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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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2023 IEEE 19th international conference on Automation Science and engineering, CASE 2023

2023 IEEE 19th International Conference on Automation Scienc...

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19th IEEE international conference on Automation Science and engineering, CASE 2023

ISBN: (纸本)9798350320695

the proceedings contain 364 papers. the topics discussed include: a new method for human-machine ratio configuration scheduling problem;dynamics of path following and constrained path synchronization applied to graded concrete element fabrication;object-centric representations for interactive online learning with non-parametric methods;Push-MOG: efficient pushing to consolidate polygonal objects for multi-object grasping;a variable stiffness gripper with dual leaf-spring mechanism;an underactuated tendon-driven gripper with variable stiffness for deformable agri-food objects;privacy-preserving user pose prediction for safe and efficient human-robot interaction;analysis of acceleration data using low-power embedded devices to detect gear faults;distributed behavior trees for heterogeneous robot teams;and an integrated offline and online optimization framework for large scale additive manufacturing.

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Requirements engineering for Feedback Loops in software-Intensive Systems 30

Requirements Engineering for Feedback Loops in Software-Inte...

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30th IEEE international Requirements engineering conference (RE)

作者： Kang, Eunsuk Meira-Goes, Romulo Carnegie Mellon Univ Inst Software Res Pittsburgh PA 15213 USA

ISBN: (数字)9781665460002

ISBN: (纸本)9781665460002

A feedback loop occurs when the output of a system induces certain changes in the environment, which, in turn, influences the system through its input. Certain self-reinforcing feedback loops can inflict significant harm on the environment, by amplifying the existing bias or other undesirable effects over time. In this paper, we argue that such feedback loops are becoming more prevalent in software-intensive systems, and propose a set of requirements engineering activities and research problems for understanding, modeling, and dealing with feedback loops.

关键词： knowledge engineering Feedback loop conferences software Requirements engineering software engineering

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Channeling the Voice of the Crowd: Applying Structured Queries in User Feedback Collection 30th

Channeling the Voice of the Crowd: Applying Structured Queri...

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30th international Working conference on Requirements engineering - Foundation for software Quality (REFSQ)

作者： Radeck, Leon Paech, Barbara Heidelberg Univ Inst Comp Sci D-69120 Heidelberg Germany

ISBN: (纸本)9783031573262;9783031573279

[Context/Motivation] Crowd-based Requirements engineering (CrowdRE) promises to overcome limitations of traditional requirements engineering by actively involving a larger number of users. A common theme in CrowdRE research is the development and deployment of online platforms where users can autonomously provide their feedback about software. [Problems] Current platforms only provide minimal guidance regarding the topics mentioned in the feedback. therefore, it is difficult tomap the feedback to existing requirements and identify gaps. [Principal ideas] To address the problems, we present a systematic process for collecting feedback through a variety of structured questions and an online platform which supports the process. We evaluate the process and the platform in the large-scale interdisciplinary research project SMART-AGE. [Contribution] To our best knowledge, this is the first platform that gathers feedback from a large number of users simultaneously through structured queries. Our contributions include a tailored list of questions for feedback collection, an analysis of how the question characteristics influence the answers and an evaluation of the user acceptance. Our findings indicate that both the quality and quantity of feedback are high, with variations based on the characteristics of the questions. Additionally, our platform is well accepted by its users.

关键词： requirements engineering crowd user feedback collection

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Towards understanding the impact of mental states on software development using EEG 19

Towards understanding the impact of mental states on softwar...

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19th IEEE/ACS international conference on Computer Systems and Applications (AICCSA)

作者： Dlamini, Gcinizwe Singatullina, Karina Succi, Giancarlo Innopolis Univ Innopolis Russia Univ Bologna Bologna Italy

ISBN: (纸本)9798350310085

A programmers mind and mental state are valuable ingredients in software development process. Burnouts and stress are the biggest challenges software developers face in the current age. these challenges has been increasing at a fast rate together with the demand in more reliable software products. Various ways to relieve stress have been adopted and some of them result in autonomous sensory meridian response (ASMR). In this study we present a systematic literature review (SLR) focused on understanding the impact of ASMR in software development related activities and how it can be identified from brain waves using electroencephalography (EEG). From the SLR, we found that there exist a positive correlation between an ASMR therapy and alleviating state anxiety, which also it is suggested that ASMR may involve atypical attention processing. Secondly, the identification of specific brain signals patterns when a person is experiencing ASMR is possible using EEG. However a specific effect on software development related activities and software product is not presented in a scientific literature. Lastly, we found out that there is a need to conduct experiments focused on understanding the effect ASMR has on software development and programmers productivity or creativity. As a result, this work serves as a bases for conducting experiments focused in analyzing the mental states evoked by ASMR and the impact in the software engineering domain.

关键词： ASMR EEG Stress software Development Productivity Health

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SCPatcher: Mining Crowd Security Discussions to Enrich Secure Coding Practices 38

SCPatcher: Mining Crowd Security Discussions to Enrich Secur...

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38th IEEE/ACM international conference on Automated software engineering (ASE)

作者： Jiang, Ziyou Shi, Lin Yang, Guowei Wang, Qing State Key Lab Intelligent Game Beijing Peoples R China Chinese Acad Sci Sci & Technol Integrated Informat Syst Lab Inst Software Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Beihang Univ Sch Software Beijing Peoples R China Univ Queensland Brisbane Qld Australia

ISBN: (纸本)9798350329964

Secure coding practices (SCPs) have been proposed to guide software developers to write code securely to prevent potential security vulnerabilities. Yet, they are typically one-sentence principles without detailed specifications, e.g., "Properly free allocated memory upon the completion of functions and at all exit points.", which makes them difficult to follow in practice, especially for software developers who are not yet experienced in secure programming. To address this problem, this paper proposes SCPatcher, an automated approach to enrich secure coding practices by mining crowd security discussions on online knowledge-sharing platforms, such as Stack Overflow. In particular, for each security post, SCPatcher first extracts the area of coding examples and coding explanations with a fix-prompt tuned Large Language Model (LLM) via Prompt Learning. then, it hierarchically slices the lengthy code into coding examples and summarizes the coding explanations with the areas. Finally, SCPatcher matches the CWE and Public SCP, integrating them with extracted coding examples and explanations to form the SCP specifications, which are the wild SCPs with details, proposed by the developers. To evaluate the performance of SCPatcher, we conduct experiments on 3,907 security posts from Stack Overflow. the experimental results show that SCPatcher outperforms all baselines in extracting the coding examples with 2.73% MLine on average, as well as coding explanations with 3.97% F1 on average. Moreover, we apply SCPatcher on 447 new security posts to further evaluate its practicality, and the extracted SCP specifications enrich the public SCPs with 3,074 lines of code and 1,967 sentences.

关键词： Artificial Intelligence Large Language Model Secure Coding Practice software Security

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Investigating Code Generation Performance of ChatGPT with Crowdsourcing Social Data 47

Investigating Code Generation Performance of ChatGPT with Cr...

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47th IEEE-Computer-Society Annual international conference on Computers, software, and Applications (COMPSAC)

作者： Feng, Yunhe Vanam, Sreecharan Cherukupally, Manasa Zheng, Weijian Qiu, Meikang Chen, Haihua Univ North Texas Denton TX 76203 USA Argonne Natl Lab Argonne IL 60439 USA Dakota State Univ Madison SD USA

ISBN: (纸本)9798350326970

the recent advancements in Artificial Intelligence, particularly in large language models and generative models, are reshaping the field of software engineering by enabling innovative ways of performing various tasks, such as programming, debugging, and testing. However, few existing works have thoroughly explored the potential of AI in code generation and users' attitudes toward AI-assisted coding tools. this knowledge gap leaves it unclear how AI is transforming software engineering and programming education. this paper presents a scalable crowdsourcing data-driven framework to investigate the code generation performance of generative large language models from diverse perspectives across multiple social media platforms. Specifically, we utilize ChatGPT, a popular generative large language model, as a representative example to reveal its insights and patterns in code generation. First, we propose a hybrid keyword word expansion method that integrates words suggested by topic modeling and expert knowledge to filter relevant social posts of interest on Twitter and Reddit. then we collect 316K tweets and 3.2K Reddit posts about ChatGPT's code generation, spanning from Dec. 1, 2022 to January 31, 2023. Our data analytics show that ChatGPT has been used in more than 10 programming languages, with Python and JavaScript being the two most popular, for a diverse range of tasks such as code debugging, interview preparation, and academic assignment solving. Surprisingly, our analysis shows that fear is the dominant emotion associated with ChatGPT's code generation, overshadowing emotions of happiness, anger, surprise, and sadness. Furthermore, we construct a ChatGPT prompt and corresponding code dataset by analyzing the screen-shots of ChatGPT code generation shared on social media. this dataset enables us to evaluate the quality of the generated code, and we have released this dataset to the public. We believe the insights gained from our work will provide valuable guidanc

关键词： ChatGPT Coding Generation software engineering Large Language Models (LLMs) Generative Models Social Media

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CNN Model Compression by Merit-Based Distillation 19

CNN Model Compression by Merit-Based Distillation

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19th IEEE international Colloquium on Signal Processing and Its Applications, CSPA 2023

作者： Morikawa, Takumi Kameyama, Keisuke University of Tsukuba Degree Programs in Systems and Information Engineering Graduate School of Science and Technology Tsukuba Japan University of Tsukuba Faculty of Engineering Information and Systems Tsukuba Japan

ISBN: (纸本)9781665476928

Deep learning has advanced dramatically in recent years, and especially large convolutional neural networks (CNNs) have shown outstanding performance in a wide variety of tasks. However, such large-scale CNNs may not be able to be utilized in practice because they require a lot of computational resources. therefore, there is a need to realize a CNN in a small model that has high performance similar to the large CNN. One method to solve these problems is Distillation, which uses a model of large scale and high performance as the teacher and a small model as the student model, and performs model compression by transferring the knowledge of the teacher model to the student model. However, in distillation, even when the teacher model incorrectly guesses the training input, the student model learns to mimic the teacher. this can prevent the student model from learning better. In this paper, we propose Meritbased Distillation, in which the accuracy of the teacher model's output determines the degree to which the student model mimics the teacher model's output, thereby preventing the student to learn undesired mappings. In the experiment, the effect of the Merit-based Distillation is evaluated. Consequently, the proposed method outperforms the improvements in the generalization by the student models trained by other known methods. © 2023 IEEE.

关键词： Image classification

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InputGen: A Tool for Automatic Generation of Prototype Inputs to Support Rapid Requirements Validation 23

InputGen: A Tool for Automatic Generation of Prototype Input...

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

作者： Chang, Shuanglong Gao, Juntao Yang, Yilong Northeast Petr Univ Sch Comp & Informat Technol Daqing Peoples R China Beihang Univ Sch Software Beijing Peoples R China

ISBN: (纸本)9798350322637

Prototyping is an effective and efficient way of requirement validation to avoid introducing errors in the early stage of software development. Our previous work RM2PT can automatically generate prototypes from requirements models to support incremental and rapid requirements validation. Although the stakeholders can validate requirements through executing the system operations of the generated prototype, the input parameters of system operations still need to be manually typed by the stakeholders. Unlike software testing, the input of system operation must be valid and reasonable for the stakeholders under the specific scenario of use case. this is usually hard to be achieved by the stakeholders who have less knowledge and concern about the state and interface of target system. In this paper, we propose a tool named InputGen to automatically refactor and enhance the generated prototype from RM2PT. the enhanced prototype can automatically generate valid input data of the system operations for requirement validation. In addition, the enhanced prototype provide an external interface to load the initial data from an external file, which can save the time of modeling the data functionality for the administrator. We demonstrate that the enhanced prototype can improve requirements validation efficiency by 13.77 times over the originally generated prototype from RM2PT. Overall, the results were satisfactory. the proposed tool can be further extended and applied for the requirements validation in the software industry. the tool can be downloaded at https://***/advs/ inputgen, and a demo video casting its features is at https: //***/iR_ojHyzDvQ

关键词： Prototype Requirements Model Requirements Validation Input Data Automatically Generate

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engineering Education: A CAN Bus Training System for Students 27th

Engineering Education: A CAN Bus Training System for Student...

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27th international conference on Interactive Collaborative Learning-ICL

作者： Egarter, C. Madritsch, C. Carinthia Univ Appl Sci Villach Austria

ISBN: (纸本)9783031856518;9783031856525

this paper introduces a newly developed compact CAN bus training system, to bridge the gap between theoretical knowledge and practical application in engineering education. the system incorporates a real BMW e46 instrument cluster into a tabletop training device, facilitating direct interaction with CAN bus technology. through a two-phase development process involving literature review and practical adaptation, the system was designed to enhance student engagement and understanding by providing hands-on experience with traditional software like Vector CANoe. Preliminary classroom evaluations indicate a marked improvement in students' comprehension and interest. this approach demonstrates that real-world applications can significantly enhance learning outcomes compared to simulations. Future research will explore the long-term effects of this hands-on educational method on knowledge retention.

关键词： CAN Case-study engineering Education

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Effective Teaching Strategies for Large Classes: A Case Study in software Architecture Education 24

Effective Teaching Strategies for Large Classes: A Case Stud...

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16th international conference on Education Technology and Computers

作者： Castro, Laura M. Hidalgo, Mauricio Astudillo, Hernan Univ A Coruna La Coruna Spain Univ Finis Terrae Santiago Chile Univ Andres Bello Vina Del Mar Chile

ISBN: (纸本)9798400717819

Right after the Covid-19 pandemics, faculty in charge of a software Architecture course (3rd year subject of a software engineering program) faced an unprecedented increase in enrollment figures, doubling previous numbers to reach over a hundred. To adapt their teaching methodologies to this situation, they deployed a strategy of early involvement using a gamified programming learning platform during the first weeks of the semester, together with personal learning contracts during the whole duration of the course. the course had a record success rate of 92%, versus an average of 71% in previous years, but some aspects demand redesign for future versions. First, most students got a full score on their personal learning contracts, and got it early rather than waiting for the semester final weeks;hence, chronological ordering of assignments matters even more than before, as latter assignments may go unfulfilled. Second, many students did this while skipping assignments for some topics, specially visual modeling;hence, learning contracts should stipulate minimal achievements for all learning of special interest. this work aims, through the detailed analysis of this teaching experience, to serve as an inspiration for other faculty who may face similar realities.

关键词： learning contract engagement mentoring continuous evaluation

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