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1. Design and implementation of campus care system based on wechat small program | |||
Wang Yanlong,Liu Jun | |||
Computer Science and Technology 23 March 2021 | |||
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Abstract:Due to the large number of students and the lack of timely access to information, Chinese college counselors have been facing enormous pressure to manage students for a long time. In order to improve the efficiency of student management and reduce the pressure of managers at the same time, many colleges and universities have begun to develop some applications, which is focusing on some important points of student management. Starting from the management of undergraduates, we design and implement a campus care system. It collects some applications to facilitate the work of counselors,achieving the effect of precise management. | |||
TO cite this article:Wang Yanlong,Liu Jun. Design and implementation of campus care system based on wechat small program[OL].[23 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754280 |
2. A Defect Feature Extraction and Confirmation Method Based on Global Data Flow Analysis | |||
Chen Lulu,Jin Dahai,Gong Yunzhan | |||
Computer Science and Technology 28 December 2019 | |||
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Abstract:Static code detection tools perform code inspection and analysis, which helps to detect and prevent errors early, greatly improve software reliability and reduce software development costs. However, the problem caused by this is that static analysis often generates a large number of false defect reports. Manual review of false positives is necessary, and it takes time and effort, so it is necessary to optimize the reports generated by static detection tools. This paper analyzes thetest problems of Defect Test System (DTS). Based on this, a feature extraction method based on global data flow analysis is proposed. This method obtains the context feature of the defect from the paths to the target point(TP), maps the feature to feature vector and finally uses machine learning methods for learning and training. Take null-pointer defect (NPD) that occupies the majority of alarms reported by DTS as an example, automatic confirmation of defects is achieved. The experimental results show that this method correctly confirms about 75% of the defects and can serve the static code detection tool better. | |||
TO cite this article:Chen Lulu,Jin Dahai,Gong Yunzhan. A Defect Feature Extraction and Confirmation Method Based on Global Data Flow Analysis[OL].[28 December 2019] http://en.paper.edu.cn/en_releasepaper/content/4750208 |
3. A New Hybrid User Similarity Model for Collaborative Filtering Algorithms | |||
FU Bin,HU Xiang | |||
Computer Science and Technology 02 April 2019 | |||
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Abstract:Collaborative filtering (CF) is one of the most widely used personalized recommendation methods. Its basic assumption is that users with similar behaviors tend to share similar preferences and make the same choices. Similarity calculation between users or items is considered to be the key of traditional collaborative filtering recommendation algorithm.Traditional collaborative filtering algorithm relies entirely on the common rating items of users when calculating the similarity,while the rating matrix is extremely sparse, the common rating items of users are rare, which results in that the similarity can not be measured or the measurement error is very large, thus affecting the recommendation effect. In addition, the traditional similarity model does not fully consider the influence factor of similarity, which causes the search for similar neighbor errors and the quality of recommendation is not high。To solve this problem, a new hybrid user similarity model for collaborative filtering is proposed,it effectively considers the impact of user\'s non-common rating information on user similarity, which solves the problem that similarity depends entirely on common rating items.At the same time, it fully considers the influence factors of user similarity, such as user common rating reward factor, item attribute preference factor, user confidence factor. The common rating reward factor increases the proportion of common reward items in the similarity measure. The item attribute preference factor can effectively distinguish the user\'s different attribute preferences for different items. The user confidence factor can reduce the influence of noise data and improve the reliability of the model output . The test is carried out on the MovieLens dataset with extremely sparse data and experimental results show that the proposed algorithm has higher accuracy of user similarity, which helps to find suitable nearest neighbor users and improve recommendation accuracy. | |||
TO cite this article:FU Bin,HU Xiang. A New Hybrid User Similarity Model for Collaborative Filtering Algorithms[OL].[ 2 April 2019] http://en.paper.edu.cn/en_releasepaper/content/4748227 |
4. Research and application of keyword driven automated testing framework in regression testing | |||
GE Jinpeng,ZHOU Xiaoguang | |||
Computer Science and Technology 29 June 2018 | |||
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Abstract:With the development of information technology, software version iteration is frequent. The testing process is a large part of the overall development process. Improving test efficiency is an urgent problem to be solved. This paper introduces regression testing, the idea of automated testing, and the existing related automated testing tools. In order to improve the efficiency of regression testing, an automatic testing framework based on the idea of keyword driven is proposed. The framework is based on the JAVA Selenium framework and is described in detail in terms of automated test framework modules, hierarchies, and workflow. | |||
TO cite this article:GE Jinpeng,ZHOU Xiaoguang. Research and application of keyword driven automated testing framework in regression testing[OL].[29 June 2018] http://en.paper.edu.cn/en_releasepaper/content/4745514 |
5. A Verilog Precompiler for Interactive Optimization of IP Core Design | |||
Donghua Wang,Yibo Fan,Kenny Q. Zhu,Wenjing Fang | |||
Computer Science and Technology 20 December 2015 | |||
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Abstract:SV+ is an interactive compiler that makes circuit designer do trade-offs between resource consuming and time cost easily, without rewriting the source code. A set of succinct SV+ syntaxes are proposed in this work. They can be used to embed with Verilog to describe the reconfigurable parts of a circuit. Users have opportunity to select optimization options during the compiling process. The compiler generates Verilog RTL codes, depends on these choices. And for different optimization choices, the circuits vary in architectures besides in time and resource. SV+ syntaxes can describe reconfigurable circuit structures in mathematical or functional level, so designers are liberated from putting much effort on concerning about module scheduling and wire connection. Unlike other circuit compilers, for example DFT compiler[13], which work on single kind of algorithm, SV+ syntaxes can be used in a range of Verilog programs as long as there are any reconfigurable components available in the design. | |||
TO cite this article:Donghua Wang,Yibo Fan,Kenny Q. Zhu, et al. A Verilog Precompiler for Interactive Optimization of IP Core Design[OL].[20 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4666319 |
6. The Study on JVM and the Transportability of Java | |||
Zheng Weiguo,Tian Qichong | |||
Computer Science and Technology 27 July 2009 | |||
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Abstract:This paper introduces the Java virtual machine based on which analyzes the dynamic loading mechanism, the working principles and uses of class loader, expounds the implementation process of Java class is loaded, summarizes the impact of class loader on efficiency of the Java virtual machine. At last, Java transportability is also discussed, analyzes the relevant factors that influence the transportability of Java. | |||
TO cite this article:Zheng Weiguo,Tian Qichong. The Study on JVM and the Transportability of Java[OL].[27 July 2009] http://en.paper.edu.cn/en_releasepaper/content/34103 |
7. A comparison of exception system between C++ and Java | |||
Bao Peng,Gao Heng,Qiu Ye | |||
Computer Science and Technology 01 July 2009 | |||
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Abstract:This article investigates the exception system in C++ and Java separately. It compares the rules in both language for matching the exception, the hierarchy and pattern of exception code, and discusses the lifetime and storage of exception objects. Finally it conceives other exception systems that similar with exceptions in other language. | |||
TO cite this article:Bao Peng,Gao Heng,Qiu Ye. A comparison of exception system between C++ and Java[OL].[ 1 July 2009] http://en.paper.edu.cn/en_releasepaper/content/33563 |
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