Clone-hunter: accelerated bound checks elimination via binary code clone detection

Xue, Hongfa; Venkataramani, Guru; Lan, Tian

doi:10.1145/3211346.3211347

Cited by 18 publications

(7 citation statements)

References 30 publications

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“…[30], [14] use machine learning techniques to identify the similarity of code patterns to facilitate discovery of vulnerabilities. Clone-Hunter [32] and Clone-Slicer [32] aim to detect code clones in program binaries for accelerated bounds check removal. Nurit et.…”

Section: Discussionmentioning

confidence: 99%

CHOP: Bypassing runtime bounds checking through convex hull Optimization

Chen

Xue

Lan

et al. 2020

Computers & Security

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Unsafe memory accesses in programs written using popular programming languages like C/C++ have been among the leading causes for software vulnerability. Prior memory safety checkers such as SoftBound enforce memory spatial safety by checking if every access to array elements are within the corresponding array bounds. However, it often results in high execution time overhead due to the cost of executing the instructions associated with bounds checking. To mitigate this problem, redundant bounds check elimination techniques are needed. In this paper, we propose CHOP, a Convex Hull OPtimization based framework, for bypassing redundant memory bounds checking via profile-guided inferences. In contrast to existing check elimination techniques that are limited by static code analysis, our solution leverages a model-based inference to identify redundant bounds checking based on runtime data from past program executions. For a given function, it rapidly derives and updates a knowledge base containing sufficient conditions for identifying redundant array bounds checking. We evaluate CHOP on real-world applications and benchmark (such as SPEC) and the experimental results show that on average 80.12% of dynamic bounds check instructions can be avoided, resulting in improved performance up to 95.80% over SoftBound.

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Section: Discussionmentioning

confidence: 99%

CHOP: Bypassing runtime bounds checking through convex hull Optimization

Chen

Xue

Lan

et al. 2020

Computers & Security

Self Cite

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“…Code Clone Detection. Tools and techniques of code clone detection can be classified as six categories [8]: textual approaches [10,23,27,34,37,51,56,58], lexical approaches [35,44,45,50,55,59], tree-based approaches [16,36,57], metric-based approaches [38,48,49], semantic approaches [18,19,22,24,43,54] and hybrid approaches [9,20,21,31,32,41,46,53]. In particular, we introduce several works closely related to our work.…”

Section: Related Workmentioning

confidence: 99%

From Innovations to Prospects

Jia

Fan

et al. 2020

Proceedings of the 17th International Conference on Mining Software Repositories

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The great influence of Bitcoin has promoted the rapid development of blockchain-based digital currencies, especially the altcoins, since 2013. However, most altcoins share similar source codes, resulting in concerns about code innovations. In this paper, an empirical study on existing altcoins is carried out to offer a thorough understanding of various aspects associated with altcoin innovations. Firstly, we construct the dataset of altcoins, including source code repository, GitHub fork relation, and market capitalization (cap). Then, we analyze the altcoin innovations from the perspective of source code similarities. The results demonstrate that more than 85% of altcoin repositories present high code similarities. Next, a temporal clustering algorithm is proposed to mine the inheritance relationship among various altcoins. The family pedigrees of altcoin are constructed, in which the altcoin presents similar evolution features as biology, such as power-law in family size, variety in family evolution, etc. Finally, we investigate the correlation between code innovations and market capitalization. Although we fail to predict the price of altcoins based on their code similarities, the results show that altcoins with higher innovations reflect better market prospects. CCS CONCEPTS• Software and its engineering → Software evolution.

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“…Results indicate that type1, type2 and type3 clones are identified. Xue et al [31] describe a novel framework, clone hunter that integrates machine learning based binary CCD to speed up the elimination of redundant array bound checks in binary executables. They utilize assembly code as source code and Feature vectors as an intermediate format.…”

Section: A Textual Approachesmentioning

confidence: 99%

A Systematic Review on Code Clone Detection

et al. 2019

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Code cloning refers to the duplication of source code. It is the most common way of reusing source code in software development. If a bug is identified in one segment of code, all the similar segments need to be checked for the same bug. Consequently, this cloning process may lead to bug propagation that significantly affects the maintenance cost. By considering this problem, code clone detection (CCD) appears as an active area of research. Consequently, there is a strong need to investigate the latest techniques, trends, and tools in the domain of CCD. Therefore, in this paper, we comprehensively inspect the latest tools and techniques utilized for the detection of code clones. Particularly, a systematic literature review (SLR) is performed to select and investigate 54 studies pertaining to CCD. Consequently, six categories are defined to incorporate the selected studies as per relevance, i.e., textual approaches (12), lexical approaches (8), treebased approaches (3), metric-based approaches (7), semantic approaches (7), and hybrid approaches (17). We identified and analyzed 26 CCD tools, i.e., 13 existing and 13 proposed/developed. Moreover, 62 opensource subject systems whose source code is utilized for the CCD are presented. It is concluded that there exist several studies to detect type1, type2, type3, and type4 clones individually. However, there is a need to develop novel approaches with complete tool support in order to detect all four types of clones collectively. Furthermore, it is also required to introduce more approaches to simplify the development of a program dependency graph (PDG) while dealing with the detection of the type4 clones.INDEX TERMS CCD, SLR, code clone detection, CCD tools, code clone types.

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Clone-hunter: accelerated bound checks elimination via binary code clone detection

Cited by 18 publications

References 30 publications

CHOP: Bypassing runtime bounds checking through convex hull Optimization

CHOP: Bypassing runtime bounds checking through convex hull Optimization

From Innovations to Prospects

A Systematic Review on Code Clone Detection

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