Detecting Java Code Clones Based on Bytecode Sequence Alignment

Yu, Dongjin; Yang, Jiazha; Chen, Xin; Chen, Jie

doi:10.1109/access.2019.2898411

Cited by 17 publications

(13 citation statements)

References 23 publications

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“…Yu et al present an approach that detects clones in Java using the Smith-Waterman algorithm on Java bytecode [39]. This approach is only suitable for languages that are translated into Java bytecode.…”

Section: Intra Variant Clone Detection (Classic Clone Detection)mentioning

confidence: 99%

Custom-Tailored Clone Detection for IEC 61131-3 Programming Languages

Rosiak¹,

Schlie²,

Linsbauer³

et al. 2021

Preprint

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Automated production systems (aPS) are highly customized systems that consist of hardware and software. Such aPS are controlled by a programmable logic controller (PLC), often in accordance with the IEC 61131-3 standard that divides system implementation into so-called program organization units (POUs) as the smallest software unit and is comprised of multiple textual (Structured Text (ST)) and graphical (Function Block Diagram (FBD), Ladder Diagram (LD), and Sequential Function Chart(SFC)) programming languages that can be arbitrarily nested.A common practice during the development of such systems is reusing implementation artifacts by copying, pasting, and then modifying code. This approach is referred to as code cloning. It is used on a fine-granular level where a POU is cloned within a system variant. It is also applied on the coarse-granular system level, where the entire system is cloned and adapted to create a system variant, for example for another customer. This ad hoc practice for the development of variants is commonly referred to as clone-and-own. It allows the fast development of variants to meet varying customer requirements or altered regulatory guidelines. However, clone-and-own is a non-sustainable approach and does not scale with an increasing number of variants. It has a detrimental effect on the overall quality of a software system, such as the propagation of bugs to other variants, which harms maintenance.In order to support the effective development and maintenance of such systems, a detailed code clone analysis is required. On the one hand, an analysis of code clones within a variant (i.e., clone detection in the classical sense) supports experts in refactoring respective code into library components. On the other hand, an analysis of commonalities and differences between cloned variants (i.e., variability analysis) supports the maintenance and further reuse and facilitates the migration of variants into a software productline (SPL).In this paper, we present an approach for the automated detection of code clones within variants (intra variant clone detection) and between variants (inter variant clone detection) of IEC61131-3 control software with arbitrary nesting of both textual and graphical languages. We provide an implementation of the approach in the variability analysis toolkit (VAT) as a freely available prototype for the analysis of IEC 61131-3 programs. For the evaluation, we developed a meta-model-based mutation framework to measure our approach's precision and recall. Besides, we evaluated our approach using the Pick and Place Unit (PPU) and Extended Pick and Place Unit (xPPU) scenarios. Results show the usefulness of intra and inter clone detection in the domain of automated production systems.

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Section: Intra Variant Clone Detection (Classic Clone Detection)mentioning

confidence: 99%

Custom-Tailored Clone Detection for IEC 61131-3 Programming Languages

Rosiak¹,

Schlie²,

Linsbauer³

et al. 2021

Preprint

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“…Compared to works on source code level, many works manipulate bytecode, such as libraries categorization [30], software product line extraction [31], code clone [32] and code diversity [33], etc. Mens et al [34] hold the view that the technique for bytecode transformation is compatible with the definition of refactoring, and refactoring can be very useful at an even more implementation dependent level than programming languages, such as refactoring of bytecode, or even refactoring of executable code.…”

Section: B Bytecode Refactoring Vs Source Code Refactoringmentioning

confidence: 99%

Refactoring Java Programs for Customizable Locks Based on Bytecode Transformation

et al. 2019

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Developers of parallel programming are faced with choices of using various Java locks. Choosing the best lock is a challenging task because a multithreaded application implemented using different locks may end up with uncertain performance. There is a strong need for automated tool support that helps Java programmers choose the best lock for each specific application. This paper presents an automated transformation approach to convert an implementation using a synchronized lock to a ReentrantLock or a ReentrantReadWriteLock at the bytecode level. For the ReentrantLock, our approach runs analysis for global monitors using the visitor pattern in the Joeq compiler. For the ReentrantReadWriteLock, a read or write lock is chosen after a side-effect analysis. Then, the proposed system validates the consistency of the analysis results to ensure a correct sequence of lock usage. Finally, lock operations and related thread communication operations are transformed into a ReentrantLock or a ReentrantReadWriteLock using a bytecode transformation framework Javassist. We validate our approach on several benchmarks including RBTree, PC, SPECjbb2005, and HSQLDB. The experimental results show that the proposed automated transformation approach can transform these benchmarks successfully in a timely fashion.

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“…The Smith-Waterman algorithm is parameter sensitive, specifically, for the following parameters: p, q, W 1 . Previous work [20], [21] set these three parameters to static fixed values, which caused the Smith-Waterman algorithm to lose similar regions between sequences in some cases. We explain this with the following example.…”

Section: ) Dynamic Parameter Acquisition Strategymentioning

confidence: 99%

“…Sheneamer and Kalita [21] applied the Smith-Waterman algorithm to align Java bytecode sequences for detecting Java code clones. Nevertheless, similar to the work of Murakami et al, DJ Yu et al used the original Smith-Waterman algorithm and set algorithm parameters to static fixed values.…”

Section: Related Workmentioning

confidence: 99%

“…The sequence alignment is Smith-Waterman algorithm [19] based, but with significant improvements. Previous work [20], [21] has applied the Smith-Waterman algorithm to code clone detection, but parameters were set to static fixed values when using the algorithm, which leads to inevitable missing of similar regions in some cases, as demonstrated in Subsection 3, Section III. For this reason, we utilize dynamic parameter acquisition strategy to dynamically optimize the key parameters in the Smith-Waterman algorithm to overcome the prescribed problem.…”

Section: Introductionmentioning

confidence: 99%

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A Large-Gap Clone Detection Approach Using Sequence Alignment via Dynamic Parameter Optimization

et al. 2019

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Large-gap clones, a kind of clones that reuses code with many edits, are very common in software development practice and widespread in software systems. The detection of such clones is very crucial. However, due to a large number of edits, most of the current work fails to detect such clones effectively. This paper aims to find an effective approach for accurate detection of large-gap clones. We transform the code clone detection problem into a biological sequence alignment question and propose a novel approach that combines code fingerprint with sequence alignment. The sequence alignment is Smith-Waterman algorithm based, but shows significant improvements using dynamic parameter acquisition strategy. Furthermore, we design new rational criteria for clone identification. The proposed approach is automatically evaluated extensively by more than 10 million lines of code for general clones detection. We further conduct an empirical study on five large-scale Java projects to manually measure the approach for large-gap clones detection. The experimental results show that the proposed approach can effectively detect large-gap clones and exhibit good performance, and at the same time remains the competitiveness with existing advanced detection tools in detecting general clone detection. INDEX TERMSCode clone detection, dynamic parameter acquisition strategy, large-gap clone, sequence alignment.

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Detecting Java Code Clones Based on Bytecode Sequence Alignment

Cited by 17 publications

References 23 publications

Custom-Tailored Clone Detection for IEC 61131-3 Programming Languages

Custom-Tailored Clone Detection for IEC 61131-3 Programming Languages

Refactoring Java Programs for Customizable Locks Based on Bytecode Transformation

A Large-Gap Clone Detection Approach Using Sequence Alignment via Dynamic Parameter Optimization

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