A Method for Analyzing Code Homology in Genealogy of Evolving Software

Hashimoto, Masatomo; Mori, Akira

doi:10.1007/978-3-642-12029-9_7

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…A Product Evolution Tree does not directly provide commonality and variability among products, but it will allow developers to use several analysis techniques. For example, Hashimoto et al proposed to track change of source code in an evolution history [4]. They searched code clones in branches and mapping nodes of Abstract Syntax Tree among versions.…”

Section: Discussion 51 Effectiveness Of Product Evolution Treementioning

confidence: 99%

Extraction of product evolution tree from source code of product variants

Kanda

Ishio

Inoue

2013

Proceedings of the 17th International Software Product Line Conference

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A large number of software products may be derived from an original single product. Although software product line engineering is advocated as an effective approach to maintaining such a family of products, re-engineering existing products requires developers to understand evolution history of the products. It is challenging because developers have only source code of products in typical cases. In this research, we propose to extract a Product Evolution Tree that approximates evolution history from source code of products. Our key idea is that two successive products are the most similar pair of products in evolution history. We construct a Product Evolution Tree as a minimum spanning tree whose cost function is defined by the number of similar files between products. As an experiment, we have extracted Product Evolution Trees from 6 datasets of open source projects. The result shows 53 to 92% of edges in the extracted trees are consistent with the actual evolution history of the projects.

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Section: Discussion 51 Effectiveness Of Product Evolution Treementioning

confidence: 99%

Extraction of product evolution tree from source code of product variants

Kanda

Ishio

Inoue

2013

Proceedings of the 17th International Software Product Line Conference

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“…They then show how tracking origins is beneficial for ownership, code comprehension, refactoring and software evolution research. Hashimoto [26] proposed an AST-based comparison of file revisions to track co-evolution of two branches in a project. Our analysis enables to track the history of source code reuse between two projects.…”

Section: B Code Clones and Origin Analysismentioning

confidence: 99%

Identifying Source Code Reuse across Repositories Using LCS-Based Source Code Similarity

Kawamitsu

Ishio

Kanda

et al. 2014

2014 IEEE 14th International Working Conference on Source Code Analysis and Manipulation

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Abstract-Developers often reuse source files developed for another project. In order to update a reused file to a newer version released by the original project, developers have to track which revision of a file was reused and how its content was modified. However, such tracking is tedious for developers. Many projects keep older versions of files whose bugs are already fixed in the original project. In this paper, we propose a technique to automatically identify source code reuse relationships between two repositories. Using a similarity metric based on longest common subsequence, we identify pairs of similar revisions of files across the repositories. To evaluate our approach, we have analyzed eight project pairs of open source software projects and compared the result with the recorded information in the repositories. As a result, we have identified 1394 file revisions as instances of source code reuse. While 75.3% of the instances are recorded in the repositories, 20.1% of the instances are unrecorded but recovered by our approach.

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A comprehensive and scalable method for analyzing fine-grained source code change patterns

Hashimoto

Mori

Izumida

2015

2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

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This paper presents a comprehensive method for identifying fine-grained change patterns in the source code of large-scale software projects. Source code changes are computed by differencing abstract syntax trees of adjacent versions and transferred to a set of logical statements called a factbase. A factbase contains information for tracking and relating source code entities across versions and can be used to integrate analysis results of other tools such as call graphs and control flows. Users can obtain a list of change pattern instances by querying the factbase. Experiments conducted on the Linux-2.6 kernel, which involve more than 4 billions of facts, are reported to demonstrate capability of the method.

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A Method for Analyzing Code Homology in Genealogy of Evolving Software

Cited by 4 publications

References 18 publications

Extraction of product evolution tree from source code of product variants

Extraction of product evolution tree from source code of product variants

Identifying Source Code Reuse across Repositories Using LCS-Based Source Code Similarity

A comprehensive and scalable method for analyzing fine-grained source code change patterns

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