• Title/Summary/Keyword: Repair Algorithm

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Applying SeqGAN Algorithm to Software Bug Repair (소프트웨어 버그 정정에 SeqGAN 알고리즘을 적용)

  • Yang, Geunseok;Lee, Byungjeong
    • Journal of Internet Computing and Services
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    • v.21 no.5
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    • pp.129-137
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    • 2020
  • Recently, software size and program code complexity have increased due to application to various fields of software. Accordingly, the existence of program bugs inevitably occurs, and the cost of software maintenance is increasing. In open source projects, developers spend a lot of debugging time when solving a bug report assigned. To solve this problem, in this paper, we apply SeqGAN algorithm to software bug repair. In detail, the SeqGAN model is trained based on the source code. Open similar source codes during the learning process are also used. To evaluate the suitability for the generated candidate patch, a fitness function is applied, and if all test cases are passed, software bug correction is considered successful. To evaluate the efficiency of the proposed model, it was compared with the baseline, and the proposed model showed better repair.

Built-In Self Repair for Embedded NAND-Type Flash Memory (임베디드 NAND-형 플래시 메모리를 위한 Built-In Self Repair)

  • Kim, Tae Hwan;Chang, Hoon
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.5
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    • pp.129-140
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    • 2014
  • BIST(Built-in self test) is to detect various faults of the existing memory and BIRA(Built-in redundancy analysis) is to repair detected faults by allotting spare. Also, BISR(Built-in self repair) which integrates BIST with BIRA, can enhance the whole memory's yield. However, the previous methods were suggested for RAM and are difficult to diagnose disturbance that is NAND-type flash memory's intrinsic fault when used for the NAND-type flash memory with different characteristics from RAM's memory structure. Therefore, this paper suggests a BISD(Built-in self diagnosis) to detect disturbance occurring in the NAND-type flash memory and to diagnose the location of fault, and BISR to repair faulty blocks.

Time Series Data Cleaning Method Based on Optimized ELM Prediction Constraints

  • Guohui Ding;Yueyi Zhu;Chenyang Li;Jinwei Wang;Ru Wei;Zhaoyu Liu
    • Journal of Information Processing Systems
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    • v.19 no.2
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    • pp.149-163
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    • 2023
  • Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.

Simultaneous Optimization of Level of Repair and Spare Parts Allocation for MIME Systems under Availability Constraint with Simulation and a Meta-heuristic (가용도 제약하에 시뮬레이션과 메타 휴리스틱을 이용한 MIME 시스템의 수리수준 및 수리부속 할당 동시 최적화)

  • Chung, Il-Han;Yun, Won-Young;Kim, Ho-Gyun
    • Korean Management Science Review
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    • v.26 no.1
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    • pp.209-223
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    • 2009
  • In this paper, an analysis problem of repair levels and spare part allocation for MIME(Multi indenture multi echelon) systems is studied using simulation and meta-heuristics. We suggest a method to determine simultaneously repair levels and spare parts allocation to minimize the life cycle cost of MIME system under availability constraint. A simulated annealing method is used to analyze the repair levels and genetic algorithm is used to obtain the optimal allocation of spare parts. We also develop a simulation system to calculate the life cycle cost and system availability. Some numerical examples are also studied.

An Optimal Preventive Maintenance Policy with General Repair : ($\theta$, m)) Maintenance Policy (일반 수리 모형에서의 최적 예방 보전 정책에 관한 연구 : ($\theta$, m) 보전 정책)

  • Hwang, Jung-Yoon;Park, You-Jin
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.4
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    • pp.9-16
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    • 2009
  • 본 논문에서는 시스템 연령(年齡)에 의해 보전 활동의 효과를 설명하는 일반 수리(修理) 개념을 이용한 최적 보전(保全) 정책에 대한 연구를 수행하였다. 본 논문에서는 주기적인 일반 수리와 고장 시 최소 수리가 적용되는 최적 보전 정책을 고려하였다. 따라서 일반 수리에 따른 보전 정책의 비용 함수를 도출하였고 최적 보전 정책을 도출하는 알고리즘을 제시하였고 예제를 통해 알고리즘의 성능을 분석하였다. 이 연구를 통해 시스템을 운영하는데 있어서 어느 수준의 보전 정책을 적용하며 어느 정도의 기간 동안 시스템을 유지할 것인지에 대안을 제공할 수 있을 것이다.

Islanding Detection Algorithm Based on a Harmonic for Distributed Generators (고조파을 이용한 분산전원 고립운전 검출 알고리즘)

  • Ko C. J.;Kwon Y. J.;Kang S. H
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.301-303
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    • 2004
  • This paper presents an islanding detection algorithm based on the second harmonic. When the DG(distributed Generator) was connected with utility supply, for maintenance and repair of equipment, an islanding occurred. So islanding detection algorithm must be developed for safety of human. Although the DG generating power is similar to power consumption. the proposed algorithm can detect the islanding condition very successfully.

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OAPR-HOML'1: Optimal automated program repair approach based on hybrid improved grasshopper optimization and opposition learning based artificial neural network

  • MAMATHA, T.;RAMA SUBBA REDDY, B.;BINDU, C SHOBA
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.261-273
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    • 2022
  • Over the last decade, the scientific community has been actively developing technologies for automated software bug fixes called Automated Program Repair (APR). Several APR techniques have recently been proposed to effectively address multiple classroom programming errors. However, little attention has been paid to the advances in effective APR techniques for software bugs that are widely occurring during the software life cycle maintenance phase. To further enhance the concept of software testing and debugging, we recommend an optimized automated software repair approach based on hybrid technology (OAPR-HOML'1). The first contribution of the proposed OAPR-HOML'1 technique is to introduce an improved grasshopper optimization (IGO) algorithm for fault location identification in the given test projects. Then, we illustrate an opposition learning based artificial neural network (OL-ANN) technique to select AST node-level transformation schemas to create the sketches which provide automated program repair for those faulty projects. Finally, the OAPR-HOML'1 is evaluated using Defects4J benchmark and the performance is compared with the modern technologies number of bugs fixed, accuracy, precession, recall and F-measure.

Adaptive-and-Resolvable Fractional Repetition Codes Based on Hypergraph

  • Tiantian Wang;Jing Wang;Haipeng Wang;Jie Meng;Chunlei Yu;Shuxia Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1182-1199
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    • 2023
  • Fractional repetition (FR) codes can achieve exact uncoded repair for multiple failed nodes, with lower computational complexity and bandwidth overhead, and effectively improve repair performance in distributed storage systems (DSS). The actual distributed storage system is dynamic, that is, the parameters such as node storage overhead and number of storage nodes will change randomly and dynamically. Considering that traditional FR codes cannot be flexibly applied to dynamic distributed storage systems, a new construction scheme of adaptive-and-resolvable FR codes based on hypergraph coloring is proposed in this paper. Specifically, the linear uniform regular hypergraph can be constructed based on the heuristic algorithm of hypergraph coloring proposed in this paper. Then edges and vertices in hypergraph correspond to nodes and coded packets of FR codes respectively, further, FR codes is constructed. According to hypergraph coloring, the FR codes can achieve rapid repair for multiple failed nodes. Further, FR codes based on hypergraph coloring can be generalized to heterogeneous distributed storage systems. Compared with Reed-Solomon (RS) codes, simple regenerating codes (SRC) and locally repairable codes (LRC), adaptive-and-resolvable FR codes have significant advantages over repair locality, repair bandwidth overhead, computational complexity and time overhead during repairing failed nodes.

Cost-Driven Optimization of Defect-Avoidant Logic Mapping Strategies for Nanowire Reconfigurable Crossbar Architecture (Nanowire Reconfigurable Crossbar 구조를 위한 결함 회피형 로직 재할당 방식의 분석과 총 비용에 따른 최적화 방안)

  • Lee, Jong-Seok;Choi, Min-Su
    • Journal of KIISE:Computer Systems and Theory
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    • v.37 no.5
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    • pp.257-271
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    • 2010
  • As the end of photolithographic integration era is approaching fast, numerous nanoscale devices and systems based on novel nanoscale materials and assembly techniques are recently emerging. Notably, various reconfigurable architectures with considerable promise have been proposed based on nanowire crossbar structure as the primitive building block. Unfortunately, high-density sys-tems consisting of nanometer-scale elements are likely to have numerous physical imperfections and variations. Therefore, defect-tolerance is considered as one of the most exigent challenges in nanowire crossbar systems. In this work, three different defect-avoidant logic mapping algorithms to circumvent defective crosspoints in nanowire reconfigurable crossbar systems are evaluated in terms of various performance metrics. Then, a novel method to find the most cost-effective repair solution is demonstrated by considering all major repair parameters and quantitatively estimating the performance and cost-effectiveness of each algorithm. Extensive parametric simulation results are reported to compare overall repair costs of the repair algorithms under consideration and to validate the cost-driven repair optimization technique.

A Study on the Transition Probability Matrix set from a Transfer Line Model (자동 생산라인 모형에서의 Transition Probability Matrix에 관한 연구)

  • No, Hyeong-Min
    • Journal of Korean Institute of Industrial Engineers
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    • v.11 no.2
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    • pp.1-9
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    • 1985
  • In this study, two stage transfer line with limited repair capability is modeled to formulate optimal dynamic repair priority policy. The method of Markov Chains is used to analyze the analytical model of this line. An efficient algorithm is developed, utilizing the block tridiagonal structure of the transition probability matrix, to obtain the steady state probabilities and system performance measures, such as the steady state production rate of the line and the average in-process inventory in the interstage buffer.

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