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software defined industrial network architecture for edge computing offloading

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The Journal of China Universities of Posts and Telecommunications 2019年第1期26卷 49-58页

作者： Xu Fangmin Ye Huanyu Cui Shaohua Zhao Chenglin Yao Haipeng School of Telecommunication Engineering Beijing University of Posts and Telecommunications China Petroleum Technology and Development Corporation

The integration of the Internet and the traditional manufacturing industry makes the industrial Internet of things(IIoT) as a popular research topic. However, traditional industrial networks continue to face challenges of resource management and limited raw data storage and computation capacity. A novel software defined industrial network(SDIN) architecture was proposed to address the existing drawbacks in IIoT such as resource utilization, data processing and storage, and system compatibility. The architecture is developed based on the software defined network(SDN) architecture, combining hierarchical cloud and fog computing and content-aware caching technologies. Based on the SDIN architecture, two types of edge computing strategies in industrial applications are discussed. Different scenarios and service requirements are considered. The simulation results confirm that the SDIN architecture is feasible and effective in the application of edge computing offloading.

关键词： software defined industrial network(SDIN) industrial Internet of things(IIoT) edge computing computing offloading time delay

software testing without the oracle correctness assumption

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Frontiers of Computer Science 2020年第3期14卷 221-224页

作者： Tun LI Wanwei LIU Xinrui GUO Ji WANG School of Computer National University of Defense TechnologyChangsha 410073China Laboratory of software Engineering for Complex Systems Changsha 410073China Microsoft STCA Beijing 100080China

1 Introduction When testing programs,the oracle correctness assumption(OCA)implies that there are no errors in the test oracles,such as the expected outputs are always correctly designed and written in unit testing ***'s work[1]is the first piece of work that investigated the influences on fault localization caused by errors in test oracles and proposed a method to identify potential incorrect ***,no systematic discussions are availed.

关键词： oracle testing software

Search-Based Cost-Effective software Remodularization

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Journal of Computer Science & Technology 2018年第6期33卷 1320-1336页

作者： Rim Mahouachi Complex Outstanding Systems Modeling Optimization and Supervision Laboratory National School of Computer Science University of Manouba 2010 Manouba Tunisia

software modularization is a technique used to divide a software system into independent modules （packages）that are expected to be cohesive and loosely coupled. However, as software systems evolve over time to meet new require-ments, their modularizations become complex and gradually loose their quality. Thus, it is challenging to automaticallyoptimize the classes＇ distribution in packages, also known as remodularization. To alleviate this issue, we introduce a newapproach to optimize software modularization by moving classes to more suitable packages. In addition to improving designquality and preserving semantic coherence, our approach takes into consideration the refactoring effort as an objective initself while optimizing software modularization. We adapt the Elitist Non-dominated Sorting Genetic Algorithm （NSGA-Ⅱ）of Deb et al. to find the best sequence of refactorings that 1） maximize structural quality, 2） maximize semantic cohesivenessof packages （evaluated by a semantic measure based on WordNet）, and 3） minimize the refactoring effort. We report theresults of an evaluation of our approach using open-source projects, and we show that our proposal is able to produce acoherent and useful sequence of recommended refactorings both in terms of quality metrics and from the developer＇s pointsof view.

关键词： remodularization search-based software engineering refactoring effort multi-objective optimization seman-tics dependency

software debugging analysis based on developer behavior data

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Frontiers of Computer Science 2021年第1期15卷 233-235页

作者： Bo YANG Qian YU Huai LIU Yuze HE Chao LIU School of Information Science and Technology North China University of TechnologyBeijing 100144China Department of Computer Science and software Engineering Swinburne University of TechnologyHawthorn VIC 3122Australia School of Computer Science and Engineering Beihang UniversityBeijing 100191China

1 Introduction software debugging is one of the most costly activities in sof-ware development *** mainly consists of four core tasks,namely fault detection,fault localization,fault understanding and fault *** them,fa... 详细信息

关键词： fault process. software

Mining Patterns from Change Logs to Support Reuse-Driven Evolution of software Architectures

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Journal of Computer Science & Technology 2018年第6期33卷 1278-1306页

作者： Aakash Ahlnad Claus Pahl Ahmed B. Altamimi Abdulrahman Alreshidi College of Computer Science and Engineering University of Ha'il Ha'il 2440 Saudi Arabia Faculty of Computer Science Free University of Bozen-Bolzano Bozen-Bolzano 39100 Italy

Modern software systems are subject to a continuous evolution under frequently varying requirements andchanges in systems＇ operational environments. Lehman＇s law of continuing change demands for long-living and continuouslyevolving software to prolong its productive life and economic value by accommodating changes in existing software. Reusableknowledge and practices have proven to be successful for continuous development and evolution of the software effectivelyand efficiently. However, challenges such as empirical acquisition and systematic application of the reusable knowledge andpractices must be addressed to enable or enhance software evolution. We investigate architecture change logs -- mininghistories of architecture-centric software evolution -- to discover change patterns that 1） support reusability of architecturalchanges and 2） enhance the efficiency of the architecture evolution process. We model architecture change logs as a graphand apply graph-based formalism （i.e., graph mining techniques） to discover software architecture change patterns. Wehave developed a prototype that enables tool-driven automation and user decision support during software evolution. Wehave used the ISO-IEC-9126 model to qualitatively evaluate the proposed solution. The evaluation results suggest that theproposed solution 1） enables the reusability of frequent architectural changes and 2） enhances the efficiency of architecture-centric software evolution process. The proposed solution promotes research efforts to exploit the history of architecturalchanges to empirically discover knowledge that can guide architecture-centric software evolution.

关键词： software architecture software maintenance and evolution evolution pattern repository mining

Forecasting of software Reliability Using Neighborhood Fuzzy Particle Swarm Optimization Based Novel Neural Network

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1365-1383页

作者： Pratik Roy Ghanshaym Singha Mahapatra Kashi Nath Dey Department of Computer Science and Engineering University of CalcuttaKolkata-700106India Department of Mathematics National Institute of TechnologyPuducherryKaraikal-609609India

This paper proposes an artificial neural network(ANN) based software reliability model trained by novel particle swarm optimization(PSO) algorithm for enhanced forecasting of the reliability of software. The proposed ANN is developed considering the fault generation phenomenon during software testing with the fault complexity of different levels. We demonstrate the proposed model considering three types of faults residing in the software. We propose a neighborhood based fuzzy PSO algorithm for competent learning of the proposed ANN using software failure data. Fitting and prediction performances of the neighborhood fuzzy PSO based proposed neural network model are compared with the standard PSO based proposed neural network model and existing ANN based software reliability models in the literature through three real software failure data sets. We also compare the performance of the proposed PSO algorithm with the standard PSO algorithm through learning of the proposed ANN. Statistical analysis shows that the neighborhood fuzzy PSO based proposed neural network model has comparatively better fitting and predictive ability than the standard PSO based proposed neural network model and other ANN based software reliability models. Faster release of software is achievable by applying the proposed PSO based neural network model during the testing period.

关键词： Artificial neural network(ANN) fuzzy particle swarm optimization(PSO) reliability prediction software reliability

Development of Calculation software for Automotive Side Swing Door Closing Energy

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Chinese Journal of Mechanical Engineering 2010年第6期23卷 690-698页

作者： GAO Yunkai XU Ruiyao YANG Lei MA Jtmjie College of Automotive Engineering Tongji University Shanghai 201804 China Pan Asia Technical Automotive Center Co. Ltd. Shanghai 201201 China

The existing research of the automotive side swing door and the closing angle via tests and simulations. In these tests, the closing energy is mainly conducted by measuring the closing energy door closing velocity and initial door closing angle are usually not taken into consideration, so the accuracy of the test data cannot be ensured, and, meanwhile, simulations require a great deal of manpower and time. Moreover, frequent tests would give rise to the increasing research and development costs. In this paper, in response to the deficiencies of these current methods, the complicated door closing process is decomposed into the closing processes of different subsystems of door, which includes weather strip seal＇, air-binding effect, door weight, hinge, check-link and latch. Mathematical models of those subsystems are established according to their working principles during the door closing process. In addition to the theoretical research, an Excel-based software using Visual Basic Application programming language is developed to realize the mathematical models, which aims to calculate the energy consumption of the subsystems. The energy consumption of different subsystems of a production vehicle door is measured to verify the accuracy of the calculation sottware developed. The proposed research provides not only the theoretical basis for the future door closing energy research, but also an interactive method and system, effectively improving the quality and efficiency of vehicle door design.

关键词： side swing door closing energy mathematical model software

DP-Share: Privacy-Preserving software Defect Prediction Model Sharing Through Differential Privacy

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Journal of Computer Science & Technology 2019年第5期34卷 1020-1038页

作者： Xiang Chen Dun Zhang Zhan-Qi Cui Qing Gu Xiao-Lin Ju School of Information Science and Technology Nantong UniversityNantong 226019China State Key Laboratory for Novel software Technology Nanjing UniversityNanjing 210023China School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Computer School Beijing Information Science and Technology UniversityBeijing 100101China

In current software defect prediction (SDP) research, most previous empirical studies only use datasets provided by PROMISE repository and this may cause a threat to the external validity of previous empirical results. Instead of SDP dataset sharing, SDP model sharing is a potential solution to alleviate this problem and can encourage researchers in the research community and practitioners in the industrial community to share more models. However, directly sharing models may result in privacy disclosure, such as model inversion attack. To the best of our knowledge, we are the first to apply differential privacy (DP) to privacy-preserving SDP model sharing and then propose a novel method DP-Share, since DP mechanisms can prevent this attack when the privacy budget is carefully selected. In particular, DP-Share first performs data preprocessing for the dataset, such as over-sampling for minority instances (i.e., defective modules) and conducting discretization for continuous features to optimize privacy budget allocation. Then, it uses a novel sampling strategy to create a set of training sets. Finally it constructs decision trees based on these training sets and these decision trees can form a random forest (i.e., model). The last phase of DP-Share uses Laplace and exponential mechanisms to satisfy the requirements of DP. In our empirical studies, we choose nine experimental subjects from real software projects. Then, we use AUC (area under ROC curve) as the performance measure and holdout as our model validation technique. After privacy and utility analysis, we find that DP-Share can achieve better performance than a baseline method DF-Enhance in most cases when using the same privacy budget. Moreover, we also provide guidelines to effectively use our proposed method. Our work attempts to fill the research gap in terms of differential privacy for SDP, which can encourage researchers and practitioners to share more SDP models and then effectively advance the state of

关键词： software defect prediction model sharing differential privacy cross project defect prediction empirical study

Decomposing Composite Changes for Code Review and Regression Test Selection in Evolving software

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Journal of Computer Science & Technology 2019年第2期34卷 416-436页

作者： Bo Guo Young-Woo Kwon Myoungkyu Song Department of Global Operations PayPal Omaha Nebraska 68128 U.S.A. School of Computer Science and Engineering Kyungpook National University Daegu 702-701 South Korea Department of Computer Science University of Nebraska at Omaha Omaha 68128 U.S.A.

Inspecting and testing code changes typically require a significant amount of developer *** a system evolves,developers often create composite changes by mixing multiple development issues,as opposed to addressing one independent issue—an atomic *** composite changes often becomes time-consuming and *** test unrelated edits on composite changes,rerunning all regression tests may require excessive *** address the problem,we present an interactive technique for change decomposition to support code reviews and regression test selection,called *** a developer specifies code change within a diff patch,ChgCutter partitions composite changes into a set of related atomic changes,which is more cohesive and self-contained regarding the issue being *** composite change inspection,it generates an intermediate program version that only includes a related change subset using program dependence *** cost reduction during regression testing,it safely selects only affected tests responsible for changes to an intermediate *** the evaluation,we apply ChgCutter to 28 composite changes in four open source *** partitions these changes with 95.7% accuracy,while selecting affected tests with 89.0% *** conduct a user study with professional software engineers at PayPal and find that ChgCutter is helpful in understanding and validating composite changes,scaling to industry projects.

关键词： software maintenance and evolution code review test selection program slicing