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作者： Wadhwani, Vickey Memon, Fiaz Hameed, M. Muzaffar Blekinge Institute of Technology Department of Systems and Software Engineering Sweden University of Sindh Institute of Mathematics and Computer Science Jamshoro Pakistan

ISBN: (纸本)3540898522

We propose an architecture-based testing and reliability framework for mobile applications. During our literature study, we explored some of the software testing and reliability techniques available, as well as investigating the techniques that are being used by industry. This paper presents case studies of two companies that are developing mobile applications. These are helpful for finding the strengths and weaknesses of existing software testing and reliability techniques. In light of these strengths and weaknesses, we propose a framework of architecture-based software testing and reliability estimation for mobile applications. © 2008 Springer-Verlag.

关键词： software reliability

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Categorizing methods for integrating machine learning with executable specifications

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science China(Information sciences) 2024年第1期67卷 5-19页

作者： David HAREL Raz YERUSHALMI Assaf MARRON Achiya ELYASAF Department of Computer Science and Applied Mathematics Weizmann Institute of Science Department of Software and Information Systems Engineering Ben-Gurion University of the Negev

Deep learning(DL),which includes deep reinforcement learning(DRL),holds great promise for carrying out real-world tasks that human minds seem to cope with quite *** promise is already delivering extremely impressive results in a variety of ***,while DL-enabled systems achieve excellent performance,they are far from *** has been demonstrated,in several domains,that DL systems can err when they encounter cases they had not hitherto ***,the opacity of the produced agents makes it difficult to explain their behavior and ensure that they adhere to various requirements posed by human *** the other end of the software development spectrum of methods,behavioral programming(BP) facilitates orderly system development using self-standing executable modules aligned with how humans intuitively describe desired system *** this paper,we elaborate on different approaches for combining DRL with BP and,more generally,machine learning(ML) with executable specifications(ES).We begin by defining a framework for studying the various approaches,which can also be used to study new emerging approaches not covered *** then briefly review state-of-the-art approaches to integrating ML with ES,continue with a focus on DRL,and then present the merits of integrating ML with *** conclude with guidelines on how this categorization can be used in decision making in system development,and outline future research challenges.

关键词： machine learning artificial intelligence grey box learning domain knowledge rules behavioral programming deep reinforcement learning survey

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Building classification rules for case-based classifier using fuzzy sets and formal concept analysis 08

Building classification rules for case-based classifier usin...

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5th International Conference on Soft Computing As Transdisciplinary science and Technology, CSTST '08

作者： Tadrat, Jirapond Boonjing, Veera Pattaraintakorn, Puntip Software Systems Engineering Laboratory Department of Mathematics and Computer Science King Mongkut's Institute of Technology Ladkrabang Bangkok 10520 Thailand Department of Mathematics and Computer Science Faculty of Science King Mongkut's Institute of Technology Ladkrabang Bangkok 10520 Thailand

ISBN: (纸本)9781605580463

The focus of this paper is a construction of better knowledge base in case-based classifier system. Our knowledge base structure is based on concept lattice where rules are built from its subconcept-superconcept relation. Since the lattice can only be constructed from inputs with binary attributes, descriptive and numeric attributes must be transformed to binary attributes. In this paper, we propose the transformation of numeric attributes to descriptive attributes using fuzzy set theory. We experiment on benchmark data sets, Car and Iris, to determine the performance in term of number of rules used and classification precision. The results show that trend of accuracy is proportional to the size of learning inputs. The number of rules used is relatively small compared with size of training data. Our case-based classifier produces very promising results in practice and can classify the new problem more accurate than traditional classifiers. Copyright 2008 ACM.

关键词： Formal concept analysis

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Pseudo complementary measurement for traditional single-pixel cameras

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Chinese Physics B 2020年第11期29卷 315-322页

作者： Qian Dong Xu-Ri Yao Xin Liu Bing Liu Guang-Jie Zhai State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Key Laboratory of Electronics and Information Technology for Space Systems National Space Science CenterChinese Academy of SciencesBeijing 100190China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

A traditional single-pixel camera needs a large number of measurements to reconstruct the object with compressive sensing *** with the 1/0 matrices in classical measurement,the 1/-1 matrices in the complementary measurement has better property for reconstruction computation and returns better reconstruction ***,each row of the 1/-1 matrices needs two measurements with the traditional single-pixel camera which results into double measurements compared with the 1/0 *** this paper,we consider the pseudo complementary measurement which only takes the same amount of measurements with the row number of some properly designed 1/0 matrix to compute the total luminous flux of the objective and derives the measurement data of the corresponding 1/-1 matrix in a mathematical *** numerical simulation and experimental result show that the pseudo complementary measurement is an efficient tool for the traditional single-pixel camera imaging under low measurement rate,which can combine the advantages of the classical and complementary measurements and significantly improve the peak signal-to-noise ratio.

关键词： computational imaging single-pixel camera

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Injections Attacks Efficient and Secure Techniques Based on Bidirectional Long Short Time Memory Model

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computers, Materials & Continua 2023年第9期76卷 3605-3622页

作者： Abdulgbar A.R.Farea Gehad Abdullah Amran Ebraheem Farea Amerah Alabrah Ahmed A.Abdulraheem Muhammad Mursil Mohammed A.A.Al-qaness School of Big Data&Software Engineering Chongqing UniversityChongqing401331China Department of Management Science Engineering Dalian University of TechnologyDalian116024China Software College Northeastern UniversityShenyang110169China Department of Information Systems College of Computer and Information ScienceKing Saud UniversityRiyadh11543Saudi Arabia Department of Management Science and Engineering South China University of TechnologyGuangzhou510641China Department of Computer Engineering and Mathematics University of Rovira i VirgiliTarragonaSpain College of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua321004China

E-commerce,online ticketing,online banking,and other web-based applications that handle sensitive data,such as passwords,payment information,and financial information,are widely *** web developers may have varying levels of understanding when it comes to securing an online *** Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the OpenWeb Application Security Project(OWASP)for its 2017 Top Ten List Cross Site Scripting(XSS).An attacker can exploit these two flaws and launch malicious web-based actions as a result of these *** published articles focused on these attacks’binary *** article described a novel deep-learning approach for detecting SQL injection and XSS *** datasets for SQL injection and XSS payloads are combined into a single *** dataset is labeledmanually into three labels,each representing a kind of *** work implements some pre-processing algorithms,including Porter stemming,one-hot encoding,and the word-embedding method to convert a word’s text into a *** model used bidirectional long short-term memory(BiLSTM)to extract features automatically,train,and test the payload *** payloads were classified into three types by BiLSTM:XSS,SQL injection attacks,and *** outcomes demonstrated excellent performance in classifying payloads into XSS attacks,injection attacks,and non-malicious ***’s high performance was demonstrated by its accuracy of 99.26%.

关键词： Web security SQL injection XSS deep learning RNN LSTM BiLSTM

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On the application of predictive control techniques for adaptive performance management of computing systems

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IEEE Transactions on Network and Service Management 2009年第4期6卷 212-225页

作者： Abdelwahed, Sherif Bai, Jia Su, Rong Kandasamy, Nagarajan Department of Electrical and Computer Engineering Mississippi State University Mississippi State MS 39759 United States Institute for Software Integrated Systems Vanderbilt University Nashville TN 37235 United States Department of Mathematics and Computer Science Eindhoven Univ. of Technology Eindhoven Netherlands Department of Electrical and Computer Engineering Drexel University Philadelphia PA 19104 United States

This paper addresses adaptive performance management of real-time computing systems. We consider a generic model-based predictive control approach that can be applied to a variety of computing applications in which the system performance must be tuned using a finite set of control inputs. The paper focuses on several key aspects affecting the application of this control technique to practical systems. In particular, we present techniques to enhance the speed of the control algorithm for real-time systems. Next we study the feasibility of the predictive control policy for a given system model and performance specification under uncertain operating conditions. The paper then introduces several measures to characterize the performance of the controller, and presents a generic tool for system modeling and automatic control synthesis. Finally, we present a case study involving a real-time computing system to demonstrate the applicability of the predictive control framework. © 2009 IEEE.

关键词： Real time systems

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Heart disease classification using neural network and feature selection

Heart disease classification using neural network and featur...

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21st International Conference on systems engineering, ICSEng 2011

作者： Khemphila, Anchana Boonjing, Veera Software Systems Engineering Laboratory Department of Mathematics and Computer Science King Mongkut's Institute of Technology Ladkrabang Chalongkrung Rd. Ladkrabang Bangkok 10520 Thailand

ISBN: (纸本)9780769544953

In this study, we introduces a classification approach using Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm and a feature selection algorithm along with biomedical test values to diagnose heart disease. Clinical diagnosis is done mostly by doctor's expertise and experience. But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis. In many cases, not all the tests contribute towards effective diagnosis of a disease. Our work is to classify the presence of heart disease with reduced number of attributes. Original, 13 attributes are involved in classify the heart disease. We use Information Gain to determine the attributes which reduces the number of attributes which is need to be taken from patients. The Artificial neural networks is used to classify the diagnosis of patients. Thirteen attributes are reduced to 8 attributes. The accuracy differs between 13 features and 8 features in training data set is 1.1% and in the validation data set is 0.82%. © 2011 IEEE.

关键词： Data mining

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An efficient algorithm for mining complete share-frequent itemsets using BitTable and heuristics

An efficient algorithm for mining complete share-frequent it...

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Nawapornanan, Chayanan Boonjing, Veera Software Systems Engineering Laboratory Department of Mathematics and Computer Science King Mongkut's Institute of Technology Ladkrabang Bangkok 10520 Thailand National Centre of Excellence in Mathematics PERDO Bangkok 10400 Thailand

ISBN: (纸本)9781467314855

This paper proposes a new efficient algorithm for mining share-frequent itemsets from BitTable knowledge - extracted once from a transaction database. The knowledge contains sufficient information for such a mining task and provides efficient interactive access. The algorithm finds all share-frequent itemsets by level-wise generating complete promising candidates from a BitTable using heuristics and testing for desired solutions. Simulation results reveal that the proposed algorithm perform significantly better than ShFSM and DCG both runtime and a number of generated candidates. © 2012 IEEE.

关键词： Data mining

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Mobile cloud system: A solution for multimedia retrieval via mobile phones

Mobile cloud system: A solution for multimedia retrieval via...

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International Conference on computer sciences and Convergence Information Technology (ICCIT)

作者： Kaewkhwan Kaewmahingsa Pattarasinee Bhattarakosol Innovative Network and Software Engineering Technology (INSET) LaboratoryDepartment of Mathematics and Computer ScienceFaculty of Science Chulalongkorn University Bangkok Thailand

The multimedia file retrieval over the Internet has been counted as a popular service on the personal computer. However, the use of the Internet is shifting to the mobile devices especially smartphone. Various types of software have been proposed and sold via the operating system providers, such as iTunes of apple, Play Store of android, marketplace of Microsoft. As a result, the use of multimedia file via smartphone is becoming popular and tends to be general and widely used among users. Unfortunately, the loading system has a common problem which is a long delay during load. Due to the long delay time of the traditional client-server multimedia file retrieval service, the Mobile Cloud System (MCS) is proposed to solve the problem. Cloud computing architecture provides high efficiency of sharing the CPU and memories of different computing devices over the network. Therefore the MCS makes use of the vacant memory of a set of smartphones to shorten the downloading time. With the help of Cloud computing, users can receive multimedia file faster.

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Upsilon-SVR Polynomial Kernel for Predicting the Defect Density in New software Projects 17

Upsilon-SVR Polynomial Kernel for Predicting the Defect Dens...

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17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018

作者： Lopez-Martin, Cuauhtemoc Azzeh, Mohammad Bou-Nassif, Ali Banitaan, Shadi Department of Information Systems Universidad de Guadalajara Mexico Department of Software Engineering Applied Science Private University Amman Jordan Department of Electrical and Computer Engineering University of Sharjah Sharjah United Arab Emirates Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States

ISBN: (纸本)9781538668047

An important product measure to determine the effectiveness of software processes is the defect density (DD). In this study, we propose the application of support vector regression (SVR) to predict the DD of new software projects obtained from the International software Benchmarking Standards Group (ISBSG) Release 2018 data set. Two types of SVR (i.e., ϵ-SVR and υ-SVR) were applied to train and test these projects. Each SVR used four types of kernels. The prediction accuracy of each SVR was compared to that of a statistical regression (i.e., a simple linear regression, SLR). Statistical significance test showed that υ-SVR with polynomial kernel was better than that of SLR when new software projects were developed on mainframes and coded in programming languages of third generation. © 2018 IEEE.

关键词： Defect density

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