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software Defect Prediction via Deep Belief Network

Chinese Journal of Electronics 2019年第5期28卷 925-932页

作者： WEI Hua SHAN Chun HU Changzhen ZHANG Yu YU Xiao School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture State Key Laboratory in China for Geomechanics and Deep Underground Engineering (Beijing) China University of Mining and Technology School of Computer Science and Technology Shandong University of Technology

Defect distribution prediction is a meaningful topic because software defects are the fundamental cause of many attacks and data loss. Building accurate prediction models can help developers find bugs and prioritize their testing efforts. Previous researches focus on exploring different machine learning algorithms based on the features that encode the characteristics of *** problem of data redundancy exists in software defect data set, which has great influence on prediction *** propose a defect distribution prediction model(Deep belief network prediction model, DBNPM), a system for detecting whether a program module contains defects. The key insight of DBNPM is Deep belief network(DBN)technology, which is an effective deep learning technique in image processing and natural language processing,whose features are similar to defects in source *** results show that DBNPM can efficiently extract and process the data characteristics of source program and the performance is better than Support vector machine(SVM), Locally linear embedding SVM(LLE-SVM), and Neighborhood preserving embedding SVM(NPE-SVM).

关键词： Defect prediction software security Deep belief network(DBN)

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Research on the Application of Visualization Computer Technology in the Design of Architectural Decoration

Research on the Application of Visualization Computer Techno...

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2013 International Conference on Vehicle and Mechanical engineering and Information Technology, VMEIT 2013

作者： Zhou, Jun Zhou, Jian Ma, Xiao Li Architecture and Art College Shijiazhuang Tiedao University Shijiazhuang China Digital Media Department Hebei Software Institute Baoding China Microsoft IT Department Shijiazhuang Information Engineering Vocational College Shijiazhuang China

ISBN: (纸本)9783037858202

With the advances of computer science and technology, the visualization computer technology profoundly affects and changes people's understanding of the traditional visual language and promotes the continuous progress of the building decoration design. Its function of repeatedly revised not only can improve the quality of design but also can shorten the design cycle. The characteristics of building decoration design and the advantages of application of visual computer technology were first analyzed;based on analyses, the article explores the reliabilities of visualization computer technology in architectural decoration design. Linear model provides a theoretical basis and practical support for the development of architectural decoration design in a certain extent. © (2013) Trans Tech Publications, Switzerland.

关键词： Visualization

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software Curriculum Transformation at the University Level 4

Software Curriculum Transformation at the University Level

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4th IEEE World engineering Education Conference, EDUNINE 2020

作者： Dorin, Michael Chong, Mario Machuca, Juan University of St. Thomas Graduate Programs in Software St. PaulMinnesota United States Universidad Del Pacífico Faculty of Engineering Lima Peru Universidad de Lima Faculty of Engineering and Architecture Lima Peru

ISBN: (数字)9781728166384

ISBN: (纸本)9781728166384

Many software-related degrees exist, and a diversity of programs makes it difficult for candidates to choose where they wish to study. Selecting the wrong program costs students time, money, and considerable effort. Though several institutions have created curriculum guidelines for data science related programs, an overall consensus on program content does not exist at either the undergraduate or graduate levels. This paper examines the most common course requirements, such as data mining, machine learning, mathematics, software engineering, data analysis, and data visualization. We then compare the requirement analysis against the specifics of data science related programs offered at the Universidad de Lima, the Universidad Pacifico, and the University of St. Thomas. The results show that all three universities have active programs worth consideration and give students a model of what to look for when selecting their programs. © 2020 IEEE.

关键词： Data visualization

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An Exploratory Analysis of Effect of Adversarial Machine Learning Attack on IoT-enabled Industrial Control Systems

An Exploratory Analysis of Effect of Adversarial Machine Lea...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Trivedi, Sandeep Anh Tran, Tien Faruqui, Nuruzzaman Hassan, Md. Maruf Deloitte Consulting Llp Houston United States Seoul National University Department of Naval Architecture and Ocean Engineering Seoul City Korea Republic of Daffodil International University Daffodil Smart City Department of Software Engineering Dhaka Bangladesh

ISBN: (纸本)9798350347050

Machine Learning (ML)-based Intrusion Detection Systems (IDS) is an effective technology to automatically detect cyber attacks in the Internet of Things (IoT) dependent Industrial Control Systems (ICS). It is faster, more efficient, and can detect attacks without human intervention. However, ML-based IDSs have introduced another security threat called Adversarial Machine Learning (AML). An AML attack may cause severe industrial infrastructural and production damage resulting in substantial financial loss. This paper presents an exploratory analysis of initiating an AML attack using adversarial samples created using a Fast Gradient Sign Method (FGSM). The research presented in this paper has been conducted from a dataset generated from a full-fledged singular module of a power distribution industry controlled by IoT-enabled ICSs. We explored the AML attack on Gradient Boosting (GB) and Iterative Dichotomiser 3 (ID3) model and discovered the average classification accuracy, precision, recall, and F1-scores are 87%, 88%, 87.5%, and 87%, respectively. The AML attack reduces the average precision, recall, and F1-score by 20.5%, 20.5%, and 22.5%, respectively, when 50% perturbations are added to 10% samples. © 2023 IEEE.

关键词： Internet of things

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Automatic Adaptation of Reliability and Performance Trade-Offs in Service- and Cloud-Based Dynamic Routing architectures

Automatic Adaptation of Reliability and Performance Trade-Of...

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IEEE International Conference on software Quality, Reliability and Security (QRS)

作者： Amirali Amiri Uwe Zdun André van Hoorn Schahram Dustdar Software Architecture Research Group University of Vienna Software Engineering and Construction Methods University of Hamburg Distributed Systems Group Technical University of Vienna

ISBN: (纸本)9781665458146

Many different dynamic routing architectures are available, including sidecar-based routing, routing through a central entity such as an event store or gateway, or architectures with multiple routers. These architectures are currently based on vastly different implementation concepts, such as API Gateways, Message Brokers, or Service Proxies. We propose a new approach that abstracts all these architecture patterns using one Adaptive Dynamic Routers architecture. We hypothesize that a dynamic self-adaptation of the routing architecture is beneficial over any fixed architecture selections for reliability and performance trade-offs. That is, if encountered with traffic and load changes, our approach dynamically self-adapts between more central or distributed routing to optimize system reliability and performance. We evaluate our approach by analyzing our previously-measured data during an experiment of 1200 hours of runtime. Our extensive systematic evaluation with 1089 cases confirms that our hypothesis holds and our approach is beneficial in terms of reliability and performance. Moreover, we empirically validate our results on Google Cloud Platform infrastructure.

关键词： Systematics Runtime Conferences Computer architecture software quality Logic gates Routing

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Individual Characteristics Analytical Models based on Deep Learning, Trajectory and Social Network Data

Individual Characteristics Analytical Models based on Deep L...

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作者： Dechang Wang Buyang Cao Zhenfang Chu School of Software Engineering Tongji University College of Architecture and Urban Planning Tongji University

The analysis of individual characteristics in this paper refers to analyze the individual characteristics in a certain field to draw the relevant conclusions such as classification, scoring and so on. The main purpose of this study is to apply deep learning, trajectory and social network data to enhance the process of individual characteristics analysis. We developed an algorithm for extracting features from trajectory data based on LSTM and an algorithm for retrieving features from social network data based on the network structural characteristics. A series of computational experiments were conducted by employing the features extracted by our algorithms. According the experimental results and the comparisons with some existing classification models, we can conclude that our approach can improve the accuracy of individual feature classification by 5% on average.

关键词： Deep Learning LSTM Social Network Ensemble Learning Classification

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Prediction of Office Building Rental upon Spatiotemporal Data

Prediction of Office Building Rental upon Spatiotemporal Dat...

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作者： Zhihong Wang Buyang Cao School of Software Engineering Tongji University College of Architecture And Urban Planning Tongji University

This paper presents a study on effectively predicting office building rentals based on the surrounding spatiotemporal data. During the planning, development, and construction stages of an office building, the stakeholders of the building may have one question to be answered, i.e., what the potential value of the office building *** potential value of office buildings may be hard to be measured directly, however, it can be reflected in the rental after the office is put into operation. An accurate prediction of the office building rental will provide the solid base for the corresponding stakeholders to make business decisions. The rental of office buildings is affected by many factors, such as its location, floors, number of parking spots, the convenience of transportation, as well as the activities of the surrounding business. To support the rental prediction, we collect the datasets from different data sources in Shanghai. The linear regression, the decision tree, and the random forest models are employed in the computational experiments to predict the office building rentals and the most suitable prediction methodology for predicting the office building rental is suggested upon the experiments.

关键词： Commercial estate Prediction Regression model Machine learning Parameter optimization

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A Scalable Quantum Neural Network for Approximate SRBB-Based Unitary Synthesis

arXiv

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arXiv 2024年

作者： Belli, Giacomo Mordacci, Marco Amoretti, Michele Quantum Software Laboratory Department of Engineering and Architecture University of Parma Parma43124 Italy

In this work, scalable quantum neural networks are introduced to approximate unitary evolutions through the Standard Recursive Block Basis (SRBB) and, subsequently, redesigned with a reduced number of CNOTs. This algebraic approach to the problem of unitary synthesis exploits Lie algebras and their topological features to obtain scalable parameterizations of unitary operators. First, the recursive algorithm that builds the SRBB is presented, framed in the original scalability scheme already known to the literature only from a theoretical point of view. Unexpectedly, 2-qubit systems emerge as a special case outside this scheme. Furthermore, an algorithm to reduce the number of CNOTs is proposed, thus deriving a new implementable scaling scheme that requires one single layer of approximation. From the mathematical algorithm, the scalable CNOT-reduced quantum neural network is implemented and its performance is assessed with a variety of different unitary matrices, both sparse and dense, up to 6 qubits via the PennyLane library. The effectiveness of the approximation is measured with different metrics in relation to two optimizers: a gradient-based method and the Nelder-Mead method. The approximate SRBB-based synthesis algorithm with CNOT-reduction is also tested on real hardware and compared with other valid approximation and decomposition methods available in the literature. © 2024, CC BY.

关键词： Qubits

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The functional programming language R and the paradigm of dynamic scientific programming (Position paper)

The functional programming language R and the paradigm of dy...

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13th Symposium on Trends in Functional Programming, TFP 2012

作者： Widemann, Baltasar Trancón Y. Bolz, Carl Friedrich Grelck, Clemens Ecological Modelling and Computer Science Universität Bayreuth Germany Software Engineering and Programming Languages Heinrich-Heine-Universität Düsseldorf Germany Computer Systems Architecture Universiteit Van Amsterdam Netherlands

ISBN: (纸本)9783642404467

R is an environment and functional programming language for statistical data analysis and visualization. Largely unknown to the functional programming community, it is popular and influential in many empirical sciences. Due to its integrated combination of dynamic and reflective scripting on one hand, and array-based numerical computation on the other, R poses unique and challenging implementation problems, at odds with the conservative language technology employed by its developers. We discuss the background of R in historical context, highlight some of the more problematic language features, and discuss the potential for the effective use of state-of-the-art language technology in a future, safe and efficient implementation. © 2013 Springer-Verlag.

关键词： Data visualization

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APPLICATION OF DESIGN AXIOMS TO MARINE DESIGN PROBLEMS

APPLICATION OF DESIGN AXIOMS TO MARINE DESIGN PROBLEMS

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ASME 2000 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2000

作者： Yang, Y.S. Jang, B.S. Song, Y.S. Yeon, Y.S. Do, S.H. Department of Naval Architecture and Ocean Engineering Seoul National University Korea Republic of Samsung Heavy Industries Koje Shipyard Korea Republic of Department of Mechanical Design Engineering Daejin University Korea Republic of Axiomatic Design Software Korea Republic of

ISBN: (纸本)9780791835142

The Design Axioms proposed by N. P. Suh consist of Independence Axiom and Information Axiom. The Independence Axiom assists a designer in generating good design alternatives by considering the relations between the functions and the physical product using a hierarchical mapping procedure. The Information Axiom, which is related to the probability of achieving the given functional requirements, can be used as a criterion for the selection of the best solution among the proposed alternatives in the conceptual or preliminary design stage. In the early stages of marine design, especially ship design, there exists a lot of uncertainty because of the size and complexity of a marine vehicle. The uncertainty often leads to a probabilistic approach rather than a deterministic approach. The ship designs are mostly routine design to change an existing design case a little. In this paper, the availability of the Design Axioms in this marine design field will be investigated through three examples. In the conceptual design of a thruster, the Independence Axiom will be proven to be useful in examining the independence of functional requirements at each level of the decomposition process. In main engine selection example, the Information Axiom will be used for selecting the best solution among the given alternatives by estimating their respective information contents under the uncertain and ambiguous condition. In the structural design, some difficulties arise in maintaining the independence of functional requirements in general because the number of design parameters is greater than that of functional requirements. Therefore, there is much trouble in generalizing the application of the Design Axioms for the structural design, especially for the preliminary design where the principal design parameters of a design object have to be determined after its shape fixed. This paper will try a generalized approach to the similarity- based design where it is important to select which param

关键词： Structural design

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