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检索条件"任意字段=IEEE International Conference on Software - Science, Technology and Engineering 2005"

共 39461 条记录，以下是61-70 订阅

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Assessing software Interface Quality in the Humanmachine Interaction Systems 6

Assessing Software Interface Quality in the Humanmachine Int...

引用

6th international Youth conference on Radio Electronics, Electrical and Power engineering, REEPE 2024

作者： Tarkhov, Sergey V. Tarkhova, Lyaylya M. Minasova, Anastasia Sh. Ufa University of Science and Technology Ufa Russia Bashkir State Agrarian University Ufa Russia Bauman Moscow State Technical University Moscow Russia

ISBN: (纸本)9798350382891

This paper considers issues of conducting research to assess the software interface quality level. The list of criteria for assessing the interface quality is determined in accordance with the generally accepted international standards in software engineering. A method for assessing the software interfaces was developed making it possible to determine their quality degree according to parameters and criteria chosen by the experts. Quality assessment of the human-machine interaction interfaces in the software application products was carried out using the Ishikawa diagram. Method for assessing the software interface quality involves introduction of the matrix method in processing hierarchical structure of the evaluation indicators imported from the Ishikawa diagram construction toolkit. Mathematical model for calculating the quality integral indicator for a software interface was developed. The quality level was determined based on convolution of the parameters and indicators-controlled values, which were expertly assessed and qualimetrically determined. Results calculation and visualization were performed using the spreadsheets. An example of assessing the software interface using the developed method are provided. The prospects for using the developed method in assessing the software interface quality and determining a list of recommendations for adjusting and improving the software product are noted. © 2024 ieee.

关键词： software testing

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Contributing Back to the Ecosystem: A User Survey of NPM Developers 22

Contributing Back to the Ecosystem: A User Survey of NPM Dev...

引用

22nd ieee/ACIS international conference on software engineering Research, Management and Applications, SERA 2024

作者： Wattanakriengkrai, Supatsara Treude, Christoph Kula, Raula Gaikovina Nara Institute of Science and Technology Japan Singapore Management University Singapore Singapore

ISBN: (纸本)9798350391343

With the rise of the library ecosystem (such as NPM for JavaScript and PyPI for Python), a developer has access to a multitude of library packages that they can adopt as dependencies into their application. Prior work has found that these ecosystems form a complex web of dependencies, where sustainability issues of a single library can have widespread network effects. Due to the Open Source software (OSS) nature of third party libraries, there are rising concerns with the sustainability of these libraries. In a survey of 49 developers from the NPM ecosystem, we find that developers are more likely to maintain their own packages rather than contribute to the ecosystem. Our results opens up new avenues into tool support and research into how to sustain these ecosystems, especially for developers that depend on these libraries. We have made available the raw results of the survey at https://***/2p8sdmr3. © 2024 ieee.

关键词： software packages

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Accuracy Prediction of Ensemble Deep Learning Model through software Defect Prediction 2

Accuracy Prediction of Ensemble Deep Learning Model through ...

引用

2nd international conference on Data science and Information System, ICDSIS 2024

作者： Charan, S. Sinha, Sumana Sujan, S.M. Nayak, Ullal Akshatha Nitte Meenakshi Institute Of Technology Information Science And Engineering Bangalore India

ISBN: (纸本)9798350381665

Defect detection and repair are critical to the performance and dependability of modern software development. To evaluate large software repositories and find errors early in the development process, this study proposes a novel deep learning (DL) method for software defect prediction (SDP). This work aims to methodically ascertain, and evaluate MLP, CNN, and LSTM models independently and finally ensemble it for better SDP. We examine the MLP, CNN, LSTM individually and compare them with the ensemble model. We achieved an accuracy of 0.78, indicating promising results for defect prediction in software development in imbalanced data set. © 2024 ieee.

关键词： Long short-term memory

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B⁴: Towards Optimal Assessment of Plausible Code Solutions with Plausible Tests 24

B<SUP>4</SUP>: Towards Optimal Assessment of Plausible Code ...

引用

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

作者： Chen, Mouxiang Liu, Zhongxin Tao, He Hong, Yusu Lo, David Xia, Xin Sun, Jianling Zhejiang Univ State Key Lab Blockchain & Data Secur Hangzhou Peoples R China Zhejiang Univ Hangzhou Peoples R China Singapore Management Univ Singapore Singapore Hangzhou High Tech Zone Binjiang Inst Blockchain Hangzhou Peoples R China

ISBN: (纸本)9798400712487

Selecting the best code solution from multiple generated ones is an essential task in code generation, which can be achieved by using some reliable validators (e.g., developer-written test cases) for assistance. Since reliable test cases are not always available and can be expensive to build in practice, researchers propose to automatically generate test cases to assess code solutions. However, when both code solutions and test cases are plausible and not reliable, selecting the best solution becomes challenging. Although some heuristic strategies have been proposed to tackle this problem, they lack a strong theoretical guarantee and it is still an open question whether an optimal selection strategy exists. Our work contributes in two ways. First, we show that within a Bayesian framework, the optimal selection strategy can be defined based on the posterior probability of the observed passing states between solutions and tests. The problem of identifying the best solution is then framed as an integer programming problem. Second, we propose an efficient approach for approximating this optimal (yet uncomputable) strategy, where the approximation error is bounded by the correctness of prior knowledge. We then incorporate effective prior knowledge to tailor code generation tasks. Both theoretical and empirical studies confirm that existing heuristics are limited in selecting the best solutions with plausible test cases. Our proposed approximated optimal strategy B-4 significantly surpasses existing heuristics in selecting code solutions generated by large language models (LLMs) with LLM-generated tests, achieving a relative performance improvement by up to 50% over the strongest heuristic and 246% over the random selection in the most challenging scenarios. Our code is publicly available at https://***/ZJU-CTAG/B4.

关键词： Code Generation software engineering Large Language Models

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Electromagnetic-Thermal-Stress Multiphysics Modeling of a TD-LTE Triple Band Patch Antenna

Electromagnetic-Thermal-Stress Multiphysics Modeling of a TD...

引用

2024 ieee international conference on Computational Electromagnetics, ICCEM 2024

作者： Liao, Zhengwen Chen, Yifan Liang, Ruihua Zhu, Jian Wan, Ting Nanjing University of Posts and Telecommunications Department of Communication Engineering Nanjing China

ISBN: (纸本)9798350383317

In this work, A multi-physics field simulation method based on the finite element method is developed for reliability analysis of multi-band antennas. The Multiphysics field simulation describes the multidisciplinary characteristics of the multiband antenna such as electrical, thermal and mechanical. To confirm that the method is accurate, we apply the proposed method to the electrical-thermal-stress simulation of a TD-LTE triple band patch antenna and compare the results with the commercial software COMSOL. © 2024 ieee.

关键词： Finite element method

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Combining Coverage and Expert Features with Semantic Representation for Coincidental Correctness Detection 24

Combining Coverage and Expert Features with Semantic Represe...

引用

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

作者： Xie, Huan Lei, Yan Li, Maojin Yan, Meng Zhang, Sheng Chongqing Univ Sch Big Data & Software Engn Chongqing Peoples R China Peng Cheng Lab Shenzhen Peoples R China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Coincidental correctness (CC) can be misleading for developers because it gives the impression that the code is functioning correctly when there are hidden faults. To mitigate the negative impacts of CC test cases, extensive research has been conducted on their detection, employing either coverage-based or expert-based features. These studies have yielded promising results. Coverage and expert features each provide unique insights into program execution, yet the literature has not fully explored the combined potential of these two feature sets to enhance the detection of CC. Additionally, the rich semantics of the test code and focal method have not been fully utilized. Therefore, we propose to build a unified model, CORE, that integrates coverage and expert features with semantic representations of test and focal methods to improve the detection of CC test cases. We make a comprehensive evaluation with six state-of-the-art baselines on the widely-used Defects4J benchmark. The experimental results show that CORE outperforms the baselines in terms of CC detection accuracy, with a substantial improvement (i.e., 40% improvement on average in terms of F1 score). Then, we conduct the ablation experiment to show that the coverage, expert, and semantics contribute to CORE. CORE can also improve the effectiveness of spectrum-based and mutation-based fault localization performance (e.g., 50% improvements for spectrum-based formula Dstar and 44% improvements for mutation-based method MUSE under relabeling strategy).

关键词： Coincidental Correctness Fault Localization Multiple Features Semantic Representation Deep Learning

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Key Logger for Recording the Keystroke of the Targeted Machine 1

Key Logger for Recording the Keystroke of the Targeted Machi...

引用

1st ieee international conference on Computing and Data science, ICCDS 2024

作者： Gnanavel, S. Sreekrishna, M. Shivaramakrishnan, P. Yaswanth, R. Gopika, G.S. Supriya, S. SRM Institute of Science and Technology Faculty of Engineering and Technology Dept of Computing Technologies Kattankulathur603203 India Sathyabama Institute of Science and Technology Dept of Computer Science Engineering Chennai600119 India

ISBN: (纸本)9798350365337

In the recent digital era security has become more challenging. There is a plethora of ways to find solution to ensure monitor the system and provide required security. Key logger is one of the cyber attacks which record the key strokes of the targeted systems or devices from the host person. In other words, the program retrieves vital information such as login credentials, passwords and other sensitive information. There are many types of key logger, software key loggers is one of the key logger type which use software applications to collect the information from the targeted machine to host machine. It is indeed difficult to trace the software key logger because it runs in background without any noticeable signs. However, there are some signs like network traffic and unexpected activity. This paper concentrates on the implementation of key logger and its observation using python file, JavaScript file and etc. © 2024 ieee.

关键词： Network security

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On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities 24

On the Effectiveness of Function-Level Vulnerability Detecto...

引用

44th ACM/ieee international conference on software engineering, ICSE 2024

作者： Li, Zhen Wang, Ning Zou, Deqing Li, Yating Zhang, Ruqian Xu, Shouhuai Zhang, Chao Jin, Hai Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hong Kong Jin YinHu Laboratory Wuhan China School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China University of Colorado Colorado Springs Department of Computer Science Colorado Springs Colorado United States Institute for Network Sciences and Cyberspace Tsinghua University Beijing China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798400702174

software vulnerabilities are a major cyber threat and it is important to detect them. One important approach to detecting vulnerabilities is to use deep learning while treating a program function as a whole, known as function-level vulnerability detectors. However, the limitation of this approach is not understood. In this paper, we investigate its limitation in detecting one class of vulnerabilities known as inter-procedural vulnerabilities, where the to-be-patched statements and the vulnerability-triggering statements belong to different functions. For this purpose, we create the first Inter -Procedural Vulnerability Dataset (InterPVD) based on C/C++ open-source software, and we propose a tool dubbed VulTrigger for identifying vulnerability-triggering statements across functions. Experimental results show that VulTrigger can effectively identify vulnerability-triggering statements and inter-procedural vulnerabilities. Our findings include: (i) inter-procedural vulnerabilities are prevalent with an average of 2.8 inter-procedural layers;and (ii) function-level vulner-ability detectors are much less effective in detecting to-be-patched functions of inter-procedural vulnerabilities than detecting their counterparts of intra-procedural vulnerabilities. © 2024 ACM.

关键词： Open source software

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RSAGEL: A Hybrid Graph Neural Network Based Intrusion Detection Model for software Defined Networking 9

RSAGEL: A Hybrid Graph Neural Network Based Intrusion Detect...

引用

9th international conference on Information science, Computer technology and Transportation, ISCTT 2024

作者： Zhang, Yue Liu, Wanxiao Chen, Jue Ma, Yurui College of Electronic and Electric Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9798350388435

software Defined Networking (SDN) has emerged as a revolutionary network architecture aimed at surpassing the constraints inherent in traditional network infrastructures. As SDN adoption increases, it brings additional complexities to the domain of network security. This study focuses on the detection of anomalous behaviors and the classification of various network attack types within the SDN *** hybrid model Residual-GraphSAGE-LSTM(RSAGEL) introduced in this paper provides a robust approach to address intrusion detection challenges in SDN environments. The advantages of this model are utilized to effectively process graph structured data, achieving an accuracy 4.5% higher than traditional deep learning algorithms on the InSDN dataset. ©2024 ieee.

关键词： Network intrusion

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Design of a Magnetic Loop Antenna Suitable for High Frequency Communication in Moving Vehicle

Design of a Magnetic Loop Antenna Suitable for High Frequenc...

引用

2024 ieee international conference on Computational Electromagnetics, ICCEM 2024

作者： Liu, Kewei Zhao, Yingyan Cao, Qunsheng College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350383317

In this paper, a near vertical incident skywave (NVIS) shortwave magnetic loop antenna suitable for engineering applications is proposed and designed, and the effects of its structural form, size, and impedance matching on antenna performance is analyzed. The antenna has been successfully applied in practical vehicle systems with good results. © 2024 ieee.

关键词： Loop antennas

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