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

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SelfPiCo: Self-Guided Partial Code Execution with LLMs 2024

SelfPiCo: Self-Guided Partial Code Execution with LLMs

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33rd ACM SIGSOFT International conference on software Testing and Analysis (ISSTA)

作者： Xue, Zhipeng Gao, Zhipeng Wang, Shaohua Li, Shanping Xia, Xin Hu, Xing Zhejiang Univ Hangzhou Peoples R China Cent Univ Finance & Econ Beijing Peoples R China

ISBN: (纸本)9798400706127

Code executability plays a vital role in software debugging and testing (e.g., detecting runtime exceptions or assertion violations). However, code execution, especially partial or arbitrary code execution, is a non-trivial task due to missing definitions and complex third-party dependencies. To make partial code (such as code snippets posted on the web or code fragments deep inside complex software projects) executable, the existing study has proposed a machine learning model to predict the undefined element types and inject the pre-defined dummy values into execution. However, the performance of their tool is limited due to its simply designed dummy values and the inability to continue learning. In this paper, we design and implement a novel framework, named SELFPICO (Self-Guided Partial Code Executor), to dynamically guide partial code execution by incorporating the open-source LLM (i.e., Code Llama) within an interactive loop. Particularly, SELFPiCo leverages few-shot in-context learning and chain-of-thought reasoning to elicit human knowledge and logical reasoning based on fine-tuning the Code Llama model. SELFPiCo continuously learns from code execution results and refines its predictions step after step. Our evaluations demonstrate that SELFPiCo can execute 72.7% and 83.3% of all lines in the open-source code and Stack Overflow snippets, outperforming the most recent state-of-the-art Lexecutor by 37.9% and 33.5%, respectively. Moreover, SELFPiCo successfully detected 18 and 33 runtime type error issues by executing the partial code from eight GitHub software projects and 43 Stack Overflow posts, demonstrating the practical usage and potential application of our framework in practice.

关键词： Partial Code Execution Dynamic Analysis Large Language Model Prompt engineering

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Complexity Handling in the software-Defined Vehicles: Documenting the Expert knowledge

Complexity Handling in the Software-Defined Vehicles: Docume...

引用

IEEE International conference on software Architecture Workshops (ICSAW)

作者： Xinxin Zhu Rose Sturm Christian Seiler Stefan Wagner Mercedes-Benz AG Böblingen Germany Mercedes-Benz AG Sindelfingen Germany Technical University of Munich Heilbronn Germany

ISBN: (数字)9798331533366

ISBN: (纸本)9798331533373

Technological advancements drive the development of new Electric/Electronic and software architectures, shifting the automotive industry to a software-defined paradigm. This change has significantly impacted product configuration, and is also expected to be crucial in maintenance and upgradability throughout the entire lifecycle. This position paper analyzes current complexities in product configuration and maintenance, emphasizing the expert knowledge on component dependency, based on functionalities and properties as well as legal and sales factors, is often applied indirectly, leading to insufficiencies. This paper proposes the idea of comprehensive documentation of relevant expert knowledge and direct utilization of this in product configuration, maintenance and upgrades. This approach aims to ensure efficient component deployment throughout the vehicle's lifecycle, preserving functional integrity with minimal errors and effort.

关键词： Industries knowledge engineering software architecture Law Documentation Transforms software Maintenance Complexity theory Automotive engineering

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Bridging Theory and Practice in Antenna Education: Students Perceptions on software based Learning 52

Bridging Theory and Practice in Antenna Education: Students ...

引用

52nd Annual conference of the European Society for engineering: Educating Responsible Engineers, SEFI 2024

作者： Asfour, R. Khamas, S. Saad, R. Department of Electronic and Electrical Engineering The University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9782873520274

In the field of engineering education, the traditional approach of solely imparting theoretical knowledge has evolved to emphasise the significance of experiential learning. Providing engineering students with opportunities to learn through hands-on experiences, critical thinking, and analysis has become increasingly essential. This shift is not only beneficial for enhancing students' understanding of theoretical concepts but also crucial for fostering practical skills and preparing them for the challenges of the modern workplace. Theoretical modules such as antennas and propagation in electromagnetics present challenges rooted in advanced mathematics and complex theoretical concepts, leading to a notable gap between theory and practice. We implemented computer simulation classes alongside traditional lectures to address this gap and enrich students' learning experiences. These simulation sessions offer students a virtual prototyping environment, guiding them through the complete design cycle - from model creation to generating Gerber files necessary for real-world antenna fabrication. Additionally, the classes incorporate 3D visualisation tools to facilitate understanding of intricate concepts. To reinforce the connection between simulation and real-world applications, each session begins with demonstrations of antenna prototypes. At the conclusion of the semester, a survey was administered to assess student satisfaction with the approach, yielding positive feedback. © 2024 SEFI 2024 - 52nd Annual conference of the European Society for engineering, Proceedings: Educating Responsible Engineers. All rights reserved.

关键词： Virtual prototyping

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Time series classification based on Unet with 2D transformation 12

Time series classification based on Unet with 2D transformat...

引用

12th IEEE International conference on Identification, Information and knowledge in the Internet of Things, IIKI 2024

作者： Du, Mingsen Wang, Yunxia Wei, Yanxuan Wu, Xiaona Ji, Cun Shandong Normal University School of Information Science and Engineering Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China

ISBN: (纸本)9798331510633

Time series classification has gained significant attention in the data mining field in recent years. Despite the proposal of numerous methods over the past decades, most of these approaches focus on feature extraction in one-dimensional space, which often results in lower classification accuracy. To address this issue, this paper proposes a Time Series Classification method based on U-Net with 2D transformation (TSC-Unet). This method first transforms univariate time series into 2D space and augments the data, effectively enhancing the diversity of the dataset. Subsequently, features are extracted from the 2D space using a fully convolutional network, fully exploiting multi-scale feature information. U-Netwith skip connections, effectively retains and transmits high-resolution features, significantly reducing information loss and improving segmentation performance. Additionally, the ability to learn multi-scale features enables the model to capture details at different levels, thereby enhancing its understanding of complex data. Experimental results demonstrate that TSC-Unet achieves high classification accuracy on the UCR datasets, validating the effectiveness and superiority of the proposed method. © 2024 IEEE.

关键词： Time series

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Methodology Metadata-driven knowledge Production Charac-teristics Identification by knowledge Retrieval and Mining 7

Methodology Metadata-driven Knowledge Production Charac-teri...

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7th International conference on Data Science and Information Technology, DSIT 2024

作者： Xu, Hao Ge, Linlin Zhang, Yan Jin, Zhenqiang Wang, Mulan Feng, Ke Kang, Zhenyuan Nanjing Institute of Technology School of Management Engineering Nanjing China Nanjing University School of Information Management Nanjing China Nanjing Institute of Technology School of Electrical Power Engineering Shen Guorong College Nanjing China Jiangsu Power Transmission & Transformation Co. Ltd Nanjing China

ISBN: (纸本)9798350384093

The progress of science, technology, and innovation is greatly aided by the advancement, improvement, and use of methodology. Our work developed a Characteristic Recognition Algorithm based on text mining to extract methodology metadata from full-text documents and identify characteristics that are methodologically driven by time trend, dissemination speed, and co-drive. A sample of 5564 publications from the economic and management (E&M) discipline were chosen, from which 9,995 methodological metadata were extracted and classified into 4 categories: model, software & tool (S&T), data, and method & theory (M&T). The co-occurrence trait was revealed using the social network approach. Results indicate that over the past 20 years, the methodology's usage rate has increased, reaching 78.49% in 2019 alone. While S&T, model, and data have slowed down, M&T has the highest usage rate, which is reflected in a continually rising diffusion feature. The outcomes of knowledge creation in E&M exhibit the features of multi-methodology that is frequently driven, including M&T (hypotheses, questionnaire surveys), data (China Statistical Yearbook, wind, and CSMAR), model (double difference and logit), and S&T (SPSS, Amos, LISREL). The process of defining characteristics of approach metadata-driven knowledge production will be applied to different areas as a preliminary investigation, as well as used as training material for the automatic extraction of large-scale corpora. © 2024 IEEE.

关键词： Intelligent Computing knowledge Production Characteristics knowledge Retrieval and Mining Methodology Driven Social Network Analysis

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Cloud-based Machine Learning Adoption Model for Higher Education Institutions

Cloud-based Machine Learning Adoption Model for Higher Educa...

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2024 International conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Kiros, Atakilti Brhanu Salau, Ayodeji Olalekan Vats, Satvik Kaushik, Keshav Tin, Ting Tin Omeje, Crescent Onyebuchi Mekelle University Mekelle Institute of Technology Mit Mekelle Ethiopia Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria Department of Cse Graphic Era Hill University Uttarakhand Dehradun India Graphic Era Deemed to be University Uttarakhand Dehradun248007 India Amity School of Engineering and Technology Amity University Mohali Punjab India Inti International University Faculty of Data Science and Information Technology Negeri Sembilan Malaysia University of Port Harcourt Department of Electrical/Electronic Engineering Rivers State Choba500004 Nigeria

ISBN: (纸本)9798350379716

As a new concept, cloud computing has attracted the IT Initiations attention especially the Mobile learning (M-learning). At present, there Higher Education Institutions (HEI's) have struggle with limited IT budgets, difficulties in obtaining and managing infrastructure licenses, and the complexities of software and hardware management. The coming of cloud computing, all of the above challenges was solved. The migration to cloud based M-learning in HEI's is a significant stage in terms of online education, especially during the COVID-19 pandemic. Cloud based M-learning approach has the potential to be a powerful and rapid solution to the many challenges faced by universities in this unprecedented time. This study starts with some brief concepts of Cloud Computing and M-learning for HEI's, mentioning for the significance of the results obtained so far. Additionally, it starting point as strategy for HEI's to adopt Cloud based M-learning is provided, by comparisons of existing models and select DOI model to propose cloud based adoption model. But, the DOI model has its own weaknesses;for example, it does not take into account the localization as Innovation determinants. This study introduces localization phase for the optimal performance of the adopted model. The adoption model was evaluating the importance of the proposed model by IT domain experts and it initiates to be both useful and suitable for a successful cloud based M-learning adoption Ethiopian perspective. Therefore, the research results obtained are promising and funding the use of Cloud based M-learning solutions for Ethiopia HEI's by improving knowledge and skill in this field provides a useful strategy for the HEI's structure. © 2024 IEEE.

关键词： Federated learning

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Cultivation Mechanism of College Students' Network Literacy in the Era of Mobile Internet 24

Cultivation Mechanism of College Students' Network Literacy ...

引用

2024 International conference on Intelligent Education and Computer Technology, IECT 2024

作者： Lei, Ying Yin, Xiaohua Zhang, Qian Hossin, Md Altab Mental Health Center University of Electronic Science and Technology of China Chengdu611731 China School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Innovation and Entrepreneurship Chengdu University Chengdu610106 China

ISBN: (纸本)9798400709920

In the era of mobile internet, network literacy is an important part of the overall quality of college students. Improving the network literacy of college students is of great practical significance for strengthening and improving ideological and political education in colleges and universities. At present, the network illiteracy of Chinese college students is at a spontaneous stage, including the identification of network information, the ability of network application software, the self-restraint of the network, and the legal issues in the field of network morality. The cultivation of College Students' network literacy is a systematic task and need to integrate several layers using web-based computer technologies and algorithms. based on the extant situation and data mining results, this paper designed and proposed a framework for cultivating college students' network literacy by integrating web technologies and suggests and discusses the "four all-round penetration"mechanism to cultivate college students' network literacy from four aspects, such as social guidance, college education, family guidance, and self-efficacy. Implementation of these scientific and reasonable four aspects can enhance the knowledge of network literacy of college students and is important for their career development, morality, and psychological stability. © 2024 ACM.

关键词： Students

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Exploring Language Diversity to Improve Neural Text Generation 1

引用

17th International conference on knowledge Science, engineering and Management (KSEM)

作者： Xu, Lingjiao Chen, Xingyuan Wang, Bing Jin, Peng Southwest Petr Univ Sch Comp & Software Engn Chengdu 610500 Sichuan Peoples R China Leshan Normal Univ Sichuan Prov Educ Dept Key Lab Internet Nat Language Proc Leshan Peoples R China Sichuan Prov Key Lab Philosophy & Social Sci Lang Leshan Peoples R China

ISBN: (数字)9789819754892

ISBN: (纸本)9789819754885;9789819754892

Text Generation aims to utilize contextual details to generate linguistically appropriate language. Research has demonstrated that integrating various linguistic features can significantly enhance the quality of text generation tasks. In light of this, this paper proposes an innovative approach Diversity Text Generation (DiversityGen)-and makes advancements in three aspects. Firstly, data augmentation techniques are employed to transform the original data, thereby enhancing the latent features of the text. Secondly, in the conversion of the model's distributed vector output into text, a combination of Top-K and Beam Search decoding methods (Top-k-bs-m) is utilized. This extends the search space through random sampling during Beam Search decoding, thereby improving decoding performance and generating diversified text. Lastly, the concept of Over Generation (OGen) is introduced, wherein the results are filtered using three probability maximization-based methods to optimize output diversity. Experimental results demonstrate the effectiveness of this approach in question generation and text summarization tasks, surpassing current benchmarks.

关键词： Diversity Generation Decoding strategy Search Space Data Augmentation

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WBS: Weighted Backtracking Strategy for Symbolic Testing of Embedded software 34

WBS: Weighted Backtracking Strategy for Symbolic Testing of ...

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34th International conference on software engineering and knowledge engineering, SEKE 2022

作者： Suresh, Varsha P. Chakrabarti, Sujit Kumar Suresh, Athul Jetley, Raoul International Institute of Information Technology Bangalore Bengaluru India ABB Corporate Research Bengaluru India

ISBN: (纸本)1891706543

Symbolic execution is an important program analysis technique that has found a number of applications in the last fifteen years or so. Popular symbolic execution approaches use backtracking when faced with infeasibility along a path being explored. A simple backtracking strategy (i.e. backtracking by a single decision node) may suffice when the goal is to cover the entire control flow graph (CFG). However, if the goal is to cover specific parts of the CFG through a single path, simple backtracking may lead to non-optimality or even non-termination. In this paper, we present weighted backtracking strategy (WBS) that exploits previous knowledge about the program behaviour to compute 'good' candidates as destinations of backtracking. We have integrated our heuristic to SymTest, a symbolic testing framework for embedded systems. Experiments with case-studies have demonstrated that WBS improves SymTest's performance both in its ability to achieve termination as well as in computing shorter test sequences compared to the original approach. SymTest with WBS generates shorter test sequences compared to several other existing test generation approaches based on symbolic execution. © 2022 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Embedded systems

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Rule based System for Enterprise Resources Planning Decision 14

Rule based System for Enterprise Resources Planning Decision

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14th International conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Kalgaonkar, Amol S. Chavan, Pallavi Computer Engineering Ramrao Adik Institute of Technology D Y Patil Deemed to be University Nerul MH Navi Mumbai India Information Technology Ramrao Adik Institute of Technology D Y Patil Deemed to be University Nerul MH Navi Mumbai India

Enterprise Resource Planning development and deployment is in many occasions a considerably significant step in the complete transformation road map related to business. A correct selection of an ERP software is essential. It is also significant to take a decision around the overall need of an ERP itself. Considering this important background, this is an effort to come up with a rule-based expert system for such a decision making. These overall efforts encompass the feature of decision-making method with an attempt to codify the process to achieve benefits of having almost many advisor’s knowledge at one’s disposal. © Grenze Scientific Society, 2023.

关键词： Decision support systems

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