CD-Form: A clone detector based on formal methods

Cuomo, Antonio; Santone, Antonella; Villano, Umberto

doi:10.1016/j.scico.2013.11.022

Cited by 9 publications

(5 citation statements)

References 25 publications

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“…They divided the bytecode into three dimensions of instruction, method call and type, and matched the bytecode content by employing a semantic search on the bytecode ontology. CD-Form, proposed by Cuomo et al [16], converted the Java bytecode to the calculus of communicating systems format, and detected code clones on the method level.…”

Section: Related Workmentioning

confidence: 99%

“…The Jaccard similarity coefficient function is adopted to calculate the similarity value in SeByte [14], [15]. In [16], an equivalence-based algorithm is employed to detect code clones. Meanwhile, Koschke et al [11] used the extended algorithm to consider the sequences missed by the basic algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…The reason we only selected them as the benchmark is that they were frequently evaluated by different tools. Meanwhile, we selected nine tools as our block-level experiment baselines because they were employed in experiments by many relevant studies and also evaluated in [12]- [16]. The characteristics of the four systems and nine tools are presented in Tables 2 and 3 respectively.…”

Section: B Experiments Benchmark and Baselinementioning

confidence: 99%

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Detecting Java Code Clones Based on Bytecode Sequence Alignment

Yang

Chen

et al. 2019

IEEE Access

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When the source code is copied and pasted or modified, there will be a lot of identical or similar code snippets in the software system, which are called code clones. Because code clones are believed to result in undesirable maintainability of software, numerous approaches and techniques have been proposed for code clone detection. However, most of them are based on the source code, while only a few employ the bytecode to detect code clones. In this paper, we introduce an approach based on Java bytecode, which mainly contains the steps of bytecode sequence alignment and similarity score comparison. In particular, we apply the Smith-Waterman algorithm to align bytecode sequences for precise matching. Moreover, we separately consider the similarities between instruction sequences and method call sequences, thus improving its effectiveness in detecting code clones. We conducted an extensive experiment on five open-source software to evaluate the proposed approach. The results show that our approach outperforms other state-of-the-art techniques.INDEX TERMS Code clones, code clone detection, Java bytecode, code sequence alignment, code similarities, instruction block, method call sequences.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: B Experiments Benchmark and Baselinementioning

confidence: 99%

See 1 more Smart Citation

Detecting Java Code Clones Based on Bytecode Sequence Alignment

Yang

Chen

et al. 2019

IEEE Access

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“…Approaches in code clone detection generally fall into six categories according to the underlying technique: text-based [25], token-based [26], tree-based [27], graphbased [28], metrics-based [29], and hybrid [30]. Some code clone detection techniques have considered the bytecode as the primary artifact [31]- [33], to detect Type 3 and 4 clones.…”

Section: Related Workmentioning

confidence: 99%

Software Product Line Extraction from Bytecode Based Applications

Ziadi

Hillah

2018

2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS)

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This paper presents a Software Product Line (SPL) extraction approach to handle legacy software systems running on the Java Virtual Machine (JVM), for which the source code is unavailable, and factor in all input programming languages for the JVM. The approach extracts from the bytecode of a collection of software variants created using the Clone-And-Own approach a full SPL with its feature model. We provide a full implementation and integration in the BUT4Reuse framework. An early experiment was carried out on the ArgoUML case study and preliminary results are discussed.

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“…This approach to program verification is also sometimes called implementation verification. Behavioral equivalence can be used also for other purposes, like, for example, for clone detection [Cuomo et al 2013]. …”

Section: Preliminariesmentioning

confidence: 99%

GreASE

Francesco

Lettieri

Santone

et al. 2014

ACM Trans. Softw. Eng. Methodol.

Self Cite

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Equivalence checking plays a crucial role in formal verification to ensure the correctness of concurrent systems. However, this method cannot be scaled as easily with the increasing complexity of systems due to the state explosion problem. This article presents an efficient procedure, based on heuristic search, for checking Milner's strong and weak equivalence; to achieve higher efficiency, we actually search for a difference between two processes to be discovered as soon as possible, thus the heuristics aims to find a counterexample, even if not the minimum one, to prove nonequivalence. The presented algorithm builds the system state graph on-the-fly, during the checking, and the heuristics promotes the construction of the more promising subgraph. The heuristic function is syntax based, but the approach can be applied to different specification languages such as CCS, LOTOS, and CSP, provided that the language semantics is based on the concept of transition. The algorithm to explore the search space of the problem is based on a greedy technique; GreASE (Greedy Algorithm for System Equivalence), the tool supporting the approach, is used to evaluate the achieved reduction of both state-space size and time with respect to other verification environments.

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CD-Form: A clone detector based on formal methods

Cited by 9 publications

References 25 publications

Detecting Java Code Clones Based on Bytecode Sequence Alignment

Detecting Java Code Clones Based on Bytecode Sequence Alignment

Software Product Line Extraction from Bytecode Based Applications

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