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检索条件"任意字段=Proceedings of the 9th Knowledge-Based Software Engineering Conference"

共 20366 条记录，以下是4701-4710 订阅

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Design and Implementation of VxWorks System Vulnerability Mining Framework based on Dynamic Symbol Execution 9th

Design and Implementation of VxWorks System Vulnerability Mi...

引用

9th International conference on Computer engineering and Networks, CENet2019

作者： Zheng, Wei Zhou, Yu Wang, Boheng Information Technology Services East China Normal University North Zhong Shan Road 3663 Shanghai China Ant-Financial Light-Year Security Lab Hangzhou China School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China

ISBN: (纸本)9789811537523

In recent years, with the popularity of VxWorks systems in various fields, VxWorks systems have been used in the underlying operating systems of industrial infrastructure in many countries. therefore, in order to ensure the rights of the country and the people, the security requirements of the system are also increasing. this article introduces the technical details of the VxWorks system vulnerability mining framework based on dynamic symbolic execution, the overall framework flow, and the experimental results of the framework. the entire framework is mainly composed of the WDB RPC-based Trace module, the dynamic symbol execution module, and the fuzzing test module. During the testing phase, the framework successfully exploited the CVE-2015-7599 vulnerability and proved the effectiveness of the vulnerability mining framework designed in this paper. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Dynamic symbol execution VxWorks system WDB RPC protocol

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ICEIT 2020 - proceedings of 2020 9th International conference on Educational and Information Technology

ICEIT 2020 - Proceedings of 2020 9th International Conferenc...

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9th International conference on Educational and Information Technology, ICEIT 2020

ISBN: (纸本)9781450375085

the proceedings contain 47 papers. the topics discussed include: an optimal slack-based course scheduling algorithm for personalized study plans;an empirical assessment of software engineering curriculum in developing economies and its professional relevance;effects of a computational thinking experimental course on studentś perceptions of their problem-solving skills;a conceptual framework for cloud-based collaborative online course provision;enhancing computing curriculum with collaborative engagement model to enrich undergraduate research experience;critical thinking development in collaborative learning: case study of transformer topic through lesson study at junior high school;analysis on the cost of implementing the flipped classroom model in universities;classroom teaching evaluation based on facial expression recognition;and a comparative analysis of consistency among self, peer, and teacher assessment during a collaborative learning experience.

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MV-HAN: A Hybrid Attentive Networks based Multi-View Learning Model for Large-scale Contents Recommendation 22

MV-HAN: A Hybrid Attentive Networks based Multi-View Learnin...

引用

proceedings of the 37th IEEE/ACM International conference on Automated software engineering

作者： Ge Fan Chaoyun Zhang Kai Wang Junyang Chen Tencent Inc. China Microsoft Research China the College of Computer Science and Software Engineering Shenzhen University China

ISBN: (纸本)9781450394758

Industrial recommender systems usually employ multi-source data to improve the recommendation quality, while effectively sharing information between different data sources remain a challenge. In this paper, we introduce a novel Multi-View Approach with Hybrid Attentive Networks (MV-HAN) for contents retrieval at the matching stage of recommender systems. the proposed model enables high-order feature interaction from various input features while effectively transferring knowledge between different types. By employing a well-placed parameters sharing strategy, the MV-HAN substantially improves the retrieval performance in sparse types. the designed MV-HAN inherits the efficiency advantages in the online service from the two-tower model, by mapping users and contents of different types into the same features space. this enables fast retrieval of similar contents with an approximate nearest neighbor algorithm. We conduct offline experiments on several industrial datasets, demonstrating that the proposed MV-HAN significantly outperforms baselines on the content retrieval tasks. Importantly, the MV-HAN is deployed in a real-world matching system. Online A/B test results show that the proposed method can significantly improve the quality of recommendations.

关键词： Transfer Learning Deep Learning Multi-View Learning Recommender Systems

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thURSDAY: A Web Platform to Support AutoML 22

THURSDAY: A Web Platform to Support AutoML

引用

proceedings of the 9th International conference on Applied Computing & Information Technology

作者： Chase Carthen Christopher Lewis Vinh Le Alireza Tavakkoli Frederick Harris Sergiu Dascalu Computer Science & Engineering University of Nevada Reno USA

ISBN: (纸本)9781450397605

thURSDAY is a web platform that aids users in building machine learning models by providing easily accessible tools to either create models manually, or through the use of automated machine learning (AutoML) libraries like AutoKeras. As part of thURSDAY’s key innovations, users are given the opportunity to configure and run multiple machine learning models. the results of these model executions can then be compared with built-in performance metrics. Finally, thURSDAY allows users to analyze hyperparameter changes, as well as the changes created by AutoML libraries, in order to provide a vital tool that aids in the revision of existing models. To meet the high volume demands of machine learning, thURDAY adopted a microservice-based design pattern that supports containerization, orchestration, and scalabability. In this paper, the design, implementation, and impact of the thURSDAY system is explored in detail. In order to evaluate the capability of thURSDAY, its core functionality is compared against similar platforms that provide machine learning support.

关键词： visualization neural networks deep learning human computer interaction automl

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Using recurrent neural networks for classification of natural language-based non-functional requirements

Using recurrent neural networks for classification of natura...

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Joint Workshops of the 27th International conference on Requirements engineering, REFSQ 2021 - OpenRE, Posters and Tools Track, and Doctoral Symposium

作者： Gnanasekaran, Rajesh Kumar Chakraborty, Suranjan Dehlinger, Josh Deng, Lin Department of Computer and Information Sciences Towson University TowsonMD21252 United States

In software projects, non-functional software requirements (NFRs) are critical because they specify system quality and constraints. As NFRs are in natural language, accurately analyzing NFRs requires domain knowledge, expertise, and significant human efforts. Automated approaches that can help identify and classify NFRs can lead to reduced ambiguity and misunderstanding among software engineers, decreasing developmental costs and increasing software quality. this paper investigates the effectiveness of leveraging machine learning techniques to automatically classify various types of NFRs. Specifically, we develop and train a recurrent neural network model, which has been evaluated to be effective in handling sequential natural language text, to classify natural language NFRs into five different categories: maintainability, operability, performance, security, and usability. We evaluate and detail insights from the experimental study performed on two data sets that contain almost 1,000 NFRs. the experimental results show that this approach can classify NFRs with a precision average of 84%, recall of 85%, F1-score near 84%, and classification accuracy of 88% on the testing data set. As indicated by the results, applying appropriate machine learning techniques can help reduce manual efforts, eliminate human mistakes, facilitate the software requirements analysis process, and lessen developmental costs. © 2021 CEUR-WS. All rights reserved.

关键词： Requirements engineering

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Cascading chaotic spreading sequences based on OCDMA-WDM-PON technology 23

Cascading chaotic spreading sequences based on OCDMA-WDM-PON...

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proceedings of the 2023 9th International conference on Communication and Information Processing

作者： Zhili Wang Liwei Yang Zeyang Bi Xue Liang Lihao Zhao Jiade Zhang College of Information and Electrical Engineering China Agricultural University China College of Mechatronics Engineering Beijing Information Science and Technology University China

ISBN: (纸本)9798400708909

this paper suggests a chaotic spread-spectrum address code design method for OCDMA-WDM-PON technology to meet the needs of passive optical networks, namely high efficiency, uniqueness, and easy implementation. the approach uses optical correlation technology to develop a spread-spectrum address code that effectively fulfills these requirements. Initially, a preferred sequence is established using the parameter control method. the output of the segmented Logistic sequence is utilized to control the fractal parameters of the Chebyshev mapping, enabling a more uniform and random variation within a specified range. this is achieved through the analysis of standard discrete chaotic series. Next, the real-valued chaotic series are transformed into numerical chaotic series to facilitate the characterization and selection of efficient preferred strategies. Subsequently, the judgment results of the preferred strategy are fed back to the improved chaotic system to obtain an excellent chaotic sequence. the constructed preferred sequence is assessed through experimental simulation, which considers factors such as iterative trajectory, initial value sensitivity, correlation properties, and the balance of the sequence. Furthermore, the system's bit error rate (BER) performance is evaluated by developing a spread-spectrum communication simulation system based on this chaotic sequence. the simulation results indicate that the preferred sequence can be successfully applied to the OCDMA-WDM-PON system, effectively meeting the BER performance needed while ensuring high speed, high capacity, and high security. these results validate the feasibility and effectiveness of the preferred sequence, thus confirming its potential to meet the future demands of high-speed broadband communication.

关键词： chaotic sequence passive optical network preference strategy spread spectrum address code

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Risk degree measurement research and empirical analysis on deep foundation pit construction of metro stations based on SEM-MC 9

Risk degree measurement research and empirical analysis on d...

引用

9th International Symposium on Project Management, ISPM 2021

作者： Wang, Yongxiang Liao, Ting School of Civil Engineering and Architecture East China Jiaotong University Jiangxi Nanchang330013 China

ISBN: (纸本)9781921712777

To enhance the veracity of risk measurement on deep foundation pit construction of metro station, considering the impact of multi-factors mutual coupling and subjectivity action on traditional methods of danger degree measurement, a combined model of Structural Equation Model (SEM) and Monte Carlo Method (MC) is applied to assess the safety of deep foundation construction of metro station. First, the risk degree measurement index system was established from the four aspects of foundation pit support, foundation pit excavation, dewatering-drainage and surrounding environment, weights of risk factors were calculated by the SEM, and the key risk factors were identified. then, based on the date distribution characteristics of risk factors, the analog values of potential factors were calculated by the MC method. Finally, the risk degree was obtained in combination with accident consequence degree and the weights of risk factors, and was applied in the judgment of risk levels. the risk degree measurement method was applied to the Shuanggang Station of Nanchang Metro. the result shows that the risk level of the deep foundation pit of the subway station is level three, and the main risk indicator that affect the safety of construction is the excavation of deep foundation pit, the direct influence factor is technical parameter of excavation. the project implementation results shows that this method can reliably measure the risks of deep foundation pit construction of metro stations. © ISPM *** right reserved.

关键词： Monte Carlo methods

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When industry meets Education 4.0: What do Computer Science companies need from Higher Education? 21

When industry meets Education 4.0: What do Computer Science ...

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9th International conference on Technological Ecosystems for Enhancing Multiculturality (TEEM)

作者： Iniesto, Francisco Sargent, Julia Rienties, Bart Llorens, Ariadna Adam, Araceli Herodotou, Christothea Ferguson, Rebecca Muccini, Henry Open Univ Inst Educ Technol London England Univ Politecn Cataluna Polytech Sch Engn Barcelona Spain Univ Politecn Cataluna Inst Educ Sci Barcelona Spain Univ Aquila Informat Engn Comp Sci & Math Laquila Italy

ISBN: (纸本)9781450390668

Education 4.0 emphasises the development of skills and competences necessary in a modern workplace. In this paper, we explored what these Education 4.0 skills look like through exploring the opinions of industry professionals in the Computer Science (CS) sector. A series of focus groups involving CS companies from across Europe were used to identify the skills required and the current gaps in training for CS graduates. the two main gaps identified by companies were graduates' lack of soft skills and challenges to applying theoretical knowledge to different practical contexts. Strengths identified included good knowledge of programming and interacting with clients and customers on a technical level. Amongst the suggested ways for addressing these gaps were a close collaboration between industry and academia through company placements and opportunities for project-based learning in higher education.

关键词： engineering education Education 4.0 graduate students skills computer science employers companies

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Smart prediction for refactorings in the software test code 21

Smart prediction for refactorings in the software test code

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35th Brazilian Symposium on software engineering, SBES 2021, held in conjunction with the Brazilian conference on software: theory and Practice, CBSoft 2021

作者： Martins, Luana Bezerra, Carla Costa, Heitor MacHado, Ivan Federal University of Bahia Bahia Brazil Federal University of Ceará Ceará Brazil Federal University of Lavras Lavras Brazil

ISBN: (纸本)9781450390613

Test smells are bad practices to either design or implement a test code. their presence may reduce the test code quality, harming the software testing activities, primarily from a maintenance perspective. therefore, defining strategies and tools to handle test smells and improve the test code quality is necessary. State-of-the-art strategies encompass automated support mainly based on hard thresholds of rules, static and dynamic metrics to identify the test smells. Such thresholds are subjective to interpretation and may not consider the complexity of the software projects. Moreover, they are limited as they do not automate test refactoring but only count on developers' expertise and intuition. In this context, a technique that uses historical implicit or tacit data to generate knowledge could assist the identification and refactoring of test smells. this study aims to establish a novel approach based on machine learning techniques to suggest developers refactoring strategies for test smells. As an expected result, we could understand the applicability of the machine learning techniques to handle test smells and a framework proposal that helps developers in decision-making regarding the refactoring of test smells. © 2021 ACM.

关键词： software testing

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software engineering taxonomy reviews 4

Software engineering taxonomy reviews

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4th International conference on Electrical, Telecommunication and Computer engineering, ELTICOM 2020

作者： Mubarakah, Naemah Soeharwinto Faculty of Engineering Dept. of Electrical Engineering Medan Indonesia

ISBN: (纸本)9781728188706

there is a lack of clarity when discussing taxonomies especially in the field of software engineering. the doubt encourages the writing of software engineering taxonomy paper with the aim of clarifying the applied terminologies. the taxonomic hierarchy plays a major role in regulating knowledge based concepts. Taxonomy is a hierarchical structure based on internal data to classify information. Taxonomy itself has a lot of branches. software engineering taxonomies are defined based on the evaluation of interrelations terms in document collections. Mapping software engineering needs to be done to analyze data in taxonomic development. © 2020 IEEE.

关键词： Taxonomies

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