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LLM-Based Business Process Documentation Generation 22nd

LLM-Based Business Process Documentation Generation

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22nd international conference on Service Oriented computing

作者： Zhu, Rui Hu, Quanzhou Wen, Lijie Lin, Leilei Xiao, Honghao Wang, Chaogang Yunnan Univ Kunming Sch Software Kunming Yunnan Peoples R China Key Lab Software Engn Kunming 650091 Yunnan Peoples R China Tsinghua Univ Beijing Sch Software Beijing Peoples R China Capital Normal Univ Beijing Sch Management Beijing Peoples R China

ISBN: (纸本)9789819608041;9789819608058

Business processes underpin enterprise execution, coordination, and management. However, differing levels of familiarity with modeling languages among users can create an understanding gap, potentially disrupting the process flow. Business process documentation bridges this gap. Current methods, such as manual writing and rule-based generation, face inefficiency, errors, and limitations. We innovate by harnessing large language models for documentation generation. Our approach involves defining a Refined Process Structure Tree (RPST) meta-model and mapping rules, then constructing fine-grained RPSTs and crafting sentences using a hierarchical construction method. Finally, global optimization enhances the documentation. Tested on 100 diverse process models, our method outperforms benchmarks in robustness, and it achieves 6% and 1% higher semantic similarity scores by n-gram and semantics metrics.

关键词： Business Process Documentation Large Language Model Hierarchical Construction Prompt Learning

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Astronomical Image Processing by the Lemur software 24

Astronomical Image Processing by the Lemur Software

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6th Asia conference on Machine Learning and computing, ACMLC 2024

作者： Khlamov, Sergii Savanevych, Vadym Briukhovetskyi, Oleksandr Vlasenko, Vladimir Dikov, Yevhen Dmytrenko, Artem Department of Media Systems and Technologies Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of systems engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Western Center of Radio Engineering Surveillance National Space Facilities Control and Test Center Kyiv Ukraine Space Research and Communication Center National Space Facilities Control and Test Center Kyiv Ukraine Department of Software Engineering GlobalLogic Incorporation Kharkiv Ukraine Institute of Astronomy V. N. Karazin Kharkiv National University Kharkiv Ukraine

ISBN: (纸本)9798400710018

The astronomical images are made by cameras with the charge-coupled device (CCD). They can be received from the different sources, like servers, clusters, predefined series, archives or "live" (online) data streams. The astronomical images processing is focused on but not limited to the following tasks: data mining, knowledge discovery, big astronomical data processing, filtering, background alignment, brightness equalization, segmentation, classification, image recognition, object's image detection, object's astrometry and photometry, moving object detection, parameters determination of the object's image and apparent motion, reference objects selection and others. The modern Lemur software of the Collection Light Technology (CoLiTec) project (https://***) was developed using the described above technologies and approaches. The Lemur software is designed to perform a sequence of the following main steps: pre-processing (astronomical information collection -> worst data rejection -> useful data extraction -> data mining -> classification -> background alignment -> brightness equalization), image processing (segmentation -> typical form analysis -> recognition patterns applying -> detection of the object's image -> astrometry -> photometry -> objects identification -> tracks detection), knowledge discovery (Solar System objects or artificial satellites to be discovered, tracks parameters for the investigation, light curves of the variable stars, scientific reports in the international formats). The paper describes the modern features for the astronomical image processing implemented in the Lemur software. It has assisted in making over 1700 discoveries of asteroids, including 5 NEOs, 21 Trojan asteroids of Jupiter, 1 Centaur. In total it has been used in about 800 000 observations, during which five comets were discovered. All such observations and discoveries have official observational circulares from the Minor Planet Center (MPC) of the international Ast

关键词： Asteroids

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Autonomous Driving System Testing: Traffic Density Does Matter 36th

Autonomous Driving System Testing: Traffic Density Does Matt...

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36th international conference on Testing software and systems

作者： Lou, Guannan Shin, Donghwan Walkinshaw, Neil Hierons, Robert M. Univ Sheffield Sheffield S10 2TN S Yorkshire England

ISBN: (纸本)9783031808883;9783031808890

In recent years, the rapid development of deep neural networks and their application technologies has propelled autonomous driving systems (ADS) towards commercialisation. However, due to the high safety requirements of ADSs, ensuring their safety and reliability remains a critical challenge in software engineering. Existing testing methods focus on simple driving scenarios with few traffic participants, neglecting the impact of high traffic density on ADS driving performance. This paper presents an empirical study exploring how traffic density affects ADS behaviour. We developed a testing framework using two open-source ADSs to generate scenarios with varying traffic densities in a high-fidelity simulator. Our results indicate that changes in traffic density significantly affect ADS performance. Different traffic densities reveal various types of safety violations and help identify potential design flaws in ADSs. This study highlights the importance of considering traffic density in ADS testing and contributes to a better understanding of ADS performance under different traffic conditions.

关键词： software engineering Test Generation Machine Learning Autonomous Driving System

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Fostering Diversity in software engineering Education: A Challenge-Based Approach to Integrate Non-STEM Students 17

Fostering Diversity in Software Engineering Education: A Cha...

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17th international conference on Computer Supported Education, CSEDU 2025

作者： Sales, Afonso Nascimento, Nicolas Chanin, Rafael de Campos, Aline School of Technology RS Porto Alegre Brazil

ISBN: (纸本)9789897587467

This paper proposes an innovative approach to addressing the lack of diversity in software engineering education by integrating non-STEM students into mobile app development programs. Leveraging the Challenge-Based Learning (CBL) methodology, this idea paper explores how targeted instructional strategies and preparatory leveling sessions can empower students from diverse academic backgrounds to succeed in highly technical environments. By breaking traditional barriers to programming education, this approach fosters an inclusive learning environment that enhances technical skills and encourages cross-disciplinary collaboration and innovation. We present the conceptual framework and practical implications of this inclusive model, offering insights into how this approach can be adopted across different educational settings to promote diversity and innovation in software engineering. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： engineering education

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Adaptive Multi-scale Fusion Transformer for Image Super-Resolution 8th

Adaptive Multi-scale Fusion Transformer for Image Super-Reso...

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8th international conference on Information science, Communication and computing

作者： Sun, Yusheng Chen, Weihai Zang, Xiaogang Wang, Changjiang Zhengzhou Univ Light Ind Sch Software Zhengzhou Peoples R China

ISBN: (纸本)9789819617838;9789819617814;9789819617807

The Transformer achieves remarkable success in image super-resolution (SR). However, it has limitations in handling complex local details, whereas Convolutional Neural Networks (CNNs) are more advantageous in fine feature extraction. Additionally, we find that the Feedforward Network (FFN) in the Transformer architecture does not effectively integrate spatial and channel information, containing redundant information that hinders feature representation capability. Thus, we propose the Adaptive Multi-scale Fusion Transformer (AMFT), which combines the global advantages of the Transformer with the local fine feature extraction capabilities of CNNs. Through feature shifting, multi-scale feature extraction, and hierarchical feature fusion, the AMFT significantly enhances image detail representation and visual quality. In detail, we incorporate the Multi-Scale Shifting Convolution Module (MSSCM) into the Transformer. MSSCM first shifts the feature positions and then extracts and fuses features at different scales, preserving more details, and through a hybrid attention mechanism achieves global transmission of information. Additionally, we replace FFN with the Spatial Channel Fusion Module (SCFM) to achieve full information integration and reduce computational complexity. Extensive experiments demonstrate the superior performance of AMFT compared to existing methods.

关键词： Transformer Super-Resolution Shifting Convolution

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Risk Assessment in Agile software Development 11th

Risk Assessment in Agile Software Development

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11th international Symposium on Applied computing for software and Smart systems, ACSS 2024

作者： Ghosh, Oindrilla Chaki, Rituparna Chaki, Nabendu Cortesi, Agostino Department of Computer Science S. A. Jaipuria College Kolkata India A. K. Choudhury School of Information Technology Kolkata India Department of Computer Science and Engineering University of Calcutta Calcutta India DAIS Ca’Foscari University Venice Italy

ISBN: (纸本)9789819797615

Risk assessment in software engineering has seen many approaches. Despite the amount of scientific literature on risk management, the failure rate of software projects after the first installation remains considerable. The reason is probably that the dynamically changing software feature has not been imbibed in the framework, which mostly deals with risk management in retrospect. This article attempts to suggest a new approach which will take these gaps into consideration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Agile methodologies Risk management software development

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31st international Working conference on Requirements engineering: Foundation for software Quality, REFSQ 2025

31st International Working Conference on Requirements Engine...

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31st international Working conference on Requirements engineering: Foundation for software Quality, REFSQ 2025

ISBN: (纸本)9783031885303

The proceedings contain 29 papers. The special focus in this conference is on Requirements engineering: Foundation for software Quality. The topics include: Towards Ethics-Driven Requirements engineering: Integrating Critical systems Heuristics and Ethical Guidelines for Autonomous Vehicles;refining and Validating Change Requests from a Crowd to Derive Requirements;do Users’ Explainability Needs in software Change with Mood?;exploring and Characterizing Ad-Hoc Requirements - A Case Study at a Large-Scale systems Provider;feReRe: Feedback Requirements Relation Using Large Language Models;how Does Users’ App Knowledge Influence the Preferred Level of Detail and Format of software Explanations?;How Effectively Do LLMs Extract Feature-Sentiment Pairs from App Reviews?;an Interactive Tool for Goal Model Construction Using a Knowledge Graph;Generating Domain Models with LLMs Using Instruction Tuning: A Research Preview;A Systematic Literature Review of KAOS Extensions;LACE-HC: A Lightweight Attention-Based Classifier for Efficient Hierarchical Classification of software Requirements;requirements Representations in Machine Learning-Based Automotive Perception systems Development for Multi-party Collaboration;automatic Prompt engineering: The Case of Requirements Classification;exploring Generative Pretrained Transformers to Support Sustainability Effect Identification - A Research Preview;prompt Me: Intelligent software Agent for Requirements engineering - A Vision Paper;detecting Redundancies Between User Stories with Graphs and Large Language Models;Leveraging Requirements Elicitation through software Requirement Patterns and LLMs;ReqRAG: Enhancing software Release Management through Retrieval-Augmented LLMs: An Industrial Study;the Potential of Citizen Platforms for Requirements engineering of Large Socio-Technical software systems;end-User Requirements Modelling: An Experience Report from Digital Agriculture;requirements Elicitation Workshops Using the Six Thinking Hat

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Towards Generating Measurable Artifact Models from Standards in Regulated Domains 25th

Towards Generating Measurable Artifact Models from Standards...

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25th international conference on Product Focused software Process Improvement

作者： Buelbuel, Mustafa Straub, Philipp Muench, Juergen Kuhrmann, Marco Reutlingen Univ Herman Hollerith Ctr Boblingen Germany

ISBN: (纸本)9783031783852;9783031783869

software and systems development projects in regulated domains need to provide evidence on their compliance to standards. Such standards often come as comprehensive documentation, i.e., documents, which need to be tailored to and interpreted for a particular project. Utilizing such documentations, it is desirable for companies working in regulated domains to provide tool support with regard to measurement systems that, eventually, help determine the product's quality and to support the compliance analysis. In this paper, we present an AI-supported approach to use a standard's documentation for generating artifact models. Such models are generated in a machine-readable format and, therefore, help companies create measurable items to be included in their metrication and measurement systems. Using selected ECSS standards from the European Space Agency as cases, we present our approach, the prompt engineering for the extraction of artifacts, and we illustrate the opportunities to generate comprehensive artifact models. Our findings show that, given sufficient information is available, the generation of artifact models is possible to a large degree with an average completeness of 99.64% and an average precision of 67.52% thus laying the foundation for building more efficient measurement systems.

关键词： Artifact Modeling Generative AI software engineering Quality Standards

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Empowering Precision Agriculture: A Comprehensive Real-Time Monitoring and Decision Support System for Farmers 3

Empowering Precision Agriculture: A Comprehensive Real-Time ...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Duraimurugan, N. Akalya, G. Aravind, S. Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331509675

A smart agricultural informatics platform integrated with Internet of Things (IoT) aims to revolutionize farming practices through a decentralized communication framework, the primary goal is to establish a knowledge-driven agricultural network in which farmers can discuss precision agronomy strategies, percentage know-how, and collaborate in real time to address challenges. The device carries a meteorological analytics module, powered by way of a RESTful Weather API, handing over a one-week climatic outlook to resource in dynamic choice-making. Advanced sensing technologies, including capacitive soil moisture sensors, electrochemical pH sensors, thermistors, and the DHT11 virtual sensor array, allow continuous tracking of soil physicochemical parameters and microclimatic situations for actionable insights. These features are wrapped in a mobility platform cell software program designed using the Flutter SDK, providing farmers with a modular UI/UX architecture that provides access to real-time farm diagnostics of their machines. Visualization of all facts using sensors. and predictive analytics for resources optimization Benefits of distributed computing and analytical aspects. When taken together this innovative platform helps farmers optimize spatial and temporal crop planning. Increase the sustainability of agricultural ecosystems and promote resilient, fact-driven agriculture. © 2025 IEEE.

关键词： Smart agriculture

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Deep learning-based cognitive digital twin system for wrist pulse diagnostic and classification 2nd

Deep learning-based cognitive digital twin system for wrist ...

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2nd international conference on Next-Generation computing and Information systems, ICNGCIS 2023

作者： Chaudhary, Jitendra Kumar Parimalam, T. Alghayadh, Faisal Yousef Keshta, Ismail Soni, Mukesh Degadwala, Sheshang School of Computing Graphic Era Hill University Bhimtal Campus Uttrakhand India Department of Computer Science Nandha Arts and Science College Tamilnadu Erode India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9781032738659

In analyzing and recognizing wrist pulse signals, it isn’t easy to mine the nonlinear information of wrist pulse signals using analysis methods such as time and frequency. Traditional machine learning methods require the manual definition of features and cannot perform self-learning of features. A cognitive digital twin technique for pulse analysis and recognition based on threshold-less recursive graph and CNN is proposed. The wrist pulse signal is converted into a threshold-free recursive graph based on the nonlinear dynamics’ theory. The VGG-16 CNN automatically extracts the nonlinear features of the recursive graph, and a pulse condition classification model is established. Experimental finding several that the classification of the proposed method accuracy can reach 98.14%, as compared with the existing pulse classification methods. This study offers a novel concept and strategy for classifying pulse signals, and it has application to the objectification of pulse diagnosis. © 2025 The Author(s).

关键词： Graphic methods

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