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检索条件"任意字段=19th International Conference on Software Engineering and Knowledge Engineering"

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OAM Beam Tilt Angle Detection Based on Uniform Circular Antenna Array 19

OAM Beam Tilt Angle Detection Based on Uniform Circular Ante...

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19th international conference on Natural Computation, Fuzzy Systems and knowledge Discovery, ICNC-FSKD 2023

作者： Zhang, Gaoji Cheng, Yifei Lu, Yi Xu, Lilan Xi'an University of Posts and Telecommunications School of Communication and Information Engineering Xi'an China

ISBN: (纸本)9798350304398

In the field of wireless communication, the reception and detection of vortex electromagnetic wave is undoubtedly the key to the use of orbital angular momentum (OAM) for communication. However, the misalignment between transceivers seriously affects the accuracy of receiver mode detection. We model the misalignment and generate phase distribution data using a uniform circular antenna array (UCAA) as the transceiver antenna. A lightweight neural network MobileNetV2 is used to build a training model to study the mapping between the OAM phase information and the inclination angle, and the inclination angle between the planes where the transceiver antenna is located is detected. the accuracy of the inclination detection model is good, reaching 0.91. © 2023 IEEE.

关键词： Electromagnetic waves

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Multivocal Literature Review on DevOps critical success factors 24

Multivocal Literature Review on DevOps critical success fact...

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28th international conference on Evaluation and Assessment in software engineering (EASE)

作者： Azad, Nasreen Hyrynsalmi, Sami LUT Univ Lahti Finland

ISBN: (纸本)9798400717017

DevOps is a methodology that seeks to unify development and operations teams in organizations, aiming to facilitate faster software delivery and promote collaboration to build a positive company culture. Our research aims to investigate the current state-of-the-art of DevOps, align academic research with industry practices, and identify critical success factors. We conducted a comprehensive literature review using a variety of databases and search engines, which revealed that several factors are essential to the success of DevOps, including DevOps culture, automation processes, continuous integration, and deployment, monitoring, and feedback, standardization with tools, team leadership, and DecSecOps for security issues. While DevOps has gained significant attention, it remains essential to understand practitioners' perspectives. Our research has the potential to strengthen the concepts and ideas of critical success factors, broaden DevOps practices and perspectives for professionals, and enhance academic knowledge in this area.

关键词： Critical Success Factors DevOps Multivocal Literature Review DevOps practices software Development

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Towards Synthetic Trace Generation of Modeling Operations using In-Context Learning Approach 24

Towards Synthetic Trace Generation of Modeling Operations us...

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39th ACM/IEEE international conference on Automated software engineering (ASE)

作者： Muttillo, Vittoriano Di Sipio, Claudio Rubei, Riccardo Berardinelli, Luca Dehghani, MohammadHadi Univ Teramo Teramo Italy Univ Aquila Laquila Italy Johannes Kepler Univ Linz Linz Austria

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Producing accurate software models is crucial in model-driven software engineering (MDE). However, modeling complex systems is an error-prone task that requires deep application domain knowledge. In the past decade, several automated techniques have been proposed to support academic and industrial practitioners by providing relevant modeling operations. Nevertheless, those techniques require a huge amount of training data that cannot be available due to several factors, e.g., privacy issues. the advent of large language models (LLMs) can support the generation of synthetic data although state-of-the-art approaches are not yet supporting the generation of modeling operations. To fill the gap, we propose a conceptual framework that combines modeling event logs, intelligent modeling assistants, and the generation of modeling operations using LLMs. In particular, the architecture comprises modeling components that help the designer specify the system, record its operation within a graphical modeling environment, and automatically recommend relevant operations. In addition, we generate a completely new dataset of modeling events by telling on the most prominent LLMs currently available. As a proof of concept, we instantiate the proposed framework using a set of existing modeling tools employed in industrial use cases within different European projects. To assess the proposed methodology, we first evaluate the capability of the examined LLMs to generate realistic modeling operations by relying on well-founded distance metrics. then, we evaluate the recommended operations by considering real-world industrial modeling artifacts. Our findings demonstrate that LLMs can generate modeling events even though the overall accuracy is higher when considering human-based operations. In this respect, we see generative AI tools as an alternative when the modeling operations are not available to train traditional IMAs specifically conceived to support industrial practitioners.

关键词： Data privacy Accuracy Large language models Training data Data models software Regulation Context modeling software engineering Synthetic data

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Ansible Lightspeed: A Code Generation Service for IT Automation 24

Ansible Lightspeed: A Code Generation Service for IT Automat...

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39th ACM/IEEE international conference on Automated software engineering (ASE)

作者： Sahoo, Priyam Pujar, Saurabh Nalawade, Ganesh Gebhardt, Richard Mandel, Louis Buratti, Luca Red Hat Raleigh NC USA IBM Res Yorktown Hts NY 10598 USA

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

the availability of Large Language Models (LLMs) which can generate code, has made it possible to create tools that improve developer productivity. Integrated development environments or IDEs which developers use to write software are often used as an interface to interact with LLMs. Although many such tools have been released, almost all of them focus on general-purpose programming languages. Domain-specific languages, such as those crucial for Information Technology (IT) automation, have not received much attention. Ansible is one such YAML-based IT automation-specific language. Ansible Lightspeed is an LLM-based service designed explicitly to generate Ansible YAML, given natural language prompt. In this paper, we present the design and implementation of the Ansible Lightspeed service. We then evaluate its utility to developers using diverse indicators, including extended utilization, analysis of user edited suggestions, as well as user sentiments analysis. the evaluation is based on data collected for 10,696 real users including 3,910 returning users. the code for Ansible Lightspeed service and the analysis framework is made available for others to use. To our knowledge, our study is the first to involve thousands of users of code assistants for domain-specific languages. We are also the first code completion tool to present N-Day user retention figures, which is 13.66% on Day 30. We propose an improved version of user acceptance rate, called Strong Acceptance rate, where a suggestion is considered accepted only if less than 50% of it is edited and these edits do not change critical parts of the suggestion. By focusing on Ansible, Lightspeed is able to achieve a strong acceptance rate of 49.08% for multi-line Ansible task suggestions. With our findings we provide insights into the effectiveness of small, dedicated models in a domain-specific context. We hope this work serves as a reference for software engineering and machine learning researchers exploring code c

关键词： Productivity Sentiment analysis Codes Automation Large language models Natural languages Machine learning software software engineering Domain specific languages

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CRAFTER: A Persona Generation Tool for Requirements engineering 19

CRAFTER: A Persona Generation Tool for Requirements Engineer...

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19th international conference on Evaluation of Novel Approaches to software engineering, ENASE 2024

作者： Karolita, Devi Grundy, John Kanij, Tanjila Obie, Humphrey McIntosh, Jennifer Department of Software Systems and Cybersecurity Faculty of Information Technology Monash University Melbourne Australia Department Informatics Engineering Faculty of Engineering Palangka Raya University Palangka Raya Indonesia Faculty of Medicine Dentistry and Health Sciences The University of Melbourne Melbourne Australia

ISBN: (纸本)9789897586965

Personas, a user characterisation, have been widely used in requirements engineering (RE) to enhance the understanding of end-users and their needs. However, the persona generation process is time-consuming and demands familiarity with a user-centered approach. the central issue lies in existing tools for automatically generating personas, which are restricted to generating persona templates and provide limited user control to tailor personas according to their specific needs. this paper introduces CRAFTER, a persona generation tool that uses Large Language Models (GPT-3.5 model). this tool not only automates persona creation but also offers recommendations to users for generating personas tailored to their requirements. the study involved an online questionnaire with 19 respondents who utilised the tool, providing feedback that indicated the tool’s sufficiency for persona generation while identifying areas for improvement. Beyond its primary function, CRAFTER stands out by providing guidance to requirements engineers throughout the persona creation process. the tool grants users the flexibility to customise personas based on their specific requirements, acknowledging the crucial human subjectivity in persona development. Additionally, CRAFTER promotes persona reusability, allowing users to save and reuse generated personas for future projects. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Requirements engineering

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Transforming software Development: A Study on the Integration of Multi-Agent Systems and Large Language Models for Automatic Code Generation 12

Transforming Software Development: A Study on the Integratio...

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12th international conference in software engineering Research and Innovation, CONISOFT 2024

作者： Ramirez-Rueda, Rolando Benitez-Guerrero, Edgard Mezura-Godoy, Carmen Barcenas, Everardo Universidad veracruzana Facultad de Estadística e Informática Xalapa Mexico Universidad Nacional Autónoma de México Facultad de Ingeniería Ciudad de México Mexico

ISBN: (纸本)9798331532116

this paper explores the integration of Multi-Agent Systems (MAS) and Large Language Models (LLMs) for auto-matic code generation, addressing the limitations of traditional manual coding. By conducting a comprehensive review of existing literature and analyzing a practical case study, we demonstrate how MAS and LLMs can collaboratively enhance software development processes. the research focuses on the technical and theoretical challenges of this integration, highlighting the potential for improved productivity, adaptability, and quality in code generation. the findings contribute to AI-based software engineering by revealing new research directions in collective intelligence and automated programming. © 2024 IEEE.

关键词： software design

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Quantum-based Automotive threat Intelligence and Countermeasures 24

Quantum-based Automotive Threat Intelligence and Countermeas...

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28th international conference on Evaluation and Assessment in software engineering (EASE)

作者： Barletta, Vita Santa Caivano, Danilo Catalano, Christian De Vincentiis, Mirko Univ Bari Aldo Moro Dept Comp Sci Bari Italy Univ Salento Dept Innovat Engn Lecce Italy

ISBN: (纸本)9798400717017

Due to the increasing amount of software and hardware in connected and autonomous cars, the attack surface is growing, which increases the risk of security attacks. Researchers proposed machine learning or deep learning techniques to identify threats in in-vehicle networks. However, using these techniques is not enough to support the automotive industry since new processes or techniques must be conceptualized to make automotive systems more secure. therefore, this research work presents a methodology, Quantum-based Automotive threat Intelligence and Countermeasures (QUANTICAR), that integrates quantum optimization for CAN bus Intrusion Detection and the National Vulnerability Database (NVD) to understand the automotive attacks. In the first phase, QUANTICAR identifies the different types of attacks and then, based on the specific attack class, extracts new knowledge using the NVD. this contributes not only to improving attack detection but also to developing an Automotive knowledge Base that can support developers and security experts in the secure development of automotive components in compliance with ISO/SAE 21434.

关键词： QBoost CAN bus automotive engineering cybersecurity NLP

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Outlier Detection through Connectivity-Based Outlier Factor for software Defect Prediction 19

Outlier Detection Through Connectivity-Based Outlier Factor ...

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19th international conference on Evaluation of Novel Approaches to software engineering, ENASE 2024

作者： Moldovan, Andrada-Mihaela-Nicoleta Vescan, Andreea Computer Science Department Faculty of Mathematics and Computer Science Babeş-Bolyai University Cluj-Napoca Romania

ISBN: (纸本)9789897586965

Regression testing becomes expensive in terms of time when changes are often made. In order to simplify testing, supervised/unsupervised binary classification software Defect Prediction (SDP) techniques may rule out non-defective components or highlight those components that are most prone to defects. In this paper, outlier detection methods for SDP are investigated. the novelty of this approach is that it was not previously used for this particular task. Two approaches are implemented, namely, simple use of the local outlier factor based on connectivity (Connectivity-based Outlier Factor, COF), respectively, improving it by the Pareto rule (which means that we consider samples with the 20% highest outlier score resulting from the algorithm as outliers), COF + Pareto. the solutions were evaluated in 12 projects from NASA and PROMISE datasets. the results obtained are comparable to state-of-the-art solutions, for some projects, the results range from acceptable to good, compared to the results of other studies. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Anomaly detection

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the Security Analysis of ROS2 Communication 19th

The Security Analysis of ROS2 Communication

引用

19th international conference on Security and Privacy in Communication Networks

作者： Yang, Shuo Li, Hongru Guo, Jian ECNU MoE Engn Res Ctr Software Hardware Codesign Technol & Applicat Shanghai Peoples R China ECNU Shanghai Trusted Ind Internet Software Collaborat Shanghai Peoples R China ECNU Xinjiang Teachers Coll Shanghai Peoples R China ECNU Natl Trusted Embedded Software Engn Technol Res C Shanghai Peoples R China

ISBN: (纸本)9783031649530;9783031649547

With the increasing use of robots in various fields, the importance of communication security between robots and their components has become a pressing concern. As the primary development framework for robot applications, ROS2 is replacing ROS1 at a rapid pace, and its security issues have direct implications for the security of robot systems. this paper presents an exploration and study of the communication security issues of ROS2 by combining CIA triad with the ROS2 communication mechanism. We propose the fundamental security requirements of the ROS2 system under different communication mechanisms and provide formal modeling and definition. Moreover, we classify and analyze network attacks at the ROS2 level and implement a tool, ROS2Tester, to conduct modeling the ROS2 formal security modules, penetration testing and evaluating the security of ROS2 systems.

关键词： ROS2 communication security CIA formal model

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Automated Security Findings Management: A Case Study in Industrial DevOps 44

Automated Security Findings Management: A Case Study in Indu...

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ACM/IEEE 46th international conference on software engineering - software engineering in Practice (ICSE-SEIP)

作者： Voggenreiter, Markus Angermeir, Florian Moyon, Fabiola Schoepp, Ulrich Bonvin, Pierre Ludwig Maximilians Univ Munchen Siemens Technol Munich Germany Fortiss GmbH Munich Germany Tech Univ Munich Siemens Technol Munich Germany Munich Univ Appl Sci Munich Germany

ISBN: (纸本)9798400702174

In recent years, DevOps, the unification of development and operation workflows, has become a trend for the industrial software development lifecycle. Security activities turned into an essential field of application for DevOps principles as they are a fundamental part of secure software development in the industry. A common practice arising from this trend is the automation of security tests that analyze a software product from several perspectives. To effectively improve the security of the analyzed product, the identified security findings must be managed and looped back to the project team for stakeholders to take action. this management must cope with several challenges ranging from low data quality to a consistent prioritization of findings while following DevOps aims. To manage security findings with the same efficiency as other activities in DevOps projects, a methodology for the management of industrial security findings minding DevOps principles is essential. In this paper, we propose a methodology for the management of security findings in industrial DevOps projects, summarizing our research in this domain and presenting the resulting artifact. As an instance of the methodology, we developed the Security Flama, a semantic knowledge base for the automated management of security findings. To analyze the impact of our methodology on industrial practice, we performed a case study on two DevOps projects of a multinational industrial enterprise. the results emphasize the importance of using such an automated methodology in industrial DevOps projects, confirm our approach's usefulness and positive impact on the studied projects, and identify the communication strategy as a crucial factor for usability in practice.

关键词： DevOps security software engineering security findings management

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