Definition, approaches, and analysis of code duplication detection (2006–2020): a critical review

Chen, Chang-Feng; Zain, Azlan Mohd; Zhou, Kai-Qing

doi:10.1007/s00521-022-07707-2

Cited by 7 publications

(3 citation statements)

References 110 publications

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“…The authors concluded that this method has superior performance for structural damage detection of engineering steel beams compared to the SVM method. Furthermore, in Chen et al (2022a), the authors provided a comprehensive review of the techniques for detecting code duplication in software development, analyzing the advantages and disadvantages of each approach.…”

Section: Detection Methodsmentioning

confidence: 99%

Advances on intelligent algorithms for scientific computing: an overview

et al. 2023

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The field of computer science has undergone rapid expansion due to the increasing interest in improving system performance. This has resulted in the emergence of advanced techniques, such as neural networks, intelligent systems, optimization algorithms, and optimization strategies. These innovations have created novel opportunities and challenges in various domains. This paper presents a thorough examination of three intelligent methods: neural networks, intelligent systems, and optimization algorithms and strategies. It discusses the fundamental principles and techniques employed in these fields, as well as the recent advancements and future prospects. Additionally, this paper analyzes the advantages and limitations of these intelligent approaches. Ultimately, it serves as a comprehensive summary and overview of these critical and rapidly evolving fields, offering an informative guide for novices and researchers interested in these areas.

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Section: Detection Methodsmentioning

confidence: 99%

Advances on intelligent algorithms for scientific computing: an overview

et al. 2023

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“…However, when there are large areas or high numbers of moving objects in the environment, there will be too few detectable feature points in the image, which results in inaccurate camera pose estimation. With the recent development of artificial intelligence [10] in diagnosis [11], duplicate checking [12], optimization [13,14], manipulator control [15][16][17], and robots [18,19] etc. As an important branch of artificial intelligence, deep learning has made major breakthroughs in image recognition and natural language processing.…”

Section: Introductionmentioning

confidence: 99%

MOR-SLAM: A New Visual SLAM System for Indoor Dynamic Environments Based on Mask Restoration

Yao,

Ding,

Lan

2023

Mathematics

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The traditional Simultaneous Localization and Mapping (SLAM) systems are based on the strong static assumption, and their performance will degrade significantly due to the presence of dynamic objects located in dynamic environments. To decrease the effects of the dynamic objects, based on the ORB-SLAM2 system, a novel dynamic semantic SLAM system called MOR-SLAM is presented using a mask repair method, which can accurately detect dynamic objects and realize high-precision positioning and tracking of the system in dynamic indoor environments. First, an instance segmentation module is added to the front end of ORB-SLAM2 to distinguish dynamic and static objects in the environment and obtain a preliminary mask. Next, to overcome the under-segmentation problem in instance segmentation, a new mask inpainting model is proposed to ensure that the integrity of object masks, which repairs large objects and small objects in the image with the depth value fusion method and morphological method, respectively. Then, a reliable basic matrix can be obtained based on the above-repaired mask. Finally, the potential dynamic feature points in the environment are detected and removed through the reliable basic matrix, and the remaining static feature points are input into the tracking module of the system to realize the high-precision positioning and tracking in dynamic environments. The experiments on the public TUM dataset show that, compared with ORB-SLAM2, the MOR-SLAM improves the absolute trajectory accuracy by 95.55%. In addition, compared with DynaSLAM and DS-SLAM on the high-dynamic sequences (fr3/w/rpy and fr3/w/static), the MOR-SLAM improves the absolute trajectory accuracy by 15.20% and 59.71%, respectively.

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“…Code clones are multiple identical or similar code fragments that exist in a software system, code repository, etc. Although code clones bring convenience to software development, they affect the iteration and maintenance of software systems negatively [1,2]. Code clones may lead to continuous expansion of software systems and increase maintenance costs [3].…”

Section: Introductionmentioning

confidence: 99%

SJBCD: A Java Code Clone Detection Method Based on Bytecode Using Siamese Neural Network

Wan,

Dong,

Zhou

et al. 2023

Applied Sciences

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Code clone detection is an important research topic in the field of software engineering. It is significant in developing software and solving software infringement disputes to discover code clone phenomenon effectively in and between software systems. In practical engineering applications, clone detection can usually only be performed on the compiled code due to the unavailability of the source code. Additionally, there is room for improvement in the detection effect of existing methods based on bytecode. Based on the above reasons, this paper proposes a novel code clone detection method for Java bytecode: SJBCD. SJBCD extracts opcode sequences from byte code files, use GloVe to vectorize opcodes, and builds a Siamese neural network based on GRU to perform supervised training. Then the trained network is used to detect code clones. In order to prove the effectiveness of SJBCD, this paper conducts validation experiments using the BigCloneBench dataset and provides a comparative analysis with four other methods. Experimental results show the effectiveness of the SJBCD method.

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Definition, approaches, and analysis of code duplication detection (2006–2020): a critical review

Cited by 7 publications

References 110 publications

Advances on intelligent algorithms for scientific computing: an overview

Advances on intelligent algorithms for scientific computing: an overview

MOR-SLAM: A New Visual SLAM System for Indoor Dynamic Environments Based on Mask Restoration

SJBCD: A Java Code Clone Detection Method Based on Bytecode Using Siamese Neural Network

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