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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

共 17413 条记录，以下是191-200 订阅

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Large Language Models as a Service: optimisation strategies via knowledge Space reduction

Large Language Models as a Service: optimisation strategies ...

引用

IEEE International conference on Omni-Layer Intelligent Systems (IEEE COINS)

作者： Panagoulias, Dimitrios P. Virvou, Maria Tsihrintzis, George A. Univ Piraeus Dept Informat Piraeus 18534 Greece

ISBN: (纸本)9798350349603;9798350349597

In Large Language Models (LLMs), "reducing the domain space" for text generation refers to limiting the range of content to be utilized for generating responses. This work explores Sequential Language Model Integration (SLMI), which mirrors the organization and distribution of knowledge across different fields of expertise. SLMI is the technique of linking multiple LLMs in a systematic manner and creating LLM-chains. In this paper, we refer to a process of choosing, linking and connecting LLMs with other services (invoke external machine learning processes or rule based applications) as "Large Language Models as a Service" to describe a complete system with specific agency. We outline the development and evaluation process of an SLMI methodology to refine response accuracy and we evaluate the methodology in the domain of dermatology using medical knowledge paths, where gains were found regarding diagnostic accuracy.

关键词： AI-empowered software engineering Large Language Models GPT BERT

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Stage division of research evolution based on scientific change theory and science mapping software 3

Stage division of research evolution based on scientific cha...

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3rd International conference on Electronic Information engineering and Data Processing, EIEDP 2024

作者： Chen, Wei Lin, Te-Hsun Miao, Changqing School of Economics and Management Jiaying University Guangdong Meizhou China

ISBN: (纸本)9781510680531

By dividing the evolutionary stages of a research field, a researcher can identify the knowledge structure, research focus and characteristics of this field. This paper develops a visualization method to identify research evolution stages. We firstly use the clustering analysis function of the knowledge mapping software CiteSpace to identify the research frontiers in a research field and visualize the evolution process of a certain research frontier in the Timeline View, and then divide and interpret the research stages with the help of Shneider's scientific change theory. This paper takes the field of value co-creation as an example to verify this method. The results show that CiteSpace software can identify the research frontiers and visualize the research evolution process of a certain research frontier, and we can easily divide research stages under the guidance of the scientific change theory. © 2024 SPIE.

关键词： Mapping

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ZK-CPABE: Blockchain-based CP-ABE Scheme Via Zero-knowledge Proof 7

ZK-CPABE: Blockchain-based CP-ABE Scheme Via Zero-Knowledge ...

引用

7th International conference on Advanced Electronic Materials, Computers, and software engineering, AEMCSE 2024

作者： Zhao, Jinyi Zhu, Jie Yin, Peng Yu, Yimin Xie, Long School of Logistics and Management Engineering Yunnan University of Finance and Economics Kunming China Division of Science & Technology Administration Yunnan University of Finance and Economics Kunming China Lianjia Primary School Wuhua District Kunming China School of Information Yunnan University of Finance and Economics Kunming China

ISBN: (纸本)9781510681866

The integration of blockchain technology with Ciphertext-Policy Attribute-based Encryption (CP-ABE) has addressed key challenges in distributed systems, such as mutual trust and collusion, while enhancing auditability of key management. However, existing blockchain-based CP-ABE models face a trilemma, unable to achieve decentralization, scalability, and security concurrently. Therefore, we propose ZK-CPABE, which merges Zero-knowledge Proofs with blockchain-based CP-ABE, significantly improving verifiability and scalability. This system combines a secure private key distribution and zero-knowledge proofs to construct off-chain computation and scalable transactions for CP-ABE. Our Ethereum-based ZK-CPABE prototype demonstrates its effectiveness and potential for secure, scalable data sharing and access control. © 2024 SPIE.

关键词： Blockchain

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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...

引用

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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Course Assessment Reform based on Internet and Mobile Internet Technology 24

Course Assessment Reform Based on Internet and Mobile Intern...

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7th International conference on Educational Technology Management, ICETM 2024

作者： Lin, Yubei Tan, Mingkui School of Software Engineering South China University of Technology Guangdong Guangzhou China

ISBN: (纸本)9798400717468

Examination and evaluation are effective methods for assessing the effectiveness of teaching and the quality of talent cultivation, which are essential components of the teaching process. Traditional course assessments focus on final assessments through paper-based tests, with grading relying on manual labor, which is inefficient and prone to errors. based on Internet and mobile Internet technologies, this paper proposes a course assessment mechanism that combines both process-oriented and summative evaluations. Considering the large number of students and the multitude of knowledge points in the Introduction to Computer and software engineering course, the smart teaching tool Yuketang is used to implement process-oriented assessments, while the summative evaluations are completed using an online examination system developed by the teaching team. After several rounds of teaching practice, the reform measures have been proven to effectively enhance teaching efficiency and improve the quality of teaching. © 2024 Copyright held by the owner/author(s).

关键词： Curricula

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Log Parsing with Prompt-based Few-shot Learning 23

Log Parsing with Prompt-based Few-shot Learning

引用

45th IEEE/ACM International conference on software engineering (ICSE)

作者： Le, Van-Hoang Zhang, Hongyu Univ Newcastle Sch Informat & Phys Sci Callaghan NSW Australia Chongqing Univ Sch Big Data & Software Engn Chongqing Peoples R China

ISBN: (纸本)9781665457019

Logs generated by large-scale software systems provide crucial information for engineers to understand the system status and diagnose problems of the systems. Log parsing, which converts raw log messages into structured data, is the first step to enabling automated log analytics. Existing log parsers extract the common part as log templates using statistical features. However, these log parsers often fail to identify the correct templates and parameters because: 1) they often overlook the semantic meaning of log messages, and 2) they require domain-specific knowledge for different log datasets. To address the limitations of existing methods, in this paper, we propose LogPPT to capture the patterns of templates using prompt-based few-shot learning. LogPPT utilises a novel prompt tuning method to recognise keywords and parameters based on a few labelled log data. In addition, an adaptive random sampling algorithm is designed to select a small yet diverse training set. We have conducted extensive experiments on 16 public log datasets. The experimental results show that LogPPT is effective and efficient for log parsing.

关键词： log parsing few-shot learning prompt-tuning deep learning

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Design of a Digital Navigation Assistant in EMINUS for People with Visual Disabilities 12

Design of a Digital Navigation Assistant in EMINUS for Peopl...

引用

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

作者： Millan Martinez, Max William Barradas, Virginia Lagunes Rojano-Caceres, Jose Rafael Maestría en Sistemas Computacionales Tecnm Instituto Tecnológico Superior de Xalapa Veracruz Xalapa Mexico Universidad Veracruzana Facultad de Estadística e Informática Veracruz Xalapa Mexico

ISBN: (纸本)9798331532116

Requirements analysis is crucial in software system development. With the growth of Artificial Intelligence (AI)-based solutions, this analysis has gained greater importance to create more robust and accessibility-focused solutions. This study defines the software requirements for designing a virtual assistant that utilizes Natural Language Processing (NLP) to facilitate navigation through voice commands for visually impaired people on the EMINUS educational platform, belonging to the Universidad Veracruzana. The necessary requirements are detailed using Google Cloud Text-to-Speech API, neural networks with Bayesian classification algorithms, Rest API services through ***, JavaScript, and HTML5 for creating a plugin in Google Chrome. © 2024 IEEE.

关键词： software design

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The Progression of Competencies and Dispositions: How do Maturing software Engineers Compare? 54

The Progression of Competencies and Dispositions: How do Mat...

引用

54th IEEE Frontiers in Education conference, FIE 2024

作者： Clear, Tony Clear, Alison Auckland University of Technology Department of Computer Science and Software Engineering Auckand New Zealand School of Computing Eastern Institute of technology Auckland New Zealand

ISBN: (纸本)9798350351507

This research paper describes and extends the outcomes from an in- depth study investigating the difference in the expected skills requirements from junior software engineers to senior software engineers, and reflections on the findings from that study. It is a given that senior software engineers have more experience and skills than junior software engineers. However, a focus on their differing competencies and dispositions provides an enhanced mechanism for comparison. Gaps were identified in assessing 'professional knowledge' as categorized by the IEEE/ACM Computing Curriculum Overview Report (CC2020), and in assessing 'dispositions'. It appeared that the specific scenario of comparing the expected competencies between junior and senior software engineers, tested the framework for assessing competencies developed in the CC2020 project and applied in its mapping to the IEEE/ACM Computer Science (CS2013) approved curriculum. In this study into the difference between Junior and Senior software Engineers, an initial review of relevant literature was conducted. The review found that research analyzing job requirements for software engineers of different levels was limited;'experience' as a keyword was seldom mentioned;and a common distinction was made between 'soft' and 'hard' skills - the latter being skills that were 'technical', such as programming languages, frameworks, libraries, and tools, whereas soft skills referred to skills such as personality traits, attitudes, and teamwork skills. In our extension of that work the notion of soft skills was unpacked into professional skills and dispositions. The process of mapping from the CC2020 competency framework to the CS2013 curriculum had deliberately modelled how to represent a competency-based rather than a knowledge-based curriculum. The critical deficiency identified here was the limitation imposed by adopting a skills framework based on the cognitive taxonomy, and thereby unwittingly omitting the crucial compani

关键词： Mapping

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Marker-based AR Application for Better Understanding of Electrical Circuits and Capacitors 4

Marker-Based AR Application for Better Understanding of Elec...

引用

4th International conference on Sustainable Expert Systems, ICSES 2024

作者： Poddar, Kishan Sharma, Bhanu Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9798331540364

This paper proposes a marker-based Augmented Reality (AR) electric circuit meant to help students grasp the knowledge of electrical circuits, especially the usage of capacitors. Recognizing components like the battery, switch, capacitor and bulb, the AR software allows students to engage with real-time representations of electrical activity including capacitor charging and discharging. The interesting and dynamic AR environment helps abstract ideas to be more interactive and accessible, therefore improving knowledge. Early evidence indicates that, when compared to conventional teaching methods, the AR tool greatly increases student attention and knowledge even if there are some technical limitations such inconsistent marker recognition problems. Positive remarks suggest that AR may be a helpful tool for questioning concepts in electrical engineering. Future initiatives will focus on enhancing the technical aspects of the system and extending its contents to provide a more whole learning experience in numerous educational situations. © 2024 IEEE.

关键词： Capacitor bank

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GSAGE2defect: An Improved Approach to software Defect Prediction based on Inductive Graph Neural Network 35

GSAGE2defect: An Improved Approach to Software Defect Predic...

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35th International conference on software engineering and knowledge engineering, SEKE 2023

作者： Ma, Ju Sun, Yi-Yang He, Peng Zeng, Zhang-Fan School of Computer Science and Information Engineering Hubei University Wuhan China School of Cyber Science and Technology Hubei University Wuhan China

Graph neural network is an effective deep learning framework for learning graph data. Existing research has introduced different variants of graph neural networks into the field of software defects and has achieved promising results. However, the graph neural network model based on the previous research is essentially transductive, is applied to a single fixed graph, and often ignores the direction and weight of the edges when modeling the network. In practice, software systems are dynamically evolving. Furthermore, in software network modeling, the direction and weight of edges are factors that are worth considering. based on an inductive graph neural network, we proposed an improved defect prediction method named GSAGE2defect. We first constructed the class dependency network of the program and then used node2vec for embedding learning to automatically obtain the structural features of the network. Then we combined the learned structural features with traditional software code features to initialize the properties of nodes in the class dependency network. Next, we fed the dependency network to GraphSAGE for a deeper class representation. Finally, we evaluated the proposed method based on eight open-source programs and demonstrated that GSAGE2defect achieves an average improvement of 2.09%-26.69% over state-of-the-art methods in terms of F-measure. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Graph neural networks

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