Mining aspectual views using formal concept analysis

Bruntink, Magiel; Deursen, Arie van

doi:10.1109/scam.2004.15

Cited by 91 publications

(53 citation statements)

References 12 publications

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“…For example, Marin et al [10] not only use the invoked method's static type, but use the set of sub-and superclasses; Tourwe and Mens [17] group by similar identifiers. The approach uses a similar technique to generalise the discovered patterns: The called method c(n) at a node n is identified by its signature either with or without the class it is defined in.…”

Section: Generalisation Of Discovered Patternsmentioning

confidence: 99%

“…Tourwe and Mens [17] use concept analysis to identify aspectual views in programs. The extraction of elements and attributes from the names of classes, methods and variables, formal concept analysis is used to group those elements into concepts that can be seen as aspect candidates.…”

Section: Related Workmentioning

confidence: 99%

“…Ceccato et al [11] have done a comparison of three aspect mining approaches: fan-in [10], identifier [17] and dynamic analyses [20]. The differences in the approaches and their results are presented and examined.…”

Section: Related Workmentioning

confidence: 99%

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Mining execution relations for crosscutting concerns

Krinke

2008

IET Softw.

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Aspect mining tries to identify crosscutting concerns in the code of existing systems and thus supports their adaption to an aspect-oriented design.A semi-automatic static aspect mining approach is described, where the program's control flow graphs are investigated for recurring execution patterns based on different constraints, such as the requirement that the patterns have to exist in different calling contexts. Two case studies done with the implemented tool show that many discovered candidates for crosscutting concerns are instances of delegation and should not be refactored into aspects. More generally, it is shown that aspect mining techniques need a way to distinguish between delegation and superimposed behaviour.

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Section: Generalisation Of Discovered Patternsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Mining execution relations for crosscutting concerns

Krinke

2008

IET Softw.

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“…An approach for aspect mining using formal concept analysis on execution traces was proposed by Tonella et al [25]. Also aspects were mined by detecting patterns in execution traces using formal concept analysis by Tourwé et al [26].…”

Section: Related Workmentioning

confidence: 99%

Relating the Evolution of Design Patterns and Crosscutting Concerns

Cerulo¹,

Penta²

2007

Seventh IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2007)

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“…There are two kinds of approaches based on whether the programs are running or not [4]. Static code analysis, like syntax and type analysis, targets the source code and the object code (the byte code) and even the design model [5]- [7]. Dynamic analysis, on the other hand, obtains internal information and the output by running the specific program to find relations [3], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Towards the Identification of Cross-Cutting Concerns: A Comprehensive Dynamic Approach Based on Execution Relations

2014

IEICE Trans. Inf. & Syst.

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SUMMARYAspect-oriented software development (AOSD) helps to solve the problem of low scalability and high maintenance costs of legacy systems caused by code scattering and tangling by extracting cross-cutting concerns and inserting them into aspects. Identifying the cross-cutting concerns of legacy systems is the key to reconstructing such systems using the approach of AOSD. However, current dynamic approaches to the identification of cross-cutting concerns simply check the methods' execution sequence, but do not consider their calling context, which may cause low precision. In this paper, we propose an improved comprehensive approach to the identification of candidate cross-cutting concerns of legacy systems based on the combination of the analysis of recurring execution relations and fan-ins. We first analyse the execution trace with a given test case and identify four types of execution relations for neighbouring methods: exit-entry, entry-exit, entry-entry and exit-exit. Afterwards, we measure the methods' left cross-cutting degrees and right cross-cutting degrees. The former ensures that the candidate recurs in a similar running context, whereas the latter indicates how many times the candidate crosscuts different methods. The final candidates are then obtained from those high fan-in methods, which not only cross-cut others more times than a predefined threshold, but are always entered or left under the same running context. The experiment conducted on three open source systems shows that our approach improves the precision of identifying cross-cutting concerns compared with tradition ones.

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Mining aspectual views using formal concept analysis

Cited by 91 publications

References 12 publications

Mining execution relations for crosscutting concerns

Mining execution relations for crosscutting concerns

Relating the Evolution of Design Patterns and Crosscutting Concerns

Towards the Identification of Cross-Cutting Concerns: A Comprehensive Dynamic Approach Based on Execution Relations

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