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8th international conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Ni, Yongkang Deng, Yuandan Mao, Yanling Chen, Weiqin School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Sichuan Provincial Key Laboratory of Intelligent Terminal jointly built by Hall and City Sichuan Yibin China University of Electronic Science and Technology of China Yibin Park Sichuan Yibin China

ISBN: (纸本)9798400710094

For the conversion from SysML (System Modeling Language) static model to dynamic model, the mapping between the two models is not direct or automated. A method to implement SysML static model conversion based on QVT-O (Query/Views/Transformation - Operational) is proposed. Extract necessary information from the BDD (Block Definition Diagram) of the SysML static model, and generate a sequence diagram corresponding to the dynamic model based on predefined rules and mapping between models. The effectiveness of this method is verified through a simple system. This automated conversion not only improves modeling efficiency, but also enhances the consistency and accuracy of the model, which has important practical value for system engineers in system design and analysis. © 2024 Copyright held by the owner/author(s).

关键词： Mapping

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Automated Test Generation: Taxonomy and Tool Applications 11th

Automated Test Generation: Taxonomy and Tool Applications

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11th IFIP WG 2.2 international conference on Fundamentals of software engineering, FSEN 2025

作者： Enoiu, Eduard Mehmood Minhas, Nasir Felderer, Michael Afzal, Wasif School of Innovation Design and Engineering Mälardalen University Västerås Sweden Oberpfaffenhofen Germany Department of Mathematics and Computer Science University of Cologne Cologne Germany

ISBN: (纸本)9783031870538

Automated test generation is an area that has seen a lot of research and development, resulting in many test automation methods and tools for test design. However, practitioners often face challenges in adopting these tools. This is not only due to the immaturity of some tools but also because of varying perspectives, confusing terminology, and, most importantly, the lack of a clear framework to guide the selection of the most suitable approach for their needs. We propose a taxonomy that characterizes the methods for automated test generation. The taxonomy was constructed using a process that involved analyzing secondary studies on automated test generation and existing taxonomies in the scientific literature. Direct observations and iterative refinements were included, followed by validation through conceptual evaluation and practitioner feedback. The resulting dimensions characterize automated test generation and its use in software testing. The taxonomy is organized into several dimensions: software artifact (i.e., type, notation, interfaces), test generation (i.e., objectives, methods, and monitoring), test execution, and test oracle. We demonstrate the taxonomy’s use by applying it to several automated test-generation tools. This paper provides the necessary concepts and a generic process for categorizing and assessing automated test generation approaches. © IFIP international Federation for Information Processing 2025.

关键词： software testing

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Adopting Continuous Deployment in a Public Administration Project: An Industrial Case Study 25th

Adopting Continuous Deployment in a Public Administration Pr...

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25th international conference on Product Focused software Process Improvement

作者： Linjama, Aapo Granlund, Thomas Solita Oy Helsinki Finland Tampere Univ Tampere Finland

ISBN: (纸本)9783031783913;9783031783920

Continuous deployment is a significant trend in software development, yet its adoption and potential benefits within the public sector remain under-researched. This paper examines a case study of continuous deployment implementation in a public sector project undertaken by Solita, a software development company, for a client utilizing agile methodologies. The study provides a comprehensive overview of the motivations, benefits, and challenges encountered during continuous deployment adoption. This study contributes to the growing body of knowledge on continuous deployment by providing valuable insights into its application within the public sector context, offering practical recommendations for overcoming challenges and achieving successful implementation.

关键词： Continuous deployment Public administration Agile software development

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A Switch-Transformer Predictive Process Monitoring Model for Next Activity Prediction in Business Process Management 24

A Switch-Transformer Predictive Process Monitoring Model for...

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8th international conference on Advances in Artificial Intelligence, ICAAI 2024

作者： Nguyen, Thanh-Hai Kim, Kyoung-Sook Kim, Kwanghoon Pio Thai Nguyen Thai Nguyen Viet Nam Contents Convergence Software Research Institute Kyonggi University Gyeonggi Suwon Korea Republic of AI Computer Science and Engineering Kyonggi University Gyeonggi Suwon Korea Republic of

ISBN: (纸本)9798400718014

This paper proposes a deep learning model for predicting the next activities in a temporal sequence of activity-events associated with a single process instance. The proposed model is based on a mixture of experts (MoE) mechanism supported by the Switch-Transformer neural network architecture. The deep learning model is trained from scratch on process enactment event log histories. The ultimate goal is to predict the next activities, generate their probabilities of occurrence, and visualize all the predicted next activities in a graphical form of temporal order representing each running case of the corresponding process model. To assess the operational effectiveness of the proposed model, we successfully conducted performance evaluations through a series of experiments on synthetic and real-life process event log datasets, which have been typically and usefully applied in other approaches in previous research works. © 2024 Copyright held by the owner/author(s).

关键词： Prediction models

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Design and Development of IoT Smart Driving Protocol for Unmanned Ground Vehicles 6

Design and Development of IoT Smart Driving Protocol for Unm...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Seelam, Santhosh Kumar Nagakishore Bhavanam, S. Midasala, Vasujadevi Reddy, Edara Sreenivasa Department of Computer Science and Engineering University College of Engineering and Technology Acharya Nagarjuna University Andhra Pradesh Guntur India Jabalpur Madhya Pradesh Barela India Department of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India

ISBN: (纸本)9798331522667

UGVs have enormous potential in industries such as defense, agriculture, and autonomous transportation. Efficiency and effectiveness can be achieved by UGVs through the sophistication of their control systems, mainly with regard to navigation and decision-making. In this study, a new IoT-based smart direction control system is proposed for UGVs. The system presented herein integrates state-of-the-art sensor fusion techniques against the backdrop of a robust and adaptive communication framework for enhanced navigation accuracy and reduced latency, with the overall goal of improving system efficiency. Equipped with GPS, IMU, and LiDAR sensors, our system provides accurate environmental perception and real-time adaptability to various terrains. The heart of this device is a high-performance, military-grade microcontroller, which ensures the reliability and handling of numerous data streams simultaneously with minimal latency. On the software side, modular design makes use of edge computing and machine learning algorithms to facilitate adaptive control and real-time decision-making. The performance was verified by rigorous testing in simulated environments and real-world field trials. The results show an improvement in the navigation accuracy and system responsiveness compared to previous solutions. A comparative deep analysis shows the superiority of our approach to hardware design, software integration, and prototype testing. © 2025 IEEE.

关键词： Adaptive control systems

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Advances in Automatic software Testing: Test-Comp 2025 28th

Advances in Automatic Software Testing: Test-Comp 2025

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28th international conference on Fundamental Approaches to software engineering, FASE 2025, which was held as part of the international Joint conferences on Theory and Practice of software, ETAPS 2025

作者： Beyer, Dirk LMU Munich Munich Germany

ISBN: (纸本)9783031908996

The 7th edition of the Competition on software Testing (Test-Comp 2025) provides an overview and comparative evaluation of automatic test-suite generators for C programs. The experimental evaluation was performed on a benchmark set of 11 226 test-generation tasks for C programs. Each test-generation task consisted of a program and a test specification. The test specifications included error coverage (generate a test suite that exhibits a bug) and branch coverage (generate a test suite that executes as many program branches as possible). Test-Comp 2025 evaluated 20 software systems for test generation that are all freely available. This included 13 test-suite generators that participated with active support from teams led by 12 different representatives from 8 countries (actively maintained software systems, participation in competition jury). Test-Comp 2025 had 1 new participant () and 2 re-entries (ESBMC-incr, ESBMC-kind). The evaluation included also 7 test-generation tools from previous years. © The Author(s) 2025.

关键词： computer software selection and evaluation

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A distributed machine learning dynamic remote proof scheme that resists collusion attacks 4

A distributed machine learning dynamic remote proof scheme t...

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4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Wang, Ke Wu, Qiuxin Qin, Yu School of Applied Science Beijing Information Science and Technology University Beijing100192 China Trusted Computing and Information Assurance Laboratory Institute of Software Chinese Academy of Science Beijing100190 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Based on the security of distributed machine learning data and model based on remote proof, a cross-domain dynamic remote proof scheme based on ring signature improves the efficiency of computer cluster proof, the application of dynamic signature, realizes the real-time measurement of the confidence of computer cluster, and strengthens the real-time protection of data and model. computers with different security domain may adopt different remote proof mechanism, and convert the proof information of different proof methods into unified proof information, thus realizes the cross-domain dynamic remote proof between computer clusters. Noise is added when the cloud server distributes data to a distributed computer cluster. Due to the particularity of distributed architecture and the unsolution of indefinite equations, the enemy cannot conspire with one or more computers to steal data or the model parameters trained by endpoints. Finally, the safety of this method is verified through safety analysis and experimental analysis, and the computational overhead required in the proof process is reduced compared with other methods. © 2025 SPIE.

关键词： Authentication

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Vision-Text Bidirectional Collaborative Image Captioning Algorithm

IAENG International Journal of Computer Science

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IAENG international Journal of computer science 2025年第2期52卷 515-523页

作者： Li, Mei-Qi Zhou, Zi-Wei School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China

Image captioning is an interdisciplinary research hotspot at the intersection of computer vision and natural language processing, representing a multimodal task that integrates core technologies from both fields. This task requires the use of computer vision techniques to analyze and extract key visual features from images, followed by the application of natural language processing techniques to generate descriptive text that is syntactically and semantically aligned with human cognition. This process poses a significant challenge for computers. Existing models mostly ignore the relative positional information of visual objects and struggle to efficiently capture the complex relationships between visual and textual data. To address these challenges, we propose a vision-to-text bidirectional collaborative image captioning method. This approach extracts both visual features and positional information of objects, allowing the model to better understand the spatial relationships between objects. The CEW word embedding approach encodes textual information more profoundly, enhancing semantic expression and contextual understanding. In the decoding phase, a bidirectional cross-attention mechanism strengthens the interaction between vision and text, leading to improved accuracy in image understanding. The model is trained and tested on the MSCOCO 2014 dataset and compared with several popular models. Experimental results demonstrate that the proposed method achieves significant improvements on the CIDEr and BLEU-1 evaluation metrics with an increase of 1.5 and 1.1, respectively. In addition, we conduct ablation experiments, quantitative analysis, and qualitative analysis to comprehensively validate the effectiveness and stability of the proposed algorithm. © (2025), (international Association of Engineers). All rights reserved.

关键词： Embeddings

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Reliability of IoT Systems for Fire Detection 16

Reliability of IoT Systems for Fire Detection

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16th international conference on ENTERprise Information Systems, CENTERIS 2024 - 12th international conference on Project MANagement, ProjMAN 2024 - 14th international conference on Health and Social Care Information Systems and Technologies, HCist 2024

作者： Singh, Khushwant Yadav, Mohit Barak, Dheerdhwaj Moreira, Fernando Department of Computer Science & Engineering U.I.E.T Maharshi Dayanand University Rohtak124001 India Department of Mathematics University Institute of Sciences Chandigarh University Punjab Mohali140413 India Department of Computer Science & Engineering Vaish College of Engineering Rohtak124001 India REMIT IJP Universidade Portucalense Porto & IEETA Universidade de Aveiro Aveiro Portugal

In this paper, a smart IoT system including the software and hardware aspects of its design, as well as its operation in the context of a city or a building, along with its advantages, disadvantages, and potential applications, all with a focus on fire safety have been analyzed. Based on the results of the aforementioned research, it is clear that an IoT-based fire system may be tailored to the specific requirements of each individual situation. The major focus of the study is on the planning and evaluation of a WSN that can detect house fires in their earliest stages. The authors address the crucial issue of giving rapid-fire alerts by including a broad range of sensors in the wireless sensor network. In order to provide precise, real-Time fire detection, the wireless sensor network (WSN) is constructed from tiny, low-power sensor devices that have sensors able to sense their surroundings. Using the Global System for Mobile Communications (GSM) to reduce the number of false alarms is one strategy the authors propose for coping with sensor malfunctions. The reliability of IoT (Internet of Things) systems for fire detection has been a topic of interest and continuous improvement. IoT-based fire detection systems have the potential to offer numerous benefits, such as real-Time monitoring, remote management, and data-driven insights. However, their reliability depends on several factors, including technology, implementation, and maintenance. This research aids in the enhancement of residential community safety by improving the early detection and prevention of house fires. © 2025 The Author(s).

关键词： Fire detectors

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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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