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Int. J. Softw. Informatics最新文献

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Time Series Data Cleaning under Multi-Speed Constraints 多速度约束下的时间序列数据清理
Pub Date : 1900-01-01 DOI: 10.21655/IJSI.1673-7288.00239
Fei Gao, Shaoxu Song, Jianmin Wang
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引用次数: 3
Transfer-based Adversarial Attack with Rectified Adam and Color Invariance 基于纠偏亚当和颜色不变性的转移对抗攻击
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00283
Jia Ding, Zhiwu Xu
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引用次数: 0
Image Style Transfering Based on StarGAN and Class Encoder 基于StarGAN和类编码器的图像样式传输
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00267
Xinzheng Xu, Jianying Chang, Shifei Ding
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引用次数: 0
Preface to the Special Issue on Robust Machine Learning for Open Scenarios 开放场景鲁棒机器学习特刊前言
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00265
Enhong Chen, Yufeng Li, Q. Zou
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引用次数: 0
Smooth Intervention Model of Individual Interactive Behavior 个体互动行为的平滑干预模型
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00256
Xinyu Liu, Zhaohui Zhang, Ziming Wei, Pengwei Wang
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引用次数: 0
AlphaQO: Robust Learned Query Optimizer AlphaQO:稳健学习查询优化器
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00275
Xiang Yu, Chengliang Chai, Xinning Zhang, N. Tang, Ji Sun, Guoliang Li
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引用次数: 0
Multi-path Back-propagation Method for Neural Network Verification 神经网络验证的多路径反向传播方法
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00281
Ye Zheng, Xiaomu Shi, Jiaxiang Liu
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引用次数: 0
Deep Learning Test Optimization Method Using Multi-objective Optimization 基于多目标优化的深度学习测试优化方法
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00282
Yanzhou Mu, Zan Wang, Xiang Chen, Junjie Chen, Jingke Zhao, Jianmin Wang
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引用次数: 2
Towards an Interoperable Metamodel Suite: Size Assessment as One Input 迈向可互操作的元模型套件:规模评估作为一个输入
Pub Date : 1900-01-01 DOI: 10.13039/501100000923
B. Henderson-Sellers, M. A. Qureshi, Cesar Gonzalez-Perez
In recent years, many metamodels have been introduced in the software engi- neering literature and standards. These metamodels vary in their focus across, for example, process, product, organizational and measurement aspects of software development and have typically been developed independently of each other with shared concepts being only ac- cidental. There is thus an increasing concern in the standards communities that possible con∞icts of structure and semantics between these various metamodels will hinder their widespread adoption. The complexity of these metamodels has also increased signiflcantly and is another barrier in their appreciation. This complexity is compounded when more than one metamodel is used in the lifecycle of a software project. Therefore there is a need to have interoperable metamodels. As a flrst step towards engendering interoperability and/or possible mergers between metamodels, we examine the size and complexity of various meta- models. To do this, we have used the Rossi and Brinkkemper metrics-based approach to evaluate the size and complexity of several standard metamodels including UML 2.3, BPMN 2.0, ODM, SMM and OSM. The size and complexity of these metamodels is also compared with the previous version of UML, BPMN and Activity diagrams. The comparatively large sizes of BPMN 2.0 and UML 2.3 suggest that future integration with these metamodels might be more di-cult than with the other metamodels under study (especially ODM, SSM and OSM).
近年来,软件工程文献和标准中引入了许多元模型。例如,这些元模型在软件开发的过程、产品、组织和度量方面的关注点各不相同,并且通常是相互独立开发的,共享的概念只是偶然的。因此,在标准社区中,越来越多的人担心这些不同元模型之间可能存在的结构和语义冲突将阻碍它们的广泛采用。这些元模型的复杂性也显著增加,这是对它们的欣赏的另一个障碍。当在软件项目的生命周期中使用多个元模型时,这种复杂性会变得更加复杂。因此,需要具有可互操作的元模型。作为产生互操作性和/或元模型之间可能合并的第一步,我们检查了各种元模型的大小和复杂性。为了做到这一点,我们使用Rossi和Brinkkemper基于度量的方法来评估几个标准元模型的大小和复杂性,包括UML 2.3、BPMN 2.0、ODM、SMM和OSM。这些元模型的大小和复杂性也与以前版本的UML、BPMN和活动图进行了比较。BPMN 2.0和UML 2.3相对较大的规模表明,与正在研究的其他元模型(尤其是ODM、SSM和OSM)相比,未来与这些元模型的集成可能更加困难。
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引用次数: 6
Minimal-unsatisfiable-core-driven Local Explainability Analysis for Random Forest 随机森林的最小-不满意核驱动局部可解释性分析
Pub Date : 1900-01-01 DOI: 10.21655/ijsi.1673-7288.00280
Shucen Ma, Jianqi Shi, Yanhong Huang, S. Qin, Zhé Hóu
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引用次数: 1
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Int. J. Softw. Informatics
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