by utilizing high-throughput sequencing of the 18S-V9 region amplified using eDNA from sediment samples collected at eight locations in the United States and South Korea. The results reveal a diverse array of taxa, underscoring the variability in community composition across different conditions. Notably, sites with seagrass beds and <i>Ulva</i> blooms showed distinct patterns in microalgal community structure. This study underscores the potential of eDNA analysis in providing comprehensive insights into the biodiversity of marine macrophyte ecosystems, thus informing conservation efforts and enhancing the understanding of marine ecological dynamics.

Ebube Alor, Ahmad Abdellatif, SayedHassan Khatoonabadi et al.

Software engineering (SE) chatbots are increasingly gaining attention for their role in enhancing development processes. At the core of chatbots are Natural Language Understanding platforms (NLUs), which enable them to comprehend user queries but require labeled data for training. However, acquiring such labeled data for SE chatbots is challenging due to the scarcity of high-quality datasets, as training requires specialized vocabulary and phrases not found in typical language datasets. Consequently, developers often resort to manually annotating user queries -- a time-consuming and resource-intensive process. Previous approaches require human intervention to generate rules, called labeling functions (LFs), that categorize queries based on specific patterns. To address this issue, we propose an approach to automatically generate LFs by extracting patterns from labeled user queries. We evaluate our approach on four SE datasets and measure performance improvement from training NLUs on queries labeled by the generated LFs. The generated LFs effectively label data with AUC scores up to 85.3% and NLU performance improvements up to 27.2%. Furthermore, our results show that the number of LFs affects labeling performance. We believe that our approach can save time and resources in labeling users' queries, allowing practitioners to focus on core chatbot functionalities rather than manually labeling queries.