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International Conference on Reliability, Maintainability and Safety,ICRMS

作者： Erqiang Feng Chuncheng Wu Software Engineering Department Establishment of Chinese Aero-polytechnology Beijing China

ISBN: (数字)9798350329988

ISBN: (纸本)9798350329995

The primary purpose of software engineering is to provide high-quality software, aimed at reducing the amount of software failures. To increase the effectiveness and efficiency of an ordinary software failure-mode analysis, an automated software failure-mode analysis method is proposed. The automated method combines a model-based approach with historical data to overcome the limitations of the ordinary method. Furthermore, the extracting and matching algorithms that are employed in the automated analysis method are discussed. Feature space is used to obtain software failure mode features. The advantages of the automated method over the ordinary method are verified through engineering applications.

关键词： Knowledge engineering Analytical models Databases software algorithms Feature extraction software Data models software reliability Safety software engineering

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HASP: High Availability SFC Placement Approach in Data Center Network 23

HASP: High Availability SFC Placement Approach in Data Cente...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Xu, Ziqi Han, Qingmian Cheng, Bo Niu, Meng Chen, Junliang Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology China The 54th Research Institute of China Electronics Technology Group Corporation Beijing China

ISBN: (纸本)9781665494571

Network Function Virtualization (NFV) is a promising technology that decouples network functions from the hardware. Virtual Network Functions (VNFs) can form service function chains (SFCs) and be orchestrated like internet applications. However, there are higher availability requirements for SFCs because the network's failure causes more severe consequences. This paper proposes the High Availability SFC Placement Approach (HASP) for SFC placement in Data Center. HASP includes a cross-backup (CB) model to improve the availability of SFCs. The software runs on the physical machine (PM), and once the PM fails, the software assigned to it will also fail. The CB model adopts offsite redundant VNF instances to avoid PM failure and guarantee SFC availability. HASP also considers the impact of data link reliability on SFC availability. In addition, a heuristic limited area search optimization (LASO) algorithm is incorporated to place the VNFs of SFCs. The evaluation results show that the LASO algorithm is 300% faster than the traditional heuristic algorithm. Combining the CB model and the LASO algorithm, HASP can improve the availability of SFCs and obtain the optimal placement scheme. © 2021 IEEE.

关键词： Data centers Smart cities Service function chaining Heuristic algorithms software algorithms software Network function virtualization

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Research of Multipath Routing and Load Balancing Processes in software Defined Networks Based on Bird Migration Algorithm

Research of Multipath Routing and Load Balancing Processes i...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Dmitry Perepelkin Maria Ivanchikova Tin Nguyen Faculty of Computer Engineering Ryazan State Radio Engineering University Ryazan Russian Federation

Technology software defined networks (SDNs) allows managing the network at the software level, expanding the functionality to control the process of data transfer in the network. SDNs provide a new level of network application abstraction to provide a level of quality of service. The purpose of the work is to develop a scientific approach to the study of multipath routing and load balancing in the SDNs based on the bird migration algorithm (BMA). The article studies and analyzes the bird migration algorithm to solve the problem of multipath routing in the SDNs. A visual software system SDNLoadBalancer has been developed and an experimental SDN topology has been designed, which makes it possible to study in detail the processes of multipath routing in the SDNs based on the proposed approach. The article also compares the proposed approach with the results of the genetic algorithm and the artificial bee colony algorithm. The obtained results show the effectiveness of the proposed approach in the SDNs, made it possible to obtain results close to optimal in an acceptable time, and also reduce the transmission delay jitter in the network.

关键词： Visualization software algorithms Birds Routing Load management software systems Artificial bee colony algorithm

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Validation Experiment of a Single-View Image-Sequence Algorithm to Identify Scale and Sea-State Characteristics

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IEEE JOURNAL OF OCEANIC ENGINEERING 2021年第3期46卷 864-878页

作者： Lin, Yolanda C. Earls, Christopher J. Cornell Univ Sch Civil & Environm Engn Ithaca NY 14850 USA Univ New Mexico Dept Geog & Environm Studies Albuquerque NM 87131 USA Cornell Univ Ctr Appl Math Ithaca NY 14850 USA

In applied science and engineering contexts, ocean free-surface wave-field characterization is an ongoing research area relevant to many diverse applications. The use of optical means for this characterization, in particular, is an appealing solution due to the promise of relatively high spatial resolution and modest cost (i.e., applying off-the-shelf still cameras or video cameras). This work investigates the validity of a previously published algorithm related to visible-wavelength ocean free-surface wave-field videos. The first part of the algorithm uses the video content to determine scale from a single-perspective, uncalibrated video. The second part of the algorithm applies the video content to determine sea-state characteristics, such as dominant wave period and wavelength. Due to the complications of obtaining well-characterized real-world data sets, algorithms proposed within the literature are not always validated experimentally, but the scientific community relies on the process of verification and validation to build confidence in emerging scientific contributions. This work addresses the need to assess the performance of the existing algorithm through validation experiments. Video recordings of approximate deep-water waves are collected in a controlled indoor environment to experimentally validate the algorithm, and a suite of postprocessing parameters is explored to identify the algorithm's sensitivities for a chosen unit problem. Recommendations for the algorithm parameter selection and an assessment of the algorithm efficacy are offered for researchers interested in the implementation of this algorithm.

关键词： Cameras Image sequences Lighting Sea measurements Standards software algorithms Optical surface waves Image processing image scale sea-state characterization validation experiment wave-field imaging

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A Learn-to-Rank Method for Model-Based Regression Test Case Prioritization

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IEEE ACCESS 2021年 9卷 16365-16382页

作者： Huang, Yechao Shu, Ting Ding, Zuohua Zhejiang Sci Tech Univ Sch Informat Sci & Technol Hangzhou 310018 Peoples R China

Regression testing plays an indispensable role in software maintenance, which refers to retest the software following modifications to determine whether the changes have introduced new faults. However, regression testing requires massive amounts of effort to achieve a high fault detection rate. To address this issue, the test case prioritization technique is used to improve the fault detection rate by adjusting the execution order of test cases. For model-based regression test case prioritization, existing approaches have been developed using the single aspect of model-related information extracted from the previous executed test cases. In this paper, a novel learn-to-rank technique is proposed to prioritize test cases by combining the multidimensional features of Extended Finite State Machine (EFSM) under test to improve fault detection rate. Specifically, our method utilizes the random forest algorithm to combine multiple existing heuristic prioritization methods. Detailed experiments are conducted to evaluate the proposed method's performance in terms of Average Percentage Fault Detected (APFD). The experimental results show that the mean APFD value of our method reaches 0.884 for five subject EFSMs, which is 33.9% higher than the compared methods.

关键词： Testing Unified modeling language software Fault detection software algorithms Monitoring Heuristic algorithms Regression testing model based testing EFSM test case prioritization learn to rank

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algorithms and Data Structures for New Models of Computation

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IT PROFESSIONAL 2021年第1期23卷 9-15页

作者： Black, Paul E. Flater, David Bojanova, Irena Natl Inst Stand & Technol NIST Gaithersburg MD 20899 USA Natl Inst Stand & Technol NIST Informat Technol Lab Software & Syst Div Gaithersburg MD USA

In the early days of computer science, the community settled on a simple standard model of computing and a basic canon of general purpose algorithms and data structures suited to that model. With isochronous computing, heterogeneous multiprocessors, flash memory, energy-aware computing, cache and other anisotropic memory, distributed computing, streaming environments, functional languages, graphics coprocessors, etc., the basic canon of algorithms and data structures is not enough. software developers know of real-world constraints and new models of computation and use them to design effective algorithms and data structures. These constraints motivate the development of elegant algorithms with broad utility. As examples, we present four algorithms that were motivated by specific hardware nuances, but are generally useful: reservoir sampling, majority of a stream, B-heap, and compacting an array in Theta(log n) time.

关键词： Computational Complexity Data Structures Multiprocessing Systems Power Aware Computing Data Structures General Purpose algorithms Isochronous Computing Energy Aware Computing Distributed Computing Reservoir Sampling B Heap X 0398 Log N Time Algorithm Computational Modeling software algorithms Data Structures Data Models software Engineering

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A Comparative Study of Class Rebalancing Methods for Security Bug Report Classification

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IEEE TRANSACTIONS ON RELIABILITY 2021年第4期70卷 1658-1670页

作者： Zheng, Wei Xun, Yuxing Wu, Xiaoxue Deng, Zhi Chen, Xiang Sui, Yulei Northwestern Polytech Univ Natl Engn Lab Integrated Aerosp Ground Ocean Big MIIT Key Lab Big Data Storage & Management Xian 710129 Peoples R China Northwestern Polytech Univ Sch Software Xian 710129 Peoples R China Yangzhou Univ Coll Informat Engn Coll Artificial Intelligence Yangzhou 225127 Jiangsu Peoples R China Northwestern Polytech Univ Sch Comp Sci & Technol Xian 710129 Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong 226019 Peoples R China Univ Technol Sydney Sch Comp Sci Sydney NSW 2007 Australia

Identifying security bug reports (SBRs) accurately from a bug repository can reduce a software product's security risk. However, the class imbalance problem exists for SBR prediction since the number of SBRs is often limited, and this issue has not been thoroughly investigated in previous studies. In our study, we choose six real-world projects of different sizes with over 120 000 bug reports in total as our empirical subjects. We first analyze the impact of the class imbalance issue on SBR prediction and confirm its negative impact on prediction performance. Then we perform a comparative study of six state-of-the-art class rebalancing methods combined with five popular classification algorithms for SBR prediction. By comparing with the baseline method Farsec, using the class rebalancing methods can improve the performance in 78% of cases in the worst case. Moreover, the combination of the Rose and random forest classification algorithm can construct the model with the best performance, which increases the performance by 267% in the best case and 75% on average in terms of F1-score. Finally, we summarize eight main findings based on our empirical studies' results, which can provide guidelines for choosing appropriate class rebalancing methods and classifiers for SBR prediction in practice.

关键词： Computer bugs Security Prediction algorithms Electronic mail software algorithms Predictive models Dimensionality reduction Class imbalance problem class rebalancing methods classification algorithms security bug report (SBRs) classification

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Efficient Projected Frame Padding for Video-Based Point Cloud Compression

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IEEE TRANSACTIONS ON MULTIMEDIA 2021年 23卷 2806-2819页

作者： Li, Li Li, Zhu Liu, Shan Li, Houqiang Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China Univ Missouri Kansas City Dept Comp Sci & Elect Engn Kansas City MO 64110 USA Tencent Amer 661 Bryant St Palo Alto CA 94301 USA

The state-of-the-art 2D-based dynamic point cloud (DPC) compression algorithm is the video-based point cloud compression (V-PCC) developed by the Moving Pictures Experts Group (MPEG). It first projects the DPC patch by patch from 3D to 2D and organizes the projected patches into a video. The video is then efficiently compressed by High Efficiency Video Coding. However, there are many unoccupied pixels that may have a significant influence on the coding efficiency. These unoccupied pixels are currently padded using either the average of 4-neighbors for the geometry or the push-pull algorithm for the color attribute. While these algorithms are simple, the unoccupied pixels are not handled in the most efficient way. In this paper, we divide the unoccupied pixels into two groups: those that should be occupied and those that should not be occupied according to the occupancy map. We then design padding algorithms tailored to each group to improve the rate-distortion performance of the V-PCC reference software, for both the geometry and the color attribute. The first group is the unoccupied pixels that should be occupied according to the block-based occupancy map. We attempt to pad those pixels using the real points in the original DPC to improve the quality of the reconstructed DPC. Additionally, we attempt to maintain the smoothness of each block so as not to negatively influence the video compression efficiency. The second group is the unoccupied pixels that were correctly identified as unoccupied according to the block-based occupancy map. These pixels are useless for improving the reconstructed quality of the DPC. Therefore, we attempt to minimize the bit cost of these pixels without considering their reconstruction qualities. The bit cost is determined by the residue of these pixels obtained by subtracting the prediction pixels from the original pixels. Therefore, we propose padding the residue using the average residue of the occupied pixels in order to minimize the

关键词： Three-dimensional displays Geometry software Two dimensional displays Color software algorithms Transform coding Frame padding high efficiency video coding occupancy map point cloud compression video-based point cloud compression

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Time-Respecting Flow Graph Pattern Matching on Temporal Graphs

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2021年第10期33卷 3453-3467页

作者： Gao, Yunjun Zhang, Tianming Qiu, Linshan Linghu, Qingyuan Chen, Gang Zhejiang Univ Coll Comp Sci 38 Zheda Rd Hangzhou 310027 Zhejiang Peoples R China

Graph pattern matching has been extensively investigated on general graphs without time information over decades. Nevertheless, few studies focus on temporal graphs, where a relationship between two vertices takes place at a specific moment and lingers for some time. In this paper, we propose a new notion so-called time-respecting flow graph, in which all paths are time-respecting (i.e., a sequence of contacts with non-decreasing time), and one vertex is distinguished as the root, from which other vertices can be reached via a time-respecting path. Based on this, we explore the problem of time-respecting flow graph pattern matching on temporal graphs. This problem motivates important applications in epidemiology, information diffusion, crime detection, etc. To address it, we present one baseline algorithm as well as two optimized algorithms that utilize several efficient matching strategies and topological sort based technique to boost efficiency. Extensive experimental evaluation using both real and synthetic data sets demonstrates the effectiveness and efficiency of our proposed algorithms. Compared with baseline method, our optimized algorithms could achieve up to three orders of magnitude speedup.

关键词： Pattern matching Computational modeling Diseases Topology Schedules Flow graphs software algorithms Temporal graph pattern matching graph mining algorithm

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PSubCLUS: A Parallel Subspace Clustering Algorithm Based On Spark

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IEEE ACCESS 2021年 9卷 2535-2544页

作者： Wen, Xiao Juan, Hu Anhui Normal Univ Sch Educ Sci Wuhu 241002 Peoples R China Wanjiang Univ Technol Anhui Higher Educ Inst Key Lab Unmanned Aerial Vehicle Dev & Data Applic Maanshan 243000 Peoples R China Wanjiang Univ Technol Maanshan Engn Technol Res Ctr Wireless Sensor Net Maanshan 243000 Peoples R China

Clustering is one of the most important unsupervised machine learning tasks. It is widely used to solve problems of intrusion detection, text analysis, image segmentation etc. Subspace clustering is the most important method for high-dimensional data clustering. In order to solve the problem of parallel subspace clustering for high-dimensional big data, this paper proposes a parallel subspace clustering algorithm based on spark named PSubCLUS which is inspired by SubCLU, a classical subspace clustering algorithm. While Spark is the most popular big data parallel processing platform currently, PSubCLUS uses the Resilient Distributed Datasets (RDD) provided by Spark to store data points in a distributed way. The two main performing stages of this algorithm, one-dimensional subspace clustering and iterative clustering, can be executed in parallel on each worker node of cluster. PSubCLUS also uses a repartition method based on the number of data points to achieve load balancing. Experimental results show that PSubCLUS has good parallel speedup and ideal load balancing effect, which is suitable for solving the parallel subspace clustering of high-dimensional big data.

关键词： Clustering algorithms Sparks Partitioning algorithms Machine learning algorithms Distributed databases Classification algorithms software algorithms Big data applications clustering algorithms parallel

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