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International Symposium on Information Engineering and Electronic Commerce, IEEC

作者： Lizhi Cai Juan Zhang Zhenyu Liu Shanghai Key Laboratory of Computer Software Testing and Evaluation Shanghai China School of Computer Engineering and Science Shanghai University Shanghai China

A Petri Net is a graphical and mathematical modeling approach used to describe the transition of states for an information system. This paper presents a novel technique to generating test cases using a Colored Petri Net (CPN) model. The state space of a model based on CPN provides a solid basis for test cases generation in a form that can be easily manipulated. This technique is based on three testing coverage criteria according to the state space. The advantage of this approach is that the correctness of the specification based on CPN can be validated by simulation tools and the state space can be also generated by state space tools. The case for vending machine illustrates the effectiveness of this method.

关键词： software testing System testing State-space methods Mathematical model Solid modeling Information systems Formal specifications software systems Laboratories Costs

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Securing personal health records in clouds by enforcing sticky policies

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Telkomnika - Indonesian Journal of Electrical Engineering 2013年第4期11卷 2200-2208页

作者： Leng, Chunxia Yu, Huiqun Wang, Jingming Huang, Jianhua Department of Computer Science and Engineering East China University of Science and Technology Shanghai 200237 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai 201112 China School of Computer and Information Engineering Chuzhou University Anhui 239012 China

The personal health records (PHR) always contain much health-related privacy information in different categories. When storing the PHR data in the cloud, the PHR owner losescontrol to the sensitive information and is confronted with potential privacy exposure. In this paper, we propose a scheme to enable the protection of the PHR data hosted in the cloud. It not only supports that the data access can be fine-grained and base on the privacy policies specified by the PHR owner, but also affords an effective encryption mechanism and flexible key management approach to enforce the privacy policies sticky to the PHR data. © 2013 Universitas Ahmad Dahlan.

关键词： Cryptography

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CRCS: Learning Synergistic Cascade Correlation for Microscopic Cascade Prediction

CRCS: Learning Synergistic Cascade Correlation for Microscop...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Huacheng Li Chunhe Xia Tianbo Wang Haopeng Zhao Key Laboratory of Beijing Network Technology Beihang University Beijing China Key Laboratory of Beijing Network Technology Beijing China School of Cyber Science and Technology Beihang University Beijing China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China

Information diffusion prediction is the basis of many fundamental tasks, such as social recommendation and community detection. Currently, most researchers infer user correlation based on cascade records to predict future infected users. However, they only consider whether the infected users at each location are correctly predicted, ignoring the semantic differences between users who participate in the retweets of similar content and other users. This naturally leads to learning biased user features. In this paper, we compute semantic relevance between two different cascades (e.g., c m and c n ) based on user coincidence and develop the cascade correlation graph (CCG) to learn user features. Afterward, we devise a position-independent sequence similarity loss (SSL) function combined with an auxiliary predictor to optimize the user encoder. The above two methods make users participating in the relevant cascades more relevant than others. Experiments show that the two methods are effective, and the combination of them can improve performance more significantly.

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A study for extended regular expression-based testing

A study for extended regular expression-based testing

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International Conference on computer and Information Science (ACIS)

作者： Pan Liu Jun Ai Zhenning Jimmy Xu College of Information and Computer Shanghai Business School Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai China School of Reliability and System Engineering Beihang University Beijing China School of business University of Southern Maine USA

ISBN: (纸本)9781509055081

software testing has become an essential activity to guarantee software quality. To reduce the overall cost of software testing, model-based testing has been widely studied in the past two decades and Finite State Machine (FSM) is used to build the model of software behaviors. However, due to the inadequacy of the modeling ability of FSM, FSM-based testing cannot be taken as a test oracle to solve all issues in software testing. To improve the modeling capability of the model, a few researchers have proposed using Extended Regular Expressions (ERE) to model software behaviors. This paper reviews the method of the ERE-based testing and presents six modeling rules to convert program codes to the ERE model. Then, a case is adopted to illustrate the process of generating executable paths from the ERE model and the method of designing test cases by those paths. Compared with the traditional graphic traversal method of constructing executable paths from the program, ERE not only has robust modeling capability to describe more types of software behaviors than FSM, but also can be used to construct effective executable paths to detect program errors.

关键词： software software testing Algorithm design and analysis Mathematical model Switches Business

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CFC: a Cascade Forest approach to discover Cancer driver genes using multi-omics data

CFC: a Cascade Forest approach to discover Cancer driver gen...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Lei Zhang Yijing Yang Zhe Wang Dongdong Li Jingping Liu Hai Yang Department of Computer Science and Engineering East China University of Science and Technology Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China Department of Computer Science University of Illinois Urbana-Champaign Champaign Illinois United States of America

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

With the development of next-generation sequencing technology, massive genomic data has been generated, primarily encouraging research on cancer driver genes. Many bioinformatics methods were proposed to identify driver genes. However, the results of driver gene identification a mong these methods show considerable differences. It is still challenging to obtain a comprehensive catalog of cancer drivers. Although current methods have greatly promoted the development of driver genes, few methods can integrate the identification results of existing methods. To solve such problems in cancer driver genes research, we proposed a cascade forest model to discover cancer driver genes(CFC) that can integrate multi-omics data and annotation scores from different cancer driver gene identification algorithms. The proposed method got precise results for 33 cancer types and Pan-cancer. The CFC framework identified 275 driver genes in Pan-cancer, of which 179 were included in the Gold standard. The identified genes were enriched i n t he principal cancer signaling pathways.

关键词： Sequential analysis Annotations Genomics Forestry Data models Bioinformatics Next generation networking

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computer-Aided Formalization of Product Family Models

SSRN

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SSRN 2022年

作者： Liu, Hongbo Wang, Xi Wang, Weiwei School of Computer Engineering and Scinece Shanghai University No.333 Nan Chen Road Baoshan District Shanghai Shanghai200444 China Shanghai Key Laboratory of Computer Software Testing and Evaluating No.333 Nan Chen Road Baoshan District Shanghai200444 China

The software product line enables the rapid construction of software products by reusing core assets. Product family modeling is one of the important activities in software product line engineering, which is a model for managing the variability of the core assets of a product family, and the dominant technique is feature modeling. Feature modeling reflects the software requirements of the whole domain by recording a set of relatively stable features and the relationships between the features, and lacks feature individual requirement analysis. Some approaches provide internal analysis of features, but separate it from the feature model. To deal with the above problems, this paper proposes a systematic approach to formalizing product family models and provides automatic support for the formalization process. The approach takes the initial feature model as the starting point, and examines the consistency of the results with the feature model in the formalization of each feature, and uses this as a basis to guide the evolution of the feature model. A template library is given to provide a set of templates to guide the construction and evolution of the feature model. A library of rules is given to check the consistency of the formal specification of the feature with the feature model. Our approach combines variability modeling with the formal specification of features to obtain an internally consistent product family feature model. © 2022, The Authors. All rights reserved.

关键词： Formal specification

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M-Detr: Multi-Scale Detr for Optical Music Recognition

SSRN

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SSRN 2023年

作者： Luo, Fei Dai, Yifan Fuentes, Joel Ding, Weichao Zhang, Xueqin East China University of Science and Technology Shanghai China Department of Computer Science and Information Technologies Universidad del Bío-Bío Chillán3780000 Chile Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China

As a new paradigm for object detection, DETR (detection transformer) has the ability to associate contextual information, which is very suitable for optical music recognition (OMR). This paper proposes a novel multi-scale detection transformer (M-DETR) for OMR with a multi-scale feature fusion mechanism and improved attention mechanisms. First, the feature fusion mechanism is combined with backbone networks to let the M-DETR network get richer multi-scale information. Then, a key-region attention mechanism is incorporated based on the character that the key information in a score image. Finally, the pre-context attention mechanism enables the network to make better use of the contextual association between recognition targets in music scores. Experiment results show that M-DETR achieves recognition accuracy of 90.6% for 7 typical small-sized notes, which is better than Faster R-CNN and YOLO v5, and the improvement rate is 10.02% compared to the original DETR algorithm. © 2023, The Authors. All rights reserved.

关键词： Object detection

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Eyou: An electronic map-based logistics service system

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Journal of Convergence Information Technology 2012年第14期7卷 206-214页

作者： Liu, Pan Miao, Huaikou Chen, Jianjiao College of Computer Engineering and Science Shanghai Business School Fengpu Road FengXian District Shanghai 201400 China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai 200072 China School of Computer Engineering and Science Shanghai University 149 Yanchang Road 200072 Shanghai China School of Information Science and Engineering Xinjiang University Xinjiang China

The paper describes a project to develop an electronic map-based logistics service system (named as Eyou). It consists of several core components, including a unified portal for searching the goods delivery information from different logistic firms, an electronic map-based interface by encapsulating Baidu map API, and the decision support component for planning the routes of the delivery vehicles in a feasible and cost-effective way. In this article, we describe the website's features and functions, the website's system architecture, a novel shortest path algorithm with time constraint and a case study based on our algorithm. The aim of Eyou is to provide some small-size logistics firms, the online shop owners and the users with three services in the convenient or inexpensive way.

关键词： Websites

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Research on Quality Model for Quantum Simulator software

Research on Quality Model for Quantum Simulator Software

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software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter), ACIS International Winter Conference on

作者： Chao Wang Jingwei Chen JianXin Ge XueZhong Wu QianQian Qu Le Luo Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China QUDOOR Technologies Inc. Hefei China Software Engineering of Computer and Information Engineering College Shanghai Polytechnic University Shanghai China QUDOOR Technologies Inc. School of Physics and Astronomy Sun Yat-Sen University Zhuhai China

In recent years, the demand for arithmetic power from all walks of life is growing, especially the increasing popularity of AIGC, which makes people realize that huge technological progress cannot be made without the support of large arithmetic power. Quantum computing may bring a leap in computing power and become a ”trigger” and “catalyst” to accelerate the development of science and technology innovation, and its technical development trend and application prospects have become a hot issue of concern, and quantum simulators are a very important part of the development process. The development of quantum simulators is a very important part of the process. However, due to the lack of systematic evaluation theories and methods, it is difficult to quantify and analyze the quality of the increasing number of simulators on the market, which may hinder researchers from practicing their quantum algorithms objectively or developing quantum technologies. For these reasons, this paper proposes a quality model for quantum simulator software, which reflects the quality characteristics of simulators in seven aspects, such as functionality and performance efficiency, and selects some simulators for experimental validation of the proposed model to prove its rationality.

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CIXG: A Comprehensive Approach to Driver Gene Identification and Causal Interpretation

CIXG: A Comprehensive Approach to Driver Gene Identification...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yawen Liu Yiwen Chen Shanling Nie Hai Yang Department of Computer Science and Engineering East China University of Science and Technology Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China Center for Continuing and Lifelong Education National University of Singapore Faculty of Engineering The University of Sydney Australia

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

With the ongoing advancements in science and technology and the increasing research focus on cancer-related issues, there has been a proliferation of omics-related resources for in-depth analysis and exploration. This burgeoning volume and complexity of biological data have fostered the integration of machine-learning techniques into biology. As a result, numerous machine-learning strategies have been established to identify driver mutations. Yet, many of these strategies produce complex models, complicating comprehension and thereby clouding the impact of input features on the resulting predictions. Our analysis presented the CIXG framework, which integrates a driver gene prediction module using XGBoost with a causality interpretation module anchored on CXPlain. This architecture enables quantifying each input feature’s contribution to the prediction outcome and ensures precise predictions of driver genes. When benchmarked against the state-of-the-art (SOTA) method, CIXG demonstrated superior accuracy in pinpointing driver genes across pan-cancer studies and within the 32 specific cancer types. Importantly, our results underscored that mutation features chiefly influence CIXG’s predictive prowess, with additional support from other omics features.

关键词： Accuracy Biological system modeling Cause effect analysis Machine learning Predictive models Benchmark testing Complexity theory Bioinformatics Cancer

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