Building Domain Specific Dictionaries of Verb-Object Relation from Source Code

Onizuka

2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE)

et al. 2014

Self Cite

Abstract-An identifier is one of the crucial elements for program readability. Method names in an object-oriented program are important identifiers because method names are used for understanding the behavior of the methods without reading a part of the program. It is well-known that each method name should consist of a verb and objects according to general guidelines. However, it is not easy to name methods consistently since each of the developers may have a different understanding of the verbs and objects used in the method names. As a first step to enable developers to name methods consistently and easily, we focus on the verbs used in the method names.In this paper, we present a technique to recommend candidate verbs for a method name so that developers can use consistent verbs for method names. Given a method, we recommend a list of verbs used in many other methods similar to the given method, by using association rules. We have extracted association rules from 445 OSS projects and applied these rules to two projects. As a result, the extracted rules could recommend the current verbs in the top 10 candidates for 60.6% of the methods covered by our approach. Furthermore, we have identified four meaningful groups of rules for verb recommendation.

Section: A Studies On Support Of Naming Methodsmentioning

confidence: 99%

Recommending verbs for rename method using association rule mining

Onizuka

2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE)

et al. 2014

Self Cite

“…We applied the extracted rules to the training data set itself and four open source projects: BlueJ, NeoDatis, Saxon-HE, and Order Portal used in [9]. The 112 projects mentioned above do not include these four projects.…”

Section: Discussionmentioning

confidence: 99%

“…The domain represents the type of domain of a project. The classification was referred to from [9]. #Method indicates the number of methods in the project, and #Target represents the number of considered methods as described in Sect.…”

Section: Discussionmentioning

confidence: 99%

Improvement in Method Verb Recommendation Technique Using Association Rule Mining

IEICE Trans. Inf. & Syst.

Inoue

2015

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“…Domain represents the type of the domain of a project. We referred to [27] with regard to classification. #LOC denotes the number of lines in the source files.…”

Section: ) Rule Extractionmentioning

confidence: 99%

Method Verb Recommendation Using Association Rule Mining in a Set of Existing Projects

IEICE Trans. Inf. & Syst.

Hata

et al. 2015

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SUMMARYIt is well-known that program readability is important for maintenance tasks. Method names are important identifiers for program readability because they are used for understanding the behavior of methods without reading a part of the program. Although developers can create a method name by arbitrarily choosing a verb and objects, the names are expected to represent the behavior consistently. However, it is not easy for developers to choose verbs and objects consistently since each developer may have a different notion of a suitable lexicon for method names. In this paper, we propose a technique to recommend candidate verbs for a method name so that developers can use various verbs consistently. We recommend candidate verbs likely to be used as a part of a method name, using association rules extracted from existing methods. To evaluate our technique, we have extracted rules from 445 open source projects written in Java and confirmed the accuracy of our approach by applying the extracted rules to several open source applications. As a result, we found that 84.9% of the considered methods in four projects are recommended the existing verb. Moreover, we found that 73.2% of the actual renamed methods in six projects are recommended the correct verb.