On fuzzy repetitions detection in documentation reuse

Luciv, Dmitry; Koznov, Dmitrij V.; Basit, Hamid Abdul; Terekhov, Andrey

doi:10.1134/s0361768816040046

Cited by 4 publications

(7 citation statements)

References 15 publications

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“…In our previous studies [8,9], we presented an approach that offers a partial solution for this problem. At first, similarly to Juergens et al [2], Wingkvist et al [6], we applied software clone detection techniques to exact duplicate detection [37].…”

Section: Basic Near Duplicate Detection and Refactoringmentioning

confidence: 99%

“…At first, similarly to Juergens et al [2], Wingkvist et al [6], we applied software clone detection techniques to exact duplicate detection [37]. Then, in [8,9] we proposed an approach to near duplicate detection. It is essentially as follows: having exact duplicates found by Clone Miner, we extract sets of duplicate groups where clones are located close to each other.…”

Section: Basic Near Duplicate Detection and Refactoringmentioning

confidence: 99%

“…The initial interval tree for is constructed using the () function (line 2). The core part of the algorithm is a loop in which new near duplicate groups are constructed (lines [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]…”

Section: Algorithm Descriptionmentioning

confidence: 99%

“…Our definition is the formalized version of the definition given in the reference [11]. We also present a generalization of the algorithm described in [8,9]. The algorithm is implemented in the Documentation Refactoring Toolkit [12], which is a part of the DocLine project [4].…”

Section: Introductionmentioning

confidence: 99%

“…Their approach was based on an informal definition of near duplicates and the problem of duplicate detection was not addressed. In our previous studies [8,9] we presented a near duplicate detection approach. Its core idea is to uncover near duplicates and then to apply the reuse techniques described in our earlier studies [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Detecting Near Duplicates in Software Documentation

Luciv

Koznov

Chernishev

et al. 2018

Program Comput Soft

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Contemporary software documentation is as complicated as the software itself. During its lifecycle, the documentation accumulates a lot of "near duplicate" fragments, i.e. chunks of text that were copied from a single source and were later modified in different ways. Such near duplicates decrease documentation quality and thus hamper its further utilization. At the same time, they are hard to detect manually due to their fuzzy nature. In this paper we give a formal definition of near duplicates and present an algorithm for their detection in software documents. This algorithm is based on the exact software clone detection approach: the software clone detection tool Clone Miner was adapted to detect exact duplicates in documents. Then, our algorithm uses these exact duplicates to construct near ones. We evaluate the proposed algorithm using the documentation of 19 open source and commercial projects. Our evaluation is very comprehensive -it covers various documentation types: design and requirement specifications, programming guides and API documentation, user manuals. Overall, the evaluation shows that all kinds of software documentation contain a significant number of both exact and near duplicates. Next, we report on the performed manual analysis of the detected near duplicates for the Linux Kernel Documentation. We present both quantative and qualitative results of this analysis, demonstrate algorithm strengths and weaknesses, and discuss the benefits of duplicate management in software documents.

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