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检索条件"任意字段=18th International Conference on Software Engineering and Knowledge Engineering"

共 35587 条记录，以下是571-580 订阅

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MalWuKong: Towards Fast, Accurate, and Multilingual Detection of Malicious Code Poisoning in OSS Supply Chains 38

MalWuKong: Towards Fast, Accurate, and Multilingual Detectio...

引用

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

作者： Li, Ningke Wang, Shenao Feng, Mingxi Wang, Kailong Wang, Meizhen Wang, Haoyu Huazhong Univ Sci & Technol Wuhan Peoples R China

ISBN: (纸本)9798350329964

In the face of increased threats within software registries and management systems, we address the critical need for effective malicious code detection. In this paper, we propose an innovative approach that integrates source code slicing, inter-procedural analysis, and cross-file inter-procedural analysis, thereby enhancing the detection precision and reducing false positives. this approach has been encapsulated within a multi-analysis-based framework for automatic detection of malicious code in real-world software packages. In its application to major third-party software registries like PyPI and NPM, our framework has proven effective, identifying 130 malicious packages from a total of 169,640 monitored over a continuous period of five weeks. this work advances the current state-of-the-art solution to malicious code detection, demonstrating significant practical impact in strengthening the software supply chain defense.

关键词： Malware Detection software Supply Chain Security Security Tools

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Addressing Today’s software Risks Requires an Assurance Educated Workforce 28

Addressing Today’s Software Risks Requires an Assurance Edu...

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28th World Multi-conference on Systemics, Cybernetics and Informatics, WMSCI 2024

作者： Woody, Carol S. Software Engineering Institute Carnegie Mellon University 4500 Fifth Avenue PittsburghPA15213-2612 United States

ISBN: (纸本)9781950492794

A noticeable gap exists in the current acquisition and engineering workforce’s knowledge, skills, and support resources needed to address software and supply chain risk. the growing reliance on software to handle system functionality and the exponential increase in cyber attacks has increased the need for those charged with software assurance to establish that all of the software used within an acquisition will function as intended and be free from vulnerabilities that create gaps in cybersecurity. However, acquirers, developers, program managers, system engineers, and decision makers typically lack the knowledge for doing so. Determining who should be trained and how they should be trained has been an ongoing discussion for several years. this paper summarizes the current efforts underway to address gaps based on recent publications and panel discussions held by the software Assurance Supply Chain (SSCA) Forum. © 2024 by the international Institute of Informatics and Systemics. All rights reserved.

关键词： Assurance Education software Assurance software Risk Supply Chain Risk

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iSMELL: Assembling LLMs with Expert Toolsets for Code Smell Detection and Refactoring 24

iSMELL: Assembling LLMs with Expert Toolsets for Code Smell ...

引用

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

作者： Wu, Di Mu, Fangwen Shi, Lin Guo, Zhaoqiang Liu, Kui Zhuang, Weiguang Zhongl, Yuqi Zhang, Li Beihang Univ Beijing Peoples R China Chinese Acad Sci Inst Software Beijing Peoples R China Huawei Software Engn Applicat Technol Lab Shenzhen Peoples R China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Detecting and refactoring code smells is challenging, laborious, and sustaining. Although large language models have demonstrated potential in identifying various types of code smells, they also have limitations such as input-output token restrictions, difficulty in accessing repository-level knowledge, and performing dynamic source code analysis. Existing learning-based methods or commercial expert toolsets have advantages in handling complex smells. they can analyze project structures and contextual information in-depth, access global code repositories, and utilize advanced code analysis techniques. However, these toolsets are often designed for specific types and patterns of code smells and can only address fixed smells, lacking flexibility and scalability. To resolve that problem, we propose iSMELL, an ensemble approach that employs various code smell detection toolsets via Mixture of Experts (MoE) architecture for comprehensive code smell detection, and enhances the LLMs with the detection results from expert toolsets for refactoring those identified code smells. First, we train a MoE model that, based on input code vectors, outputs the most suitable expert tool for identifying each type of smell. then, we select the recommended toolsets for code smell detection and obtain their results. Finally, we equip the prompts with the detection results from the expert toolsets, thereby enhancing the refactoring capability of LLMs for code with existing smells, enabling them to provide different solutions based on the type of smell. We evaluate our approach on detecting and refactoring three classical and complex code smells, i.e., Refused Bequest, God Class, and Feature Envy. the results show that, by adopting seven expert code smell toolsets, iSMELL achieved an average F1 score of 75.17% on code smell detection, outperforming LLMs baselines by an increase of 35.05% in F1 score. We further evaluate the code refactored by the enhanced LLM. the quantitative and human eval

关键词： Measurement Learning systems Codes Source coding Scalability Large language models Feature extraction Vectors software software engineering

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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...

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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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Group-based control of large-scale micro-robot swarms with on-board Physical Finite-State Machines 18

Group-based control of large-scale micro-robot swarms with o...

引用

IEEE 18th international conference on Automation Science and engineering (IEEE CASE)

作者： Li, Siyu Zefran, Milos Paprotny, Igor Univ Illinois Dept Elect & Comp Engn Chicago IL 60607 USA

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

An important problem in microrobotics is how to control a large group of microrobots with a global control signal. this paper focuses on controlling a large-scale swarm of MicroStressBots with on-board physical finite-state machines. We introduce the concept of group-based control, which makes it possible to scale up the swarm size while reducing the complexity both of robot fabrication as well as swarm control. We prove that the group-based control system is locally accessible in terms of the robot positions. We further hypothesize based on extensive simulations that the system is globally controllable. A nonlinear optimization strategy is proposed to control the swarm by minimizing control effort. We also propose a probabilistically complete collision avoidance method that is suitable for online use. the paper concludes with an evaluation of the proposed methods in simulations.

关键词： Fabrication Uncertainty Computer aided software engineering Automata Probabilistic logic Controllability Numerical models

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A Transformer-based Approach for Augmenting software engineering Chatbots Datasets 24

A Transformer-based Approach for Augmenting Software Enginee...

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18th ACM/IEEE international Symposium on Empirical software engineering and Measurement, ESEM 2024

作者： Abdellatif, Ahmad Badran, Khaled Costa, Diego Elias Shihab, Emad University of Calgary Calgary Canada Concordia University Montreal Canada

ISBN: (纸本)9798400710476

Background: the adoption of chatbots into software development tasks has become increasingly popular among practitioners, driven by the advantages of cost reduction and acceleration of the software development process. Chatbots understand users' queries through the Natural Language Understanding component (NLU). To yield reasonable performance, NLUs have to be trained with extensive, high-quality datasets, that express a multitude of ways users may interact with chatbots. However, previous studies show that creating a high-quality training dataset for software engineering chatbots is expensive in terms of both resources and time. Aims: therefore, in this paper, we present an automated transformer-based approach to augment software engineering chatbot datasets. Method: Our approach combines traditional natural language processing techniques with the BART transformer to augment a dataset by generating queries through synonym replacement and paraphrasing. We evaluate the impact of using the augmentation approach on the Rasa NLU's performance using three software engineering datasets. Results: Overall, the augmentation approach shows promising results in improving the Rasa's performance, augmenting queries with varying sentence structures while preserving their original semantics. Furthermore, it increases Rasa's confidence in its intent classification for the correctly classified intents. Conclusions: We believe that our study helps practitioners improve the performance of their chatbots and guides future research to propose augmentation techniques for SE chatbots. © 2024 ACM.

关键词： Semantics

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A dynamic programming-based slot reservation method for non-clear containers in automated container terminals 18

A dynamic programming-based slot reservation method for non-...

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IEEE 18th international conference on Automation Science and engineering (IEEE CASE)

作者： Zhu, Jiyue Lee, Wei Lian William Qin, Wei Shanghai Jiao Tong Univ Sch Mech Engn Dept Ind Engn & Management Shanghai Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Stowage planning is one of the most important stages in management of container terminals and depends the sequence of containers to be loaded on the ship. For non-clear containers, which are absence from the terminal, their slots will be selected manually by stowage planners, making it a time-consuming job. In order to optimize the slot reservation problem of non-clear containers, a mathematical model based on the knapsack problem is constructed. A Stack Selection Algorithm based on dynamic programming is proposed to solve the model. Further case study of Yangshan automatic container terminal demonstrates that the method can solve the non-clear containers reservation problem in a very short time, and the results are better than traditional heuristic approaches.

关键词： Computer aided software engineering Automation Heuristic algorithms Containers Mathematical models Planning Dynamic programming

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Optimising the supply and demand decisions in high-end equipment manufacturing based on Stackelberg game 18

Optimising the supply and demand decisions in high-end equip...

引用

IEEE 18th international conference on Automation Science and engineering (IEEE CASE)

作者： Han, Tiaojuan Lu, Jianfeng Zhang, Hao Tongji Univ CIMS Res Ctr Shanghai 201804 Peoples R China

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

High-end equipment is manufactured using a "main manufacturer-supplier" mode. the supply-demand relationship of high-end equipment involves benefit conflicts among the customer, the main manufacturer, and multiple suppliers, so transaction decisions become very complicated. Traditional optimisation methods are inadequate at revealing the interactions among multiple stakeholders. In this study, based on the transaction process of high-end equipment manufacturing, two correlated Stackelberg game models, namely, "main manufacturer-customer" and "main manufacturer-supplier," are constructed and their Nash equilibria are solved to maximize the profit of each stakeholder. the effects of various parameters on the decision variables of each stakeholder are analyzed through numerical simulation.

关键词： Costs Supply and demand Computer aided software engineering Automation Optimization methods Games Numerical simulation

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FBG Sensor Design and Analysis for Early Detection of Cancer 18

FBG Sensor Design and Analysis for Early Detection of Cancer

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18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Sharan, S.C. Dhruva, H.K. Mary Anitha, T. Roy, Neil Sharan, Preeta Madhwesha Moudgalya, R. The Oxford College of Engineering Dept. of Computer Science and Engineering Bangalore India The Oxford College of Engineering Dept. of Mca Bangalore India Delhi Technological University Dept. of Computer Science and Engineering New Delhi India The Oxford College of Engineering Dept. of Electronics and Communication Engineering Bangalore India The Oxford College of Engineering Dept. of Science and Humanities Bangalore India

ISBN: (纸本)9789380544519

Several of the current procedures for detecting cancer, such as mammography, ultrasound, MRI, and biopsy, are either expensive, painful, intrusive, or have limitations in accuracy and sensitivity. As a result, there is a need for a simple, noninvasive, and cost-effective tool for detecting cancer at an early stage. Fiber Bragg grating (FBG) sensors offer a wide range of uses in primary care and biomedical applications for intelligent sensing. Furthermore, fiber-optic FBGs have several benefits that set them apart. the most noteworthy of these applications, of course, are incredibly valuable human health indicators such as blood pressure, heart rate, and body temperature. Temperature and blood pressure vary depending on a person's physical, involuntary, nervous, and mental state. therefore, measuring vital parameters, especially temperature can help in the early identification of symptoms of a disease. Research suggests that temperature variation is observed in cancerous cells (breast, cervix, and blood vessels). FBGs can be utilized as thermal sensors to measure temperature changes with great sensitivity and precision. FBG sensors also face some challenges, such as low signal-to-noise ratio, cross-sensitivity, and environmental interference. therefore, optimizing the Q factor of FBG sensors is crucial for improving their performance and reliability for cancer identification. In the current study, an optimized FBG sensor was designed and simulated. the average Q-factor obtained in 244.26. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Blood cancer FBG Fiberoptic Hela cells MCF-7 cells modulation OptiGrating SMF

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Dynamic Scoring Code Token Tree: A Novel Decoding Strategy for Generating High-Performance Code 24

Dynamic Scoring Code Token Tree: A Novel Decoding Strategy f...

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

作者： Qu, Muzi Liu, Jie Kang, Liangyi Wang, Shuai Ye, Dan Huang, Tao Chinese Acad Sci Inst Software Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Key Lab Syst Software Beijing 100190 Peoples R China Chinese Acad Sci State Key Lab Comp Sci Inst Software Beijing 100190 Peoples R China Univ Chinese Acad Sci Nanjing 211135 Peoples R China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Within the realms of scientific computing, large-scale data processing, and artificial intelligence-powered computation, disparities in performance, which originate from differing code implementations, directly influence the practicality of the code. Although existing works tried to utilize code knowledge to enhance the execution performance of codes generated by large language models, they neglect code evaluation outcomes which directly refer to the code execution details, resulting in inefficient computation. To address this issue, we propose DSCT-Decode, an innovative adaptive decoding strategy for large language models, that employs a data structure named 'Code Token Tree' (CTT), which guides token selection based on code evaluation outcomes. DSCT-Decode assesses generated code across three dimensions-correctness, performance, and similarity-and utilizes a dynamic penalty-based boundary intersection method to compute multi-objective scores, which are then used to adjust the scores of nodes in the CTT during backpropagation. By maintaining a balance between exploration, through token selection probabilities, and exploitation, through multi-objective scoring, DSCT-Decode effectively navigates the code space to swiftly identify high-performance code solutions. To substantiate our framework, we developed a new benchmark, big-DS-1000, which is an extension of DS-1000. this benchmark is the first of its kind to specifically evaluate code generation methods based on execution performance. Comparative evaluations with leading large language models, such as CodeLlama and GPT-4, show that our framework achieves an average performance enhancement of nearly 30%. Furthermore, 30% of the codes exhibited a performance improvement of more than 20%, underscoring the effectiveness and potential of our framework for practical applications.

关键词： Code Generation Large Language Model Performance Optimization

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