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Journal articles on the topic 'Control Flow Graph (CFG)'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Koppel, James, Jackson Kearl, and Armando Solar-Lezama. "Automatically deriving control-flow graph generators from operational semantics." Proceedings of the ACM on Programming Languages 6, ICFP (2022): 742–71. http://dx.doi.org/10.1145/3547648.

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We develop the first theory of control-flow graphs from first principles, and use it to create an algorithm for automatically synthesizing many variants of control-flow graph generators from a language’s operational semantics. Our approach first introduces a new algorithm for converting a large class of small-step operational semantics to an abstract machine. It next uses a technique called ”abstract rewriting” to automatically abstract the semantics of a language, which is used both to directly generate a CFG from a program (”interpreted mode”) and to generate standalone code, similar to a hu

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Qiu, Dehong, Jialin Sun, and Hao Li. "Improving Similarity Measure for Java Programs Based on Optimal Matching of Control Flow Graphs." International Journal of Software Engineering and Knowledge Engineering 25, no. 07 (2015): 1171–97. http://dx.doi.org/10.1142/s0218194015500229.

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Measuring program similarity plays an important role in solving many problems in software engineering. However, because programs are instruction sequences with complex structures and semantic functions and furthermore, programs may be obfuscated deliberately through semantics-preserving transformations, measuring program similarity is a difficult task that has not been adequately addressed. In this paper, we propose a new approach to measuring Java program similarity. The approach first measures the low-level similarity between basic blocks according to the bytecode instruction sequences and t

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Kapoor, Akshay, and Sunita Dhavale. "Control Flow Graph Based Multiclass Malware Detection Using Bi-normal Separation." Defence Science Journal 66, no. 2 (2016): 138. http://dx.doi.org/10.14429/dsj.66.9701.

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<p>Control flow graphs (CFG) and OpCodes extracted from disassembled executable files are widely used for malware detection. Most of the research in static analysis is focused on binary class malware detection which only classifies an executable as benign or malware. To overcome this issue, CFG based multiclass malware detection system that automatically classifies the malware into their respective families is proposed. The use Bi-normal separation (BNS) as a feature scoring metric. Experimental results show that proposed method using BNS outperforms compared to hitherto use technique of

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WANG, XUEXIANG, HANLAI PU, JUN YANG, and LONGXING SHI. "EXTENDED CONTROL FLOW GRAPH BASED PERFORMANCE AND ENERGY CONSUMPTION OPTIMIZATION USING SCRATCH-PAD MEMORY." Journal of Circuits, Systems and Computers 18, no. 04 (2009): 697–711. http://dx.doi.org/10.1142/s0218126609005204.

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A Scratch-Pad memory (SPM) allocation method to improve the performance of a specified application while reducing its energy consumption is presented in this paper. Integrated in the design is an extended control flow graph (ECFG) built directly from the application's instruction flow. The application of the design is transformed into a directed graph that consists of nodes and relationships. Likewise, to provide a solution in decreasing the overhead of moving nodes to SPM, the design is enhanced with a refined greedy algorithm based on ECFG. An experiment is conducted to prove the feasibility

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WONG, W. ERIC, and YU LEI. "REACHABILITY GRAPH-BASED TEST SEQUENCE GENERATION FOR CONCURRENT PROGRAMS." International Journal of Software Engineering and Knowledge Engineering 18, no. 06 (2008): 803–22. http://dx.doi.org/10.1142/s0218194008003878.

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One common approach to test sequence generation for structurally testing concurrent programs involves constructing a reachability graph (RG) and selecting a set of paths from the graph to satisfy some coverage criterion. It is often suggested that test sequence generation methods for testing sequential programs based on a control flow graph (CFG) can also be used to select paths from an RG for testing concurrent programs. However, there is a major difference between these two, as the former suffers from a feasibility problem (i.e., some paths in a CFG may not be feasible at run-time) and the l

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Dong, Kwan Kim. "Enhancing code clone detection using control flow graphs." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3804–12. https://doi.org/10.11591/ijece.v9i5.pp3804-3812.

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Code clones are syntactically or semantically equivalent code fragments of source code. Copy-and-paste programming allows software developers to improve development productivity, but it could produce code clones that can introduce non-trivial difficulties in software maintenance. In this paper, a code clone detection framework is presented with a feature extractor and a clone classifier using deep learning. The clone classifier is trained with true and false clones and then is tested with a test dataset to evaluate the performance of the proposed approach to clone detection. In particular, the

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Qiang, Weizhong, Shizhen Wang, Hai Jin, and Jiangying Zhong. "Fine-Grained Control-Flow Integrity Based on Points-to Analysis for CPS." Security and Communication Networks 2018 (October 17, 2018): 1–11. http://dx.doi.org/10.1155/2018/3130652.

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A cyber-physical system (CPS) is known as a mix system composed of computational and physical capabilities. The fast development of CPS brings new security and privacy requirements. Code reuse attacks that affect the correct behavior of software by exploiting memory corruption vulnerabilities and reusing existing code may also be threats to CPS. Various defense techniques are proposed in recent years as countermeasures to emerging code reuse attacks. However, they may fail to fulfill the security requirement well because they cannot protect the indirect function calls properly when it comes to

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Gao, Hao, Tong Zhang, Songqiang Chen, Lina Wang, and Fajiang Yu. "FUSION: Measuring Binary Function Similarity with Code-Specific Embedding and Order-Sensitive GNN." Symmetry 14, no. 12 (2022): 2549. http://dx.doi.org/10.3390/sym14122549.

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Binary code similarity measurement is a popular research area in binary analysis with the recent development of deep learning-based models. Current state-of-the-art methods often use the pre-trained language model (PTLM) to embed instructions into basic blocks as representations of nodes within a control flow graph (CFG). These methods will then use the graph neural network (GNN) to embed the whole CFG and measure the binary similarities between these code embeddings. However, these methods almost directly treat the assembly code as a natural language text and ignore its code-specific features

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Stiawan, Deris, Somame Morianus Daely, Ahmad Heryanto, Nurul Afifah, Mohd Yazid Idris, and Rahmat Budiarto. "Ransomware Detection Based On Opcode Behavior Using K-Nearest Neighbors Algorithm." Information Technology and Control 50, no. 3 (2021): 495–506. http://dx.doi.org/10.5755/j01.itc.50.3.25816.

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Ransomware is a malware that represents a serious threat to a user’s information privacy. By investigating howransomware works, we may be able to recognise its atomic behaviour. In return, we will be able to detect theransomware at an earlier stage with better accuracy. In this paper, we propose Control Flow Graph (CFG) asan extracting opcode behaviour technique, combined with 4-gram (sequence of 4 “words”) to extract opcodesequence to be incorporated into Trojan Ransomware detection method using K-Nearest Neighbors (K-NN)algorithm. The opcode CFG 4-gram can fully represent the detailed behavi

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Park, Jungsoo, and Souhwan Jung. "Android Adware Detection using Soot and CFG." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 13, no. 4 (2022): 94–104. http://dx.doi.org/10.58346/jowua.2022.i4.006.

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Adware is the most common type of malware. While considered not harmful in nature, it disrupts the user experience and generates unwanted revenue. Adware is also difficult to analyze and detect, therefore it is actively distributed through the Google Play Store. In the case of known adware detection, analysis takes a long time due to prolonged dynamic analysis to reveal Ads, and the result of network traffic analysis is difficult to determine traffic such as multimedia streaming, which results in a high probability of false positives. In this paper, we introduce a method to efficiently detect

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Yu, Zeping, Rui Cao, Qiyi Tang, Sen Nie, Junzhou Huang, and Shi Wu. "Order Matters: Semantic-Aware Neural Networks for Binary Code Similarity Detection." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (2020): 1145–52. http://dx.doi.org/10.1609/aaai.v34i01.5466.

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Binary code similarity detection, whose goal is to detect similar binary functions without having access to the source code, is an essential task in computer security. Traditional methods usually use graph matching algorithms, which are slow and inaccurate. Recently, neural network-based approaches have made great achievements. A binary function is first represented as an control-flow graph (CFG) with manually selected block features, and then graph neural network (GNN) is adopted to compute the graph embedding. While these methods are effective and efficient, they could not capture enough sem

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M., Nandish, Jalesh Kumar, Mohan H. G., and Manjunath Sargur Krishnamurthy. "GraphConvDeep: A Deep Learning Approach for Enhancing Binary Code Similarity Detection using Graph Embeddings." International Journal of Computer Network and Information Security 17, no. 3 (2025): 72–88. https://doi.org/10.5815/ijcnis.2025.03.05.

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Binary code similarity detection (BCSD) is a method for identifying similarities between two or more slices of binary code (machine code or assembly code) without access to their original source code. BCSD is often used in many areas, such as vulnerability detection, plagiarism detection, malware analysis, copyright infringement and software patching. Numerous approaches have been developed in these areas via graph matching and deep learning algorithms. Existing solutions have low detection accuracy and lack cross-architecture analysis. This work introduces a cross-platform graph deep learning

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Liu, Guangming, Xin Zhou, Jianmin Pang, Feng Yue, Wenfu Liu, and Junchao Wang. "Codeformer: A GNN-Nested Transformer Model for Binary Code Similarity Detection." Electronics 12, no. 7 (2023): 1722. http://dx.doi.org/10.3390/electronics12071722.

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Binary code similarity detection is used to calculate the code similarity of a pair of binary functions or files, through a certain calculation method and judgment method. It is a fundamental task in the field of computer binary security. Traditional methods of similarity detection usually use graph matching algorithms, but these methods have poor performance and unsatisfactory effects. Recently, graph neural networks have become an effective method for analyzing graph embeddings in natural language processing. Although these methods are effective, the existing methods still do not sufficientl

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Kim, Dong Kwan. "Enhancing code clone detection using control flow graphs." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3804. http://dx.doi.org/10.11591/ijece.v9i5.pp3804-3812.

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Code clones are syntactically or semantically equivalent code fragments of source code. Copy-and-paste programming allows software developers to improve development productivity, but it could produce code clones that can introduce non-trivial difficulties in software maintenance. In this paper, a code clone detection framework is presented with a feature extractor and a clone classifier using deep learning. The clone classifier is trained with true and false clones and then is tested with a test dataset to evaluate the performance of the proposed approach to clone detection. In particular, the

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Althunibat, Ahmed, Mustafa Mahmood, Hend Alnuhait, Sally Almanasra, and Haneen A. Al-Khawaja. "Proposed Test Case Generation Model using Fuzzy Logic (TCGMFL)." WSEAS TRANSACTIONS ON COMPUTER RESEARCH 12 (November 22, 2023): 161–72. http://dx.doi.org/10.37394/232018.2024.12.16.

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This research addresses the pressing need to enhance software testing, specifically focusing on white-box testing and basis path generation. Software testing is a linchpin in the software development process, ensuring software operates flawlessly and aligns with its intended objectives. However, this phase often incurs substantial time and resource investments. The primary aim of this study is to introduce an efficient and automated approach for basis path generation, a crucial component of white-box testing. The model commences by transforming source code into a tailored control flow graph (C

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Tauner, Stefan, and Mario Telesklav. "Comparative Analysis and Enhancement of CFG-based Hardware-Assisted CFI Schemes." ACM Transactions on Embedded Computing Systems 20, no. 5s (2021): 1–25. http://dx.doi.org/10.1145/3476989.

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Subverting the flow of instructions (e.g., by use of code-reuse attacks) still poses a serious threat to the security of today’s systems. Various control flow integrity (CFI) schemes have been proposed as a powerful technique to detect and mitigate such attacks. In recent years, many hardware-assisted implementations of CFI enforcement based on control flow graphs (CFGs) have been presented by academia. Such approaches check whether control flow transfers follow the intended CFG by limiting the valid target addresses. However, these papers all target different platforms and were evaluated with

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Yang, Haixin, Zhen Li, and Xinyu Guo. "A Novel Source Code Clone Detection Method Based on Dual-GCN and IVHFS." Electronics 12, no. 6 (2023): 1315. http://dx.doi.org/10.3390/electronics12061315.

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Source code clone detection, which can identify code fragments with similar functions, plays a significant role in software development and quality assurance. Existing methods either extract single syntactic or semantic information, or ignore the associated information between code statements in different structures. It is difficult for these methods to effectively detect clone pairs with similar functions. In this paper, we propose a new model based on a dual graph convolutional network (GCN) and interval-valued hesitant fuzzy set (IVHFS), which we named DG-IVHFS. Specifically, we simplified

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Lee, Sungbin, and Jeonghun Cho. "ACE-M: Automated Control Flow Integrity Enforcement Based on MPUs at the Function Level." Electronics 11, no. 6 (2022): 912. http://dx.doi.org/10.3390/electronics11060912.

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Control-flow integrity(CFI) ensures that the execution flow of a program follows the control-flow graph(CFG) determined at compile time. CFI is a security technique designed to prevent runtime attacks such as return-oriented programming (ROP). With the development of the Internet of Things (IoT), the number of embedded devices has increased, and security and protection techniques in embedded systems have become important. Since the hardware-based CFI technique requires separate hardware support, it is difficult to apply to an embedded device that is already arranged. In this paper, we propose

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Yang, Zhao Hong, Qing Xiao, Yun Zhan Gong, Da Hai Jin, and Ya Wen Wang. "The Research of an Abstract Semantic Framework for Defect Detecting." Advanced Materials Research 186 (January 2011): 536–40. http://dx.doi.org/10.4028/www.scientific.net/amr.186.536.

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This paper proposes a non-relational abstract semantic framework. It uses interval set to represent the value of numerical variables and complete lattice to represent Boolean variables and reference variables. It presents the abstract computation method of basic expressions and the nodes of control flow graph. It uses function summaries to represent the context information of function call needed by defects detecting. Based on the results of abstract computation, it uses extended state machine to define defect patterns and proposes a path-sensitive method based on dataflow analysis to detect d

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Khoshavi, Navid, Hamid Zarandi, and Mohammad Maghsoudloo. "Two control-flow error recovery methods for multithreaded programs running on multi-core processors." Facta universitatis - series: Electronics and Energetics 28, no. 3 (2015): 309–23. http://dx.doi.org/10.2298/fuee1503309k.

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This paper presents two control-flow error recovery techniques, CFE Recovery using Data-flow graph Consideration and CFE Recovery using Macro block-level Check pointing. These techniques are proposed with regards to thread interactions in the programs. These techniques try to moderate the high memory and performance overheads of conventional control-flow checking techniques. The proposed recovery techniques are composed of two phases of control-flow error detection and recovery. These phases are designed by means of inserting additional instructions into program at compile time considering dep

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Setyawan, Moh Arsyad Mubarak, Fajar Pradana, and Bayu Priyambadha. "Pengembangan sistem otomatisasi pembangkitan kasus uji dengan algoritma genetika dan test case generation method." teknologi 10, no. 1 (2020): 1. http://dx.doi.org/10.26594/teknologi.v10i1.1912.

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Pengujian perangkat lunak merupakan salah satu bagian penting dari pembuatan perangkat lunak. Pada pengujian perangkat lunak terdapat pengujian unit. Pengujian unit merupakan proses pengujian komponen yang berfokus untuk memverifikasi unit terkecil pada perancangan perangkat lunak. Pada tahap pengujian unit terdapat proses pembangkitan kasus uji. Selama ini, pembangkitan kasus uji dari suatu kode program dilakukan secara manual se-hingga membutuhkan waktu yang lama. Hal ini dikarenakan banyaknya kemungkinan jalur pada kode sumber yang akan diuji. Dalam penelitian ini dibangun suatu sistem otom

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Liu, Qiang, Wei Zhu, Feng Ma, Xiyu Jia, Yu Gao, and Jun Wen. "Graph attention network-based fluid simulation model." AIP Advances 12, no. 9 (2022): 095114. http://dx.doi.org/10.1063/5.0122165.

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Traditional computational fluid dynamics (CFD) techniques deduce the dynamic variations in flow fields by using finite elements or finite differences to solve partial differential equations. CFD usually involves several tens of thousands of grid nodes, which entail long computation times and significant computational resources. Fluid data are usually irregular data, and there will be turbulence in the flow field where the physical quantities between adjacent grid nodes are extremely nonequilibrium. We use a graph attention neural network to build a fluid simulation model (GAFM). GAFM assigns w

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Zhao, Jingwen, Yanxia Wu, Yan Fu, and Shuyong Liu. "ESfix: An Embedded Program Repair Tool for Effective Removal of Concurrency Defects." Entropy 27, no. 3 (2025): 294. https://doi.org/10.3390/e27030294.

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Embedded programs are not only inseparable from our daily lives but are also widely used in aerospace, medical devices, and other fields that require very high security and stability. The uncertainty and randomness of the large amount of data generated by these systems during operation can be quantified by entropy. Traditional repair methods for concurrency defects may introduce new issues such as deadlocks, original semantic destruction, and high performance overhead. To overcome the limitations of the existing methods and help developers reduce the time and effort spent on fixing software de

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Wang, Zhongru, Yuntao Zhang, Zhihong Tian, et al. "Automated Vulnerability Discovery and Exploitation in the Internet of Things." Sensors 19, no. 15 (2019): 3362. http://dx.doi.org/10.3390/s19153362.

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Recently, automated software vulnerability detection and exploitation in Internet of Things (IoT) has attracted more and more attention, due to IoT’s fast adoption and high social impact. However, the task is challenging and the solutions are non-trivial: the existing methods have limited effectiveness at discovering vulnerabilities capable of compromising IoT systems. To address this, we propose an Automated Vulnerability Discovery and Exploitation framework with a Scheduling strategy, AutoDES that aims to improve the efficiency and effectiveness of vulnerability discovery and exploitation. I

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Gu, Zhenghua, Wenqing Wan, Jundong Xie, and Chang Wu. "Dependency Graph-based High-level Synthesis for Maximum Instruction Parallelism." ACM Transactions on Reconfigurable Technology and Systems 14, no. 4 (2021): 1–15. http://dx.doi.org/10.1145/3468875.

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Performance optimization is an important goal for High-level Synthesis (HLS). Existing HLS scheduling algorithms are all based on Control and Data Flow Graph (CDFG) and will schedule basic blocks in sequential order. Our study shows that the sequential scheduling order of basic blocks is a big limiting factor for achievable circuit performance. In this article, we propose a Dependency Graph (DG) with two important properties for scheduling. First, DG is a directed acyclic graph. Thus, no loop breaking heuristic is needed for scheduling. Second, DG can be used to identify the exact instruction

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Kar, Santosh Kumar, Brojo Kishore Mishra, and Sanjit Kumar Acharya. "Refurbishment of object-oriented code: A methodical approach to minimize program complexity." Journal of Decision Analytics and Intelligent Computing 5, no. 1 (2025): 52–69. https://doi.org/10.31181/jdaic10018052025k.

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In order to determine software testing competence, test coverage analysis techniques are commonly implemented. The uncovered areas or statements of a program are identified using a technique that employs a set of test cases best suited for the program. Depending on the current approach or the complexity of the program, the concept of test coverage is especially useful in identifying and eliminating test cases that do not contribute significantly to achieving the desired output. In other words, this technique helps in making a program more robust and error-free. It is also useful for identifyin

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Wasiur, Rhmann*1 Gufran Ansari2. "APPLICATION OF CLONAL SELECTION ALGORITHM IN SOFTWARE TEST DATA GENERATION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 7 (2017): 452–59. https://doi.org/10.5281/zenodo.829221.

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This paper presents an artificial immune system (AIS) based optimized test data generation technique. Software test data generation is a critical activity in software testing. Redundant test data impose an extra cost in form of more testing and increase in efforts. So the generation of effective test data can save time and efforts spent on extra testing of the software. Optimized test data is generated for critical paths of the program. Paths criticality is defined based on the presence of loops and decision. The clonal selection algorithm is an immune system based machine learning algorithm a

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Xu, Luhang, Liangze Yin, Wei Dong, Weixi Jia, and Yongjun Li. "Expediting Binary Fuzzing with Symbolic Analysis." International Journal of Software Engineering and Knowledge Engineering 28, no. 11n12 (2018): 1701–18. http://dx.doi.org/10.1142/s0218194018400247.

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Fuzzing is an important method for binary vulnerability mining. It can analyze binary programs without their source codes, which is not easy to do by other technologies. But due to the blindness of input generation, binary fuzzing often falls into traps for a long time when the new mutated inputs cannot generate unexplored paths. In this paper, we propose an efficient and flexible fuzzing framework named Tinker. It defines the growth rate of path coverage to measure the current state of fuzzing. If the fuzzing falls into low-speed or blocked states, a symbolic analysis procedure is invoked to

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Liu, Chang Yun, Xue Zeng Zhao, and Fang Chen. "Application of Numerical Simulation in Analysis and Optimization of Constant Flux Blanking Plug." Materials Science Forum 532-533 (December 2006): 765–68. http://dx.doi.org/10.4028/www.scientific.net/msf.532-533.765.

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The constant flux blanking plug is a downhole flow control device used in the separate layer water injection system of oil-field, its flow characteristic and reliability are the most important matters that people care about. So these performances of the constant flux blanking plug are analyzed by numerical methods here. The dynamic model of the constant flux blanking plug is established by bond-graph, then the simulation is made by the 20-SIM software. The influence of local flow field is studied by CFD (computational fluid dynamics), with which some different valve spools and pockets are comp

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Riyadhthusollehan Khairulfuaad, Norzelawati Asmuin, Juntakan Taweekun, Azizan Ismail, and Nabil Izzuddin Shahhidan. "CFD Analysis for Valve-Holding Camber Permanent Inhaler Spacer (AerospaAcer) with Different Valves." CFD Letters 16, no. 6 (2024): 53–67. http://dx.doi.org/10.37934/cfdl.16.6.5367.

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During the COVID-19 pandemic, data statistics showed that patients with respiratory problems become infected. One of the therapy techniques for the respiratory condition was the use of a metered-dose inhaler and spacer. The objective of this paper is to determine the flow parameters of three types of valves which is duckbill valve, cross slit valve and umbrella valve in inhaler spacer to compare fluid flow between valve Previous researchers chose the duckbill valve to control fluid flow in inhaler spacer. The flow characteristics are unaffected by the materials used in the new disposable inhal

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Chumpol, Surachate, Panadda Solod, Krerkchai Thongnoo, and Nattha Jindapetch. "Model-Based Design Optimization using CDFG for Image Processing on FPGA." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 17, no. 4 (2023): 479–87. http://dx.doi.org/10.37936/ecti-cit.2023174.252417.

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As the automotive industry moves toward autonomous driving and ADAS (Advanced Driver Assistance Systems), Model-Based Design (MBD) is a practical design methodology. It can be used to develop rapid prototyping by using MATLAB and Simulink. The MBD method still has limitations for handling complex models. This paper uses the Control Data Flow Graph (CDFG), an intermediate representation for analyzing complex algorithms, so that suitable optimizations for image processing applications can be implemented on an FPGA. The experimental results show that the proposed CDFG method improved both the are

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Zivkovic, Vladimir, der van, Ed Deprettere, and Kock de. "A new approach for system-level architecture exploration." Facta universitatis - series: Electronics and Energetics 16, no. 1 (2003): 103–14. http://dx.doi.org/10.2298/fuee0301103z.

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In this paper, we present a new design-space exploration approach which we call the symbolic program approach. The symbolic program approach is based on both the trace driven approach and the control data flow graph approach. As expected, the trajectory of the symbolic program approach appears somewhere in-between the two extremes mentioned above. Thus, it leads to the shorter simulation time while it can still give fairly accurate performance numbers. Moreover, it produces results that can be readily taken as input for further design. Keywords: System-level, design-space exploration traces, C

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Fukuda, Kazumasa, and Haruaki Tamada. "To Prevent Reverse-Enginnering Tools by Shuffling the Stack Status with Hook Mechanism." International Journal of Software Innovation 3, no. 3 (2015): 14–25. http://dx.doi.org/10.4018/ijsi.2015070102.

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In this paper, we propose an obfuscation method to shuffle the stack status for preventing illegal analysis from crackers. Generally, crackers tries building a call flow graph of a program to clarify its behaviors. The call flow graph represents relations among methods, and helps comprehension of a program. On the other hand, a callee is fixed by a method name and the stack status in object oriented languages. Then, changing a stack status causes changing a callee when the callee is overloaded. Therefore, we focus on a hook mechanism to change a callee at runtime by changing the stack status.

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M, Thillai Rani, Rajkumar R, Sai Pradeep K.P, Jaishree M, and Rahul S.G. "Integrated extreme gradient boost with c4.5 classifier for high level synthesis in very large scale integration circuits." ITM Web of Conferences 56 (2023): 01005. http://dx.doi.org/10.1051/itmconf/20235601005.

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High-level synthesis (HLS) is utilized for high-performance and energy-efficient heterogeneous systems designing. HLS is assist in field-programmable gate array circuits designing where hardware implementations are refined and replaced in target device. However, the power-process-voltage-temperature-delay (PPVTD) variation in VLSI circuits undergoes many problems and reduced the performance. In order to address these problems, C4.5 with eXtreme Gradient Boosting Classification based High Level Synthesis (C4.5-XGBCHLS) Method is designed for afford better runtime adaptability (RA) with minimal

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Vershkov, V. A., B. S. Kritsky, and R. M. Mirgazov. "FEATURES OF MODELING THE FLOW AROUND THE HELICOPTER MAIN ROTOR TAKING INTO ACCOUNT ARBITRARY BLADES MOTION." Civil Aviation High TECHNOLOGIES 22, no. 3 (2019): 25–34. http://dx.doi.org/10.26467/2079-0619-2019-22-3-25-34.

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The article considers the problem of the flow around the helicopter main rotor taking into account blades flapping in the plane of rotation and in the plane of thrust as well as the elastic blades deformation. The rotor rotation is modeled by the method of converting Navier-Stokes equations from a fixed coordinate system associated with the incoming flow into a rotating system associated with the rotor hub. For axial flow problems, this makes it possible to formulate the problem as stationary at a constant rotational speed of rotor. For a mode of skewed flow around the rotor in the terms of in

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Wang, Feng Qin, and Heng Jin Ke. "Control Flow Analyze for Procedure Blueprint." Applied Mechanics and Materials 58-60 (June 2011): 1061–66. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1061.

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Based on the well-defined UML2.0 activity diagram, a meta-model based on Control Flow Diagram is presented. And our strategy in this article is to define an OCL-based mapping in a formal and verifiable form as consistency rules between an AISD and a CFG, so as to ensure the completeness of our meta-models and allow their verification. At last, we adopt a static analyze method to transform procedure blueprint to Control Flow diagram.

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Gan, Vincent J. L., Han Luo, Yi Tan, Min Deng, and H. L. Kwok. "BIM and Data-Driven Predictive Analysis of Optimum Thermal Comfort for Indoor Environment." Sensors 21, no. 13 (2021): 4401. http://dx.doi.org/10.3390/s21134401.

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Mechanical ventilation comprises a significant proportion of the total energy consumed in buildings. Sufficient natural ventilation in buildings is critical in reducing the energy consumption of mechanical ventilation while maintaining a comfortable indoor environment for occupants. In this paper, a new computerized framework based on building information modelling (BIM) and machine learning data-driven models is presented to analyze the optimum thermal comfort for indoor environments with the effect of natural ventilation. BIM provides geometrical and semantic information of the built environ

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Jang, Hyerean, Moon Chan Park, and Dong Hoon Lee. "IBV-CFI: Efficient fine-grained control-flow integrity preserving CFG precision." Computers & Security 94 (July 2020): 101828. http://dx.doi.org/10.1016/j.cose.2020.101828.

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Gautam, Pratiksha, and Hemraj Saini. "Non-Trivial Software Clone Detection Using Program Dependency Graph." International Journal of Open Source Software and Processes 8, no. 2 (2017): 1–24. http://dx.doi.org/10.4018/ijossp.2017040101.

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Code clones are copied fragments that occur at different levels of abstraction and may have different origins in a software system. This article presents an approach which shows the significant parts of source code. Further, by using significant parts of a source code, a control flow graph can be generated. This control flow graph represents the statements of a code/program in the form of basic blocks or nodes and the edges represent the control flow between those basic blocks. A hybrid approach, named the Program Dependence Graph (PDG) is also presented in this article for the detection of no

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Jin, Da Hai, Yun Zhan Gong, Zhao Hong Yang, Qing Xiao, and Chuan Chang Liu. "A Method of Software Static Testing in the Presence of Runtime Exception." Applied Mechanics and Materials 63-64 (June 2011): 789–94. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.789.

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Control flow graph plays an important role in software static testing based on defect patterns, while the impact of runtime exception on control flow graph is not negligible. After the runtime exception control flow graph and exception pattern Finite State Machine were defined, an algorithm for fault detection in the presence of runtime exception was proposed. Basing on FSM for exception pattern, the feasible states and its condition are iterated along the node of control flow graph, while the abnormal status, which can throw a runtime exception, will be added into control flow graph as an edg

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Xu, Pei, Yuxiang Lei, Yulei Sui, and Jingling Xue. "Iterative-Epoch Online Cycle Elimination for Context-Free Language Reachability." Proceedings of the ACM on Programming Languages 8, OOPSLA1 (2024): 1437–62. http://dx.doi.org/10.1145/3649862.

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Context-free language reachability (CFL-reachability) is a fundamental framework for implementing various static analyses. CFL-reachability utilizes context-free grammar (CFG) to extend the expressiveness of ordinary graph reachability from an unlabeled graph to an edge-labeled graph. Solving CFL-reachability requires a (sub)cubic time complexity with respect to the graph size, which limits its scalability in practice. Thus, an approach that can effectively reduce the graph size while maintaining the reachability result is highly desirable. Most of the existing graph simplification techniques

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Roghair, Ivo. "Advanced Numerical Tools for Chemical Process Intensification: Innovations in 3D Printing, Membrane Reactors, and Bubble Dynamics." Resúmenes de Mecánica Computacional 1, no. 3 (2024): 29. https://doi.org/10.70567/rmc.v1i3.146.

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Chemical process intensification (CPI) is concerned with making innovations for chemical processes to make them smaller and faster, and more sustainable and efficient. Typically, CPI aims for utilizing and enforcing a synergy of the different chemical-physical processes in a reactor and involves a deep understanding of the reactor behavior and being able to control the different aspects of the reactor system. We therefore work on the development of digital twins for various reactor system types, along with experimental validation and verification. In this talk, I will give an overview of the n

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Bobrovnikova, Kira, Sergii Lysenko, Bohdan Savenko, Piotr Gaj, and Oleg Savenko. "Technique for IoT malware detection based on control flow graph analysis." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 1 (February 23, 2022): 141–53. http://dx.doi.org/10.32620/reks.2022.1.11.

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The Internet of Things (IoT) refers to the millions of devices around the world that are connected to the Internet. Insecure IoT devices designed without proper security features are the targets of many Internet threats. The rapid integration of the Internet into the IoT infrastructure in various areas of human activity, including vulnerable critical infrastructure, makes the detection of malware in the Internet of Things increasingly important. Annual reports from IoT infrastructure cybersecurity companies and antivirus software vendors show an increase in malware attacks targeting IoT infras

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Buss, Armands, Arturs Suleiko, Normunds Jekabsons, Juris Vanags, and Dagnija Loca. "Constraint Handling and Flow Control in Stirred Tank Bioreactors with Magnetically Coupled Impellers." Materials Science Forum 1071 (October 18, 2022): 189–96. http://dx.doi.org/10.4028/p-w35yei.

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In this study, Computational Fluid Dynamics (CFD), applied to a non-Newtonian fluid, was developed to characterize gas-liquid interaction and mixing process in a 15 m3 (working volume) bioreactor. The bioreactor was equipped with four arrangements of standard Rushton, Pitch-blade and Scaba® impellers. Gas-liquid hydrodynamics was estimated based on CFD results. The chosen operating conditions were defined by the settings used for production of xanthan gum via fermentation route by Xanthomonas campestris. The mixing process was simulated by using the k-epsilon turbulence model, Multiple Referen

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Alam, Shahid, Issa Traore, and Ibrahim Sogukpinar. "Annotated Control Flow Graph for Metamorphic Malware Detection." Computer Journal 58, no. 10 (2014): 2608–21. http://dx.doi.org/10.1093/comjnl/bxu148.

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Shao, Jun Peng, Jian Ying Li, Zhong Wen Wang, and Gui Hua Han. "Research on Electro-Hydraulic Load Simulator Based on Building Model of Flow Press Servo Valve." Advanced Materials Research 129-131 (August 2010): 213–17. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.213.

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The model of flow press servo valve is built in this paper, during building the model, the author emphatically analyses the flow equation and force (torque) balance equation of every part of the valve, at the same time, all levels sub-models are organic combined according to power flow direction, signal flow direction of elements and causality, then we get the bond graph model of the flow press servo from this way. Adapting flow press servo valve and flow servo valve to concurrently control load system has its great advantage in restraining the superfluous force of the electro-hydraulic load s

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Conrado, Giovanna Kobus, Amir Kafshdar Goharshady, and Chun Kit Lam. "The Bounded Pathwidth of Control-Flow Graphs." Proceedings of the ACM on Programming Languages 7, OOPSLA2 (2023): 292–317. http://dx.doi.org/10.1145/3622807.

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Pathwidth and treewidth are standard and well-studied graph sparsity parameters which intuitively model the degree to which a given graph resembles a path or a tree, respectively. It is well-known that the control-flow graphs of structured goto-free programs have a tree-like shape and bounded treewidth. This fact has been exploited to design considerably more efficient algorithms for a wide variety of static analysis and compiler optimization problems, such as register allocation, µ-calculus model-checking and parity games, data-flow analysis, cache management, and liftetime-optimal redundancy

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Sen, A. K. "Metabolic control analysis. An application of signal flow graphs." Biochemical Journal 269, no. 1 (1990): 141–47. http://dx.doi.org/10.1042/bj2690141.

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In this paper the method of signal-flow graphs is used for calculating the Control Coefficients of metabolic pathways in terms of enzyme elasticities. The method is applied to an unbranched pathway (a) without feedback or feedforward regulation and (b) with feedback inhibition of the first enzyme by the last variable metabolite. It is shown that, by using a signal-flow graph, the control structure of a metabolic pathway can be represented in a graphical manner directly from the configuration of the pathway, without the necessity of writing the governing equations in a matrix form. From a signa

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Ran, Longyan, Yunhe Cui, Jianpeng Zhao, and Hongzhen Yang. "TITAN: Combining a bidirectional forwarding graph and GCN to detect saturation attack targeted at SDN." PLOS ONE 19, no. 4 (2024): e0299846. http://dx.doi.org/10.1371/journal.pone.0299846.

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The decoupling of control and forwarding layers brings Software-Defined Networking (SDN) the network programmability and global control capability, but it also poses SDN security risks. The adversaries can use the forwarding and control decoupling character of SDN to forge legitimate traffic, launching saturation attacks targeted at SDN switches. These attacks can cause the overflow of switch flow tables, thus making the switch cannot forward benign network traffic. How to effectively detect saturation attack is a research hotspot. There are only a few graph-based saturation attack detection m

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Gao, Yun, Hirokazu Hasegawa, Yukiko Yamaguchi, and Hajime Shimada. "Malware Detection by Control-Flow Graph Level Representation Learning With Graph Isomorphism Network." IEEE Access 10 (2022): 111830–41. http://dx.doi.org/10.1109/access.2022.3215267.

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