CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model

Article


Ullah, F., Naeem, M., Naeem, H., Cheng, X. and Alazab, M. 2022. CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model. International Journal of Intelligent Systems. 37 (9), pp. 5768-5795. https://doi.org/10.1002/int.22813
TypeArticle
TitleCroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model
AuthorsUllah, F., Naeem, M., Naeem, H., Cheng, X. and Alazab, M.
Abstract

Software similarity in different programming codes is a rapidly evolving field because of its numerous applications in software development, software cloning, software plagiarism, and software forensics. Currently, software researchers and developers search cross-language open-source repositories for similar applications for a variety of reasons, such as reusing programming code, analyzing different implementations, and looking for a better application. However, it is a challenging task because each programming language has a unique syntax and semantic structure. In this paper, a novel tool called Cross-Language Software Similarity (CroLSSim) is designed to detect similar software applications written in different programming codes. First, the Abstract Syntax Tree (AST) features are collected from different programming codes. These are high-quality features that can show the abstract view of each program. Then, Methods Description (MDrep) in combination with AST is used to examine the relationship among different method calls. Second, the Term Frequency Inverse Document Frequency approach is used to retrieve the local and global weights from AST-MDrep features. Third, the Latent Semantic Analysis-based features extraction and selection method is proposed to extract the semantic anchors in reduced dimensional space. Fourth, the Convolution Neural Network (CNN)-based features extraction method is proposed to mine the deep features. Finally, a hybrid deep learning model of CNN-Long-Short-Term Memory is designed to detect semantically similar software applications from these latent variables. The data set contains approximately 9.5K Java, 8.8K C#, and 7.4K C++ software applications obtained from GitHub. The proposed approach outperforms as compared with the state-of-the-art methods.

KeywordsArtificial Intelligence, Human-Computer Interaction, Theoretical Computer Science, Software
PublisherWiley
JournalInternational Journal of Intelligent Systems
ISSN0884-8173
Electronic1098-111X
Publication dates
Online09 Jan 2022
Print30 Jul 2022
Publication process dates
Deposited20 Jan 2022
Accepted25 Dec 2021
Output statusPublished
Accepted author manuscript
Copyright Statement

This is the peer reviewed version of the following article: Ullah, F, Naeem, MR, Naeem, H, Cheng, X, Alazab, M. CroLSSim: Cross-language software similarity detector using hybrid approach of LSA-based AST-MDrep features and CNN-LSTM model. Int J Intell Syst. 2022; 37: 5768- 5795. doi:10.1002/int.22813, which has been published in final form at https://doi.org/10.1002/int.22813. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited

Digital Object Identifier (DOI)https://doi.org/10.1002/int.22813
LanguageEnglish
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PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an explainable diagnosis of COVID-19 with multiple-way data augmentation
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Task bundling in worker-centric mobile crowdsensing
Zhao, T., Yang, Y., Wang, E., Mumtaz, S. and Cheng, X. 2021. Task bundling in worker-centric mobile crowdsensing. International Journal of Intelligent Systems. 36 (9), pp. 4936-4961. https://doi.org/10.1002/int.22497
ShadowFPE: new encrypted web application solution based on shadow DOM
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Learning context-aware outfit recommendation
Abugabah, A., Cheng, X. and Wang, J. 2020. Learning context-aware outfit recommendation. Symmetry. 12 (6), pp. 1-13. https://doi.org/10.3390/sym12060873
Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm
Liu, W., Huang, Y., Ye, Z., Cai, W., Yang, S., Cheng, X. and Frank, I. 2020. Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm. Applied Sciences. 10 (9). https://doi.org/10.3390/app10093225
Reliability analysis of an air traffic network: from network structure to transport function
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XOR multiplexing technique for nanocomputers
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Fine-grained action recognition by motion saliency and mid-level patches
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Adaptive dynamic disturbance strategy for differential evolution algorithm
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A game theoretic analysis of resource mining in blockchain
Singh, R., Dwivedi, A., Srivastava, G., Wisznieska-Mayszkiel, A. and Cheng, X. 2020. A game theoretic analysis of resource mining in blockchain. Cluster Computing. 23 (3), pp. 2035-2046. https://doi.org/10.1007/s10586-020-03046-w
Hybridization of cognitive computing for food services
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Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network
Xie, X., Zhang, Z., Wang, J. and Cheng, X. 2019. Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network. Journal on Communications. 40 (8), pp. 143-150. https://doi.org/10.11959/j.issn.1000-436x.2019172
Incremental association rule mining based on matrix compression for edge computing
Zhou, D., Ouyang, M., Kuang, Z., Li, Z., Zhou, J. and Cheng, X. 2019. Incremental association rule mining based on matrix compression for edge computing. IEEE Access. 7, pp. 1730444-173053. https://doi.org/10.1109/ACCESS.2019.2956823
Facial landmark detection via attention-adaptive deep network
Sadiq, M., Shi, D., Guo, M. and Cheng, X. 2019. Facial landmark detection via attention-adaptive deep network. IEEE Access. 7, pp. 181041-181050. https://doi.org/10.1109/ACCESS.2019.2955156
Annual and non-monsoon rainfall prediction modelling using SVR-MLP: an empirical study from Odisha
Yhang, X., Mohanty, S., Parida, A., Pani, S., Dong, B. and Cheng, X. 2020. Annual and non-monsoon rainfall prediction modelling using SVR-MLP: an empirical study from Odisha. IEEE Access. 8, pp. 30223-30233. https://doi.org/10.1109/ACCESS.2020.2972435
A sparse Bayesian learning method for structural equation model-based gene regulatory network inference
Li, Y., Liu, D., Chu, J., Zhu, Y., Liu, J. and Cheng, X. 2020. A sparse Bayesian learning method for structural equation model-based gene regulatory network inference. IEEE Access. 8, pp. 40067-40080. https://doi.org/10.1109/ACCESS.2020.2976743
Micro-distortion detection of lidar scanning signals based on geometric analysis
Liu, S., Chen, X., Li, Y. and Cheng, X. 2019. Micro-distortion detection of lidar scanning signals based on geometric analysis. Symmetry. 11 (12), pp. 2-13. https://doi.org/10.3390/sym11121471
Verifying cryptographic protocols
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Verifying security protocols by knowledge analysis
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A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA
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A security design for cloud computing: an implementation of an on premises authentication with Kerberos and IPSec within a network
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Comparative experiments on resource discovery in P2P networks
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Unbalanced private set intersection cardinality protocol with low communication cost
Lv, S., Ye, J., Yin, S. and Cheng, X. 2020. Unbalanced private set intersection cardinality protocol with low communication cost. Future Generation Computer Systems. 102, pp. 1054-1061. https://doi.org/10.1016/j.future.2019.09.022
Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface
Men, J., Xu, G., Han, Z., Sun, Z., Zhou, X., Lian, W. and Cheng, X. 2019. Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface. IEEE Access. 7, pp. 103751-103759. https://doi.org/10.1109/ACCESS.2019.2931061
Behavior modelling and individual recognition of sonar transmitter for secure communication in UASNs
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Introduction of key problems in long-distance learning and training
Liu, S., Li, Z., Zhang, Y. and Cheng, X. 2019. Introduction of key problems in long-distance learning and training. Mobile Networks and Applications. 24 (1), pp. 1-4. https://doi.org/10.1007/s11036-018-1136-6
Vulnerabilities and limitations of MQTT protocol used between IoT devices
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Imbalanced big data classification based on virtual reality in cloud computing
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Platform of quality evaluation system for multimedia video communication based NS2
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An authentication scheme to defend against UDP DrDoS attacks in 5G networks
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Data provenance with retention of reference relations
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Editorial: Recent advances of content understanding in image and multimedia
Liu, S., Cheng, X. and Min, G. 2017. Editorial: Recent advances of content understanding in image and multimedia. Recent Patents on Computer Science. 10 (1), pp. 2-5. https://doi.org/10.2174/221327591001170808093310
Channel state information-based detection of Sybil attacks in wireless networks
Wang, C., Zhu, L., Gong, L., Zhao, Z., Yang, L., Liu, Z. and Cheng, X. 2018. Channel state information-based detection of Sybil attacks in wireless networks. Journal of Internet Services and Information Security. 8 (1), pp. 2-17. https://doi.org/10.22667/JISIS.2018.02.28.002
Research on trust model in container-based cloud service
Xie, X., Yuan, T., Zhou, X. and Cheng, X. 2018. Research on trust model in container-based cloud service. Computers, Materials and Continua. 56 (2), pp. 273-283. https://doi.org/10.3970/cmc.2018.03587
Introduction of recent advanced hybrid information processing
Liu, S., Li, Z., Cheng, X. and Lin, Y. 2018. Introduction of recent advanced hybrid information processing. Mobile Networks and Applications. 23 (4), pp. 673-676. https://doi.org/10.1007/s11036-018-1013-3
Accurate Sybil attack detection based on fine-grained physical channel information
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DivORAM: Towards a practical oblivious RAM with variable block size
Liu, Z., Huang, Y., Li, J., Cheng, X. and Shen, C. 2018. DivORAM: Towards a practical oblivious RAM with variable block size. Information Sciences. 447, pp. 1-11. https://doi.org/10.1016/j.ins.2018.02.071
M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices
Gao, C., Lv, S., Wei, Y., Wang, Z., Liu, Z. and Cheng, X. 2018. M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices. IEEE Access. 6, pp. 38860-38869. https://doi.org/10.1109/ACCESS.2018.2852329
A distributed anomaly detection system for in-vehicle network using HTM
Wang, C., Zhao, Z., Gong, L., Zhu, L., Liu, Z. and Cheng, X. 2018. A distributed anomaly detection system for in-vehicle network using HTM. IEEE Access. 6, pp. 9091-9098. https://doi.org/10.1109/ACCESS.2018.2799210
Crime pattern recognition based on high-performance computing
Eissa, A., Cheng, X. and Petridis, M. 2018. Crime pattern recognition based on high-performance computing. 2017 International Conference Next Generation Community Policing. Heraklion, Crete, Greece 25 - 27 Oct 2017
A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface
Liu, S., Pan, Z. and Cheng, X. 2017. A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface. Fractals. 25 (04), pp. 1740004-1-11. https://doi.org/10.1142/s0218348x17400047
Degradation and encryption for outsourced PNG images in cloud storage
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Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud
Xie, X., Liu, R., Cheng, X., Hu, X. and Ni, J. 2016. Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud. Intelligent Automation & Soft Computing: An International Journal . 22 (4), pp. 561-566.
Numeric characteristics of generalized M-set with its asymptote
Liu, S., Cheng, X., Fu, W., Zhou, Y. and Li, Q. 2014. Numeric characteristics of generalized M-set with its asymptote. Applied Mathematics and Computation. 243, pp. 767-774. https://doi.org/10.1016/j.amc.2014.06.016
Local semantic indexing for resource discovery on overlay network using mobile agents
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Fractal property of generalized M-set with rational number exponent
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Mechanical verification of cryptographic protocols
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DNSsec in Isabelle – replay attack and origin authentication
Kammueller, F., Kirsal-Ever, Y. and Cheng, X. 2013. DNSsec in Isabelle – replay attack and origin authentication. SMC 2013: IEEE International Conference on Systems, Man, and Cybernetics. Manchester, UK 13 - 16 Oct 2013 IEEE. pp. 4772-4777 https://doi.org/10.1109/SMC.2013.812
A cooperative particle swarm optimizer with statistical variable interdependence learning
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Survey of grid resource monitoring and prediction strategies.
Hu, L., Cheng, X. and Che, X. 2010. Survey of grid resource monitoring and prediction strategies. International Journal of Intelligent Information Processing. 1 (2).
Efficient identity-based broadcast encryption without random oracles.
Hu, L., Liu, Z. and Cheng, X. 2010. Efficient identity-based broadcast encryption without random oracles. Journal of Computers. 5 (3), pp. 331-336.
Solving job shop scheduling problem using genetic algorithm with penalty function
Sun, L., Cheng, X. and Liang, Y. 2010. Solving job shop scheduling problem using genetic algorithm with penalty function. International Journal of Intelligent Information Processing. 1 (2), pp. 65-77.
Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization
Cheng, X., Che, X. and Hu, L. 2010. Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization. International Journal of Computational Intelligence Systems. 3 (1), pp. 70-83. https://doi.org/10.2991/ijcis.2010.3.1.7
Resource discovery using mobile agents
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Resource discovery using mobile agents
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New e-Learning system architecture based on knowledge engineering technology
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Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals
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Formal verification of the merchant registration phase of the SET protocol.
Cheng, X. and Ma, X. 2005. Formal verification of the merchant registration phase of the SET protocol. International Journal of Automation and Computing. 2 (2), pp. 155-162. https://doi.org/10.1007/s11633-005-0155-5
Programming style based program partition
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An improved model-based method to test circuit faults
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Topology control of ad hoc wireless networks for energy efficiency
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