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International Conference in software Engineering Research and Innovation (CONISOFT)

作者： Johann A. Olivares-Galindo Ángel J. Sánchez-García R. Erandi Barrientos-Martínez Jorge Octavio Ocharán-Hernández Facultad de Estadística e Informática Universidad Veracruzana Xalapa México Instituto de Investigaciones en Inteligencia Artificial Universidad Veracruzana Xalapa México

ISBN: (数字)9798350328837

ISBN: (纸本)9798350328844

The software Defect Prediction area is important in software development since it allows anticipating possible software defects before they occur in production and affect end users. If software defects are not corrected, they can degrade system quality and reliability. This work aims to carry out a Systematic Literature Review to know which ensemble classification algorithms help predict if a system module is prone to software defects. In the same way, it is intended to know the most popular metrics that evaluate the effectiveness of the applied algorithms and the results of the algorithms in the area of software Defect Prediction. This work shows that the most used ensemble classifiers for predicting software defects are Random Forest and AdaBoost; regarding the metrics, most of the studies use AVC and F-Measure and Accuracy.

关键词： Measurement Technological innovation Systematics Bibliographies software algorithms Prediction algorithms software

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A New Method for Searching Optimal Differential and Linear Trails in ARX Ciphers

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IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第2期67卷 1054-1068页

作者： Liu, Zhengbin Li, Yongqiang Jiao, Lin Wang, Mingsheng Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Beijing 100093 Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing 100049 Peoples R China State Key Lab Cryptol Beijing 100878 Peoples R China

In this paper, we propose an automatic tool to search for optimal differential and linear trails in ARX ciphers. It's shown that a modulo addition can be divided into sequential small modulo additions with carry bit, which turns an ARX cipher into an S-box-like cipher. From this insight, we introduce the concepts of carry-bit-dependent difference distribution table (CDDT) and carry-bit-dependent linear approximation table (CLAT). Based on them, we give efficient methods to trace all possible output differences and linear masks of a big modulo addition, with returning their differential probabilities and linear correlations simultaneously. Then an adapted Matsui's algorithm is introduced, which can find the optimal differential and linear trails in ARX ciphers. Besides, the superiority of our tool's potency is also confirmed by experimental results for round-reduced versions of HIGHT and SPECK. More specifically, we find the optimal differential trails for up to 10 rounds of HIGHT, reported for the first time. We also find the optimal differential trails for 10, 12, 16, 8 and 8 rounds of SPECK32/48/64/96/128, and report the provably optimal differential trails for SPECK48 and SPECK64 for the first time. The optimal linear trails for up to 9 rounds of HIGHT are reported for the first time, and the optimal linear trails for 22, 13, 15, 9 and 9 rounds of SPECK32/48/64/96/128 are also found respectively. These results evaluate the security of HIGHT and SPECK against differential and linear cryptanalysis. Also, our tool is useful to estimate the security in the design of ARX ciphers.

关键词： Ciphers Correlation Linear approximation software algorithms Approximation algorithms Tools Hash functions Automatic search differential trail linear trail ARX HIGHT SPECK

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Research on the Development and Execution of Virtual Reality Merchandise software Utilizing the Artificial Intelligence Deep Learning Algorithm

Research on the Development and Execution of Virtual Reality...

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Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on

作者： Xiongwei Qiu Lianzhi Shi Jiale Ren Zhejiang Yixiong Intelligent Technology Co. LTD Zhejiang China Hangzhou Ptop Information Technology Co. LTD Zhejiang China

ISBN: (数字)9798350341690

ISBN: (纸本)9798350341706

As a method of immersive interaction, virtual reality (VR) is rapidly permeating a variety of disciplines due to the continuous development of artificial intelligence and deep learning technology. This study seeks to investigate the design and implementation methodologies of AI-based deep learning-based interactive product software for virtual reality. The study first provides an overview of virtual reality technology and deep learning algorithms, and introduces their application prospects in interaction design. Then, the study details the key technology of gesture recognition based on deep learning to enhance the naturalness and immersion of virtual reality interaction. In terms of software design, the study designed a prototype of a virtual reality interaction product that integrates the above techniques, and evaluated its performance and user experience through experiments. The experimental results show that the virtual reality interaction product based on AI deep learning algorithms has achieved significant improvement in terms of interaction effect and user satisfaction. In summary, this study provides useful guidance and reference for further promoting the development of virtual reality interactive products.

关键词： Deep learning Training Solid modeling Heuristic algorithms software algorithms Virtual reality Gesture recognition

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Design and Analysis of software and Hardware Cooperative Mode

Design and Analysis of Software and Hardware Cooperative Mod...

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Neural Networks, Information and Communication Engineering (NNICE), International Conference on

作者： Yinglu Zhao Xinyi Song Yin Xiong Siyu Wang School of Information Engineering Wuhan University of Technology Wuhan China

In daily work, there is a large number of remote document signing requirements. At present, the mainstream method is to mail the signed documents or transmit pictures of the signed documents. Obviously, mailing some confidential documents is not conducive to confidentiality, and the picture transmission of the signed documents is easy to leak and cannot guarantee the signature of the person. Combined with the above scenarios, a secure remote document signing solution is urgently needed in the current market. Based on the design idea of hardware and software collaboration,we introduce the domestic Hummingbird E203 processor with RISC- V architecture as the core controller, use FPGA (field-programmable gate array) to realize the convolutional neural network handwritten character recognition hardware accelerator and digital watermark embedding algorithm, and carry out functional simulation and experimental data collection.

关键词： Handwriting recognition Costs software algorithms Process control Watermarking software Convolutional neural networks

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MT-ART: A Test Case Generation Method Based on Adaptive Random Testing and Metamorphic Relation

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IEEE TRANSACTIONS ON RELIABILITY 2021年第4期70卷 1397-1421页

作者： Hui, Zhan-wei Wang, Xiaojuan Huang, Song Yang, Sen Acad Mil Sci Inst Evaluat & Assessment Res Beijing 100091 Peoples R China Army Engn Univ PLA Software Testing & Evaluat Ctr Nanjing 210007 Peoples R China Army Engn Univ PLA Command Control Engn Inst Nanjing 210007 Peoples R China

Most of metamorphic testing (MT) research works focused on the generation and application of metamorphic relations (MRs). There is no clear conclusion about the relationship between test case generation methods and performance of MT. In this article, we introduce a novel method based on adaptive random testing (ART) and MR for MT test case generation. It proposes a family of algorithms for MT test cases generation, named as MT based ART (MT-ART). Three distances are measured to generate the next MT test case. In order to verify the performance of this method, series of experiments on four programs with different numbers of inputs are introduced. The results show that MT-ART performs better than other ART algorithms not only in test effectiveness, but also in test efficiency and test coverage. Based on this article, the following conclusions can be drawn: first, considering the effectiveness of MRs and test cases in MT may lead to better results. In this way, most of the existing research can be improved by this method. This is the most important contribute of our research. Second, not only the source test cases, but also the follow-up test cases can improve the performance of MT. Therefore, they should be considered together during the process of the next test case generation. Third, the average distance performs better than the max distance and the minimum distance in metamorphic test case selection.

关键词： Testing Subspace constraints software Partitioning algorithms Genetic algorithms Target tracking software algorithms Adaptive random test metamorphic distance (MD) metamorphic relation (MR) metamorphic testing (MT) random test

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An Adaptive Opposition-Based Learning Selection: The Case for Jaya Algorithm

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IEEE ACCESS 2021年 9卷 55581-55594页

作者： Nasser, Abdullah B. Zamli, Kamal Z. Hujainah, Fadhl Ghanem, Waheed Ali H. M. Saad, Abdul-Malik H. Y. Alduais, Nayef Abdulwahab Mohammed Univ Malaysia Pahang Coll Comp & Appl Sci Fac Comp Pekan 26600 Malaysia Chalmers & Univ Technol Comp Sci & Engn Dept S-41296 Gothenburg Sweden Univ Malaysia Terengganu Fac Ocean Engn Technol & Informat Kuala Terengganu 21030 Malaysia Univ Teknol Malaysia Fac Engn Sch Elect Engn Div Elect & Comp Engn Johor Baharu 81310 Malaysia Univ Tun Hussein Onn Malaysia UTHM Fac Comp Sci & Informat Technol FSKTM Parit Raja 86400 Malaysia

Over the years, opposition-based Learning (OBL) technique has been proven to effectively enhance the convergence of meta-heuristic algorithms. The fact that OBL is able to give alternative candidate solutions in one or more opposite directions ensures good exploration and exploitation of the search space. In the last decade, many OBL techniques have been established in the literature including the Standard-OBL, General-OBL, Quasi Reflection-OBL, Centre-OBL and Optimal-OBL. Although proven useful, much existing adoption of OBL into meta-heuristic algorithms has been based on a single technique. If the search space contains many peaks with potentially many local optima, relying on a single OBL technique may not be sufficiently effective. In fact, if the peaks are close together, relying on a single OBL technique may not be able to prevent entrapment in local optima. Addressing this issue, assembling a sequence of OBL techniques into meta-heuristic algorithm can be useful to enhance the overall search performance. Based on a simple penalized and reward mechanism, the best performing OBL is rewarded to continue its execution in the next cycle, whilst poor performing one will miss cease its current turn. This paper presents a new adaptive approach of integrating more than one OBL techniques into Jaya Algorithm, termed OBL-JA. Unlike other adoptions of OBL which use one type of OBL, OBL-JA uses several OBLs and their selections will be based on each individual performance. Experimental results using the combinatorial testing problems as case study demonstrate that OBL-JA shows very competitive results against the existing works in term of the test suite size. The results also show that OBL-JA performs better than standard Jaya Algorithm in most of the tested cases due to its ability to adapt its behaviour based on the current performance feedback of the search process.

关键词： software algorithms Optimization Genetic algorithms Explosions Artificial neural networks Search problems Reinforcement learning Opposition based learning adaptive selection Jaya algorithm

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MemComputing vs. Quantum Computing: some analogies and major differences 22

MemComputing vs. Quantum Computing: some analogies and major...

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IEEE 22nd International Conference on Nanotechnology (NANO)

作者： Di Ventra, Massimiliano Univ Calif San Diego Dept Phys La Jolla CA 92093 USA

ISBN: (数字)9781665452250

ISBN: (纸本)9781665452250

Quantum computing employs some quantum phenomena to process information. It has been hailed as the future of computing but it is plagued by serious hurdles when it comes to its practical realization. MemComputing is a new paradigm that instead employs non-quantum dynamical systems and exploits time non-locality (memory) to compute. It can be efficiently emulated in software and its path towards hardware is more straightforward. I will discuss some analogies between these two computing paradigms, and the major differences that set them apart.

关键词： Quantum computing software algorithms software Hardware Dynamical systems Physics Optimization

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Evaluation of Vehicle Assignment algorithms for Autonomous Mobility on Demand

Evaluation of Vehicle Assignment Algorithms for Autonomous M...

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33rd IEEE Intelligent Vehicles Symposium (IEEE IV)

作者： Goncu, Sadullah Silgu, Mehmet Ali Celikoglu, Hilmi Berk Istanbul Tech Univ ITU ITU ITS Res Lab TR-34469 Istanbul Turkey Fatih Sultan Mehmet Vakif Univ Dept Civil Engn TR-34445 Istanbul Turkey Bartin Univ Dept Civil Engn TR-74100 Bartin Turkey Istanbul Tech Univ ITU Dept Civil Engn TR-34469 Istanbul Turkey

ISBN: (纸本)9781665488211

The term "Mobility" is gaining new perspectives. Due to the paradigm shift driven by information technologies and autonomous vehicles, on-demand mobility services have experienced significant growth. Operating such a service efficiently is a challenging task. Especially, assigning vehicles to customers plays a vital role in this regard. To meet a satisfactory level of service while keeping the operational costs to a minimum requires efficient assignment strategies. Work summarized in this paper utilizes several shared and non-shared assignment algorithms in order to propose a methodology to assess the effects on the overall system performance for an Autonomous Mobility on Demand system. Selected algorithms are tested in a theoretical network with real-world taxi data with the help of microscopic traffic simulation software Simulation of Urban Mobility. Simulation scenarios are generated for both varying demand levels and increasing fleet sizes. Results suggest that for high demand levels and small fleet sizes, shared algorithms outperform non-shared algorithms for every performance measure chosen: total vehicle kilometers traveled, the ratio of empty fleet kilometers, average passenger waiting time for pick up, and the number of customers served in a period.

关键词： Heuristic algorithms System performance software algorithms Urban areas Traffic control Size measurement Routing

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Tracking Buggy Files: New Efficient Adaptive Bug Localization Algorithm

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IEEE TRANSACTIONS ON software ENGINEERING 2021年第7期48卷 2557-2569页

作者： Fejzer, Mikolaj Narebski, Jakub Przymus, Piotr Stencel, Krzysztof Nicolaus Copernicus Univ Torun Fac Math & Comp Sci PL-87100 Torun Poland Nicolaus Copernicus Univ Torun PL-87100 Torun Poland Univ Warsaw PL-00927 Warsaw Poland

Upon receiving a new bug report, developers need to find its cause in the source code. Bug localization can be helped by a tool that ranks all source files according to how likely they include the bug. This problem was thoroughly examined by numerous scientists. We introduce a novel adaptive bug localization algorithm. The concept behind it is based on new feature weighting approaches and an adaptive selection algorithm utilizing pointwise learn-to-rank method. The algorithm is evaluated on publicly available datasets, and is competitive in terms of accuracy and required computational resources compared to state-of-the-art. Additionally, to improve reproducibility we provide extended datasets that include computed features and partial steps, and we also provide the source code.

关键词： Computer bugs Location awareness software History software algorithms Machine learning algorithms Training Bug reports software maintenance learning to rank

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PFHA: A Novel Page Migration Algorithm for Hybrid Memory Embedded Systems

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2021年第10期29卷 1685-1692页

作者： Niu, Na Fu, Fangfa Yang, Bing Wang, Qiang Li, Xinpeng Lai, Fengchang Wang, Jinxiang Harbin Inst Technol Dept Microelect Ctr Harbin 150000 Peoples R China Harbin Univ Sci & Technol Dept Software Harbin 150000 Peoples R China Harbin Univ Sci & Technol Microelect Sch Harbin 150000 Peoples R China

Phase change memory (PCM) and DRAM-based hybrid main memory have emerged as one of the most promising technology for the future embedded systems. Previous research works have focused on page migration strategies to fully exploit the advantages of DRAM and PCM to achieve higher performance and energy efficiency. However, the ability to predict the pages' future behavior in these strategies could be further improved and most strategies do not consider how to reduce the DRAM energy consumption to further decrease the hybrid system energy. In this article, we propose a novel dynamic hardware migration strategy named periodical frequency hot-region aware page replacement algorithm (PFHA), which utilizes the relation of periodical read and write access frequencies to predict the hotness of a certain page. Meanwhile, PFHA innovatively initiates write hot page self-migration within DRAM to establish a concentrate DRAM write hot region to reduce the DRAM energy. Experiment results confirm that the proposed technique is able to make most of the write hot pages absorbed by DRAM. Meanwhile, it decreases the PCM average access time to a great extent and gets preferable energy consumption.

关键词： Random access memory Phase change materials Prediction algorithms Memory architecture Embedded systems software algorithms Energy consumption Embedded system hybrid main memory memory controller page migration scheme phase change memory (PCM)

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