Exploring code clones in programmable logic controller software

Thaller, Hannes; Ramler, Rudolf; Pichler, Josef; Egyed, Alexander

doi:10.1109/etfa.2017.8247574

Cited by 11 publications

(9 citation statements)

References 34 publications

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“…The properties of the similarity metric splits clones into two groups [9]. Type 1-3 clones capture textual similarity while Type 4 clones capture semantic similarity [10], [14], [18], [9], [11], [19]. These types are increasingly challenging to detect, with Type 4 being the most complex one.…”

Section: A Clone Detectionmentioning

confidence: 99%

Towards Fault Localization via Probabilistic Software Modeling

Thaller

Linsbauer

Egyed

et al. 2020

2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST)

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Software testing helps developers to identify bugs. However, awareness of bugs is only the first step. Finding and correcting the faulty program components is equally hard and essential for high-quality software. Fault localization automatically pinpoints the location of an existing bug in a program. It is a hard problem, and existing methods are not yet precise enough for widespread industrial adoption. We propose fault localization via Probabilistic Software Modeling (PSM). PSM analyzes the structure and behavior of a program and synthesizes a network of Probabilistic Models (PMs). Each PM models a method with its inputs and outputs and is capable of evaluating the likelihood of runtime data. We use this likelihood evaluation to find fault locations and their impact on dependent code elements. Results indicate that PSM is a robust framework for accurate fault localization.

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Section: A Clone Detectionmentioning

confidence: 99%

Towards Fault Localization via Probabilistic Software Modeling

Thaller

Linsbauer

Egyed

et al. 2020

2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST)

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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“…For this purpose, Java source code is used as input and as we know that NICAD can detect type1, type2 and type3 clones so we can assume that these types of clones are identified. Thaller et al [33] describe the results from the analyses of code clones in real-world PLC software. These results show that normalized C/C++, ST source code is utilized and type1 and type2 clones are detected.…”

Section: A Textual Approachesmentioning

confidence: 99%

“…Simian is a clone detection tool based on textbased technique [47]. It uncovers exact (type 1) clones in all source codes but for several programming languages, it incorporates additional normalization features [33]. It relays on the comparison of text line with an ability for checking basic modification of code [76].…”

Section: G Clone Detection Toolsmentioning

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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Exploring code clones in programmable logic controller software

Cited by 11 publications

References 34 publications

Towards Fault Localization via Probabilistic Software Modeling

Towards Fault Localization via Probabilistic Software Modeling

From Innovations to Prospects

A Systematic Review on Code Clone Detection

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