FeatureClouds: Naming the Identified Feature Implementation Blocks from Software Source Code Using Word Clouds
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The document introduces 'featureclouds,' an approach developed to assist software engineers in naming identified feature implementation blocks (ifibs) from source code using word cloud visualization techniques. This method analyzes the content of each ifib, suggesting names based on the most frequently occurring words, and has demonstrated promise in terms of precision and recall in evaluations. Limitations are noted, such as the potential for irrelevant names due to poorly named identifiers and the necessity for future enhancements in word weighting for different software identifier types.
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![Feature identification and feature
naming
• Feature identification or location is the process
of detecting the source code elements, such as
classes or methods, that implement particular
functionality in a software product [1].
• Several works have been carried out on feature
identification, whether from single software or
a group of software products [2].
• Feature naming is the activity of suggesting a
meaningful name for the extracted feature
implementations.
• In this work, a feature is a functionality
provided by a software product.](https://image.slidesharecdn.com/featurecloudsnamingtheidentifiedfeatureimplementationblocksfromsoftwaresourcecodeusingwordclouds-240904222624-4bb1d595/85/FeatureClouds-Naming-the-Identified-Feature-Implementation-Blocks-from-Software-Source-Code-Using-Word-Clouds-5-320.jpg)
![FeatureClouds
• In this paper, we propose an approach
called FeatureClouds to support
feature naming during the feature
identification process from software
source code.
• The proposed approach exploits the
word cloud visualization technique [9]
to help software engineers to name
the IFIBs.
• As each block include only the
implementation of a single feature.
• Feature naming is based on an analysis
of the content of each IFIB to propose
a feature name.
• Where the IFIBs can be named by
selecting words with the highest
frequency from word clouds.
FeatureClouds](https://image.slidesharecdn.com/featurecloudsnamingtheidentifiedfeatureimplementationblocksfromsoftwaresourcecodeusingwordclouds-240904222624-4bb1d595/85/FeatureClouds-Naming-the-Identified-Feature-Implementation-Blocks-from-Software-Source-Code-Using-Word-Clouds-7-320.jpg)
![Related work
• Table II presents a comparison between feature naming approaches
that exploited the word cloud visualization technique.
• There is only one study concerned with feature naming based on
the word-cloud in the literature, which is the study of Martinez et
al. [12].
• We evaluate this closest work to our approach based on the
following criteria:
• granularity level of block code,
• programmed method,
• cloud filters,
• evaluation criteria of the proposed name,
• cloud layout,
• cloud arrangement,
• word preprocessing.](https://image.slidesharecdn.com/featurecloudsnamingtheidentifiedfeatureimplementationblocksfromsoftwaresourcecodeusingwordclouds-240904222624-4bb1d595/85/FeatureClouds-Naming-the-Identified-Feature-Implementation-Blocks-from-Software-Source-Code-Using-Word-Clouds-9-320.jpg)
![State
Collaboration
Activity
Use case Sequence
Deployment
Class
Cognitive support
Logging Diagrams
ArgoUML
Mandatory
Optional
Legend:
Fig. 5. ArgoUML FM [21].](https://image.slidesharecdn.com/featurecloudsnamingtheidentifiedfeatureimplementationblocksfromsoftwaresourcecodeusingwordclouds-240904222624-4bb1d595/85/FeatureClouds-Naming-the-Identified-Feature-Implementation-Blocks-from-Software-Source-Code-Using-Word-Clouds-25-320.jpg)
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FeatureClouds: Naming the Identified Feature Implementation Blocks from Software Source Code Using Word Clouds
- 1. FeatureClouds: Naming the Identified Feature Implementation Blocks from Software Source Code Using Word Clouds Ra'Fat Al-Msie'deen, Hamzeh Eyal Salman, Anas H. Blasi, and Mohammed A. Alsuwaiket Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan E-mail address: [email protected] https://rafat66.github.io/Al-Msie-Deen/
- 2. Abstract Identifying software identifiers that implement a particular feature of a software product is known as feature identification. Feature identification is one of the most critical and popular processes performed by software engineers during software maintenance activity. However, a meaningful name must be assigned to the Identified Feature Implementation Block (IFIB) to complete the feature identification process. The feature naming process remains a challenging task, where the majority of existing approaches manually assign the name of the IFIB. In this paper, the approach called FeatureClouds was proposed, which can be exploited by software developers to name the IFIBs from software code. FeatureClouds approach incorporates word clouds visualization technique to name Feature Blocks (FBs) by using the most frequent words across these blocks. FeatureClouds had evaluated by assessing its added benefit to the current approaches in the literature, where limited tool support was supplied to software developers to distinguish feature names of the IFIBs. For validity, FeatureClouds had applied to draw shapes and ArgoUML software. The findings showed that the proposed approach achieved promising results according to well-known metrics in terms of Precision and Recall.
- 3. Index terms ✓ Feature naming, feature implementation blocks, software engineering, word clouds.
- 4. Introduction In this paper, we propose an approach called FeatureClouds to support feature naming during the feature identification process from software source code. The proposed approach exploits the word cloud visualization technique to help software engineers to name the IFIBs. As each block include only the implementation of a single feature. Feature naming is based on an analysis of the content of each IFIB to propose a feature name. IFIBs can be named by selecting words with the highest frequency from word clouds.
- 5. Feature identification and feature naming • Feature identification or location is the process of detecting the source code elements, such as classes or methods, that implement particular functionality in a software product [1]. • Several works have been carried out on feature identification, whether from single software or a group of software products [2]. • Feature naming is the activity of suggesting a meaningful name for the extracted feature implementations. • In this work, a feature is a functionality provided by a software product.
- 6. Fig. 1. The IFIBs from software source code
- 7. FeatureClouds • In this paper, we propose an approach called FeatureClouds to support feature naming during the feature identification process from software source code. • The proposed approach exploits the word cloud visualization technique [9] to help software engineers to name the IFIBs. • As each block include only the implementation of a single feature. • Feature naming is based on an analysis of the content of each IFIB to propose a feature name. • Where the IFIBs can be named by selecting words with the highest frequency from word clouds. FeatureClouds
- 9. Related work • Table II presents a comparison between feature naming approaches that exploited the word cloud visualization technique. • There is only one study concerned with feature naming based on the word-cloud in the literature, which is the study of Martinez et al. [12]. • We evaluate this closest work to our approach based on the following criteria: • granularity level of block code, • programmed method, • cloud filters, • evaluation criteria of the proposed name, • cloud layout, • cloud arrangement, • word preprocessing.
- 10. Related Work
- 11. Related Work ✓ The majority of the current studies manually suggest feature names of the extracted FIBs based on existing software documentation. In the related work, no work automatically provides a name for the IFIBs.
- 14. Inputs Feature implementation blocks FeatureClouds Creating word cloud Extracting identifier names (words) Splitting words Returning words to their roots Identifying words arrangement Determining word weights Outputs Feature implementation block names
- 15. MyOval getOvalx getOvaly Oval setOvaly setOvalx Drawing.Shapes.Oval Ovalx Ovaly OvalSettings Rectangle RectangleSettings Drawing.Shapes.Rectangle setRectangley setRectanglex Rectanglex Rectangley getRectangley MyRectangle getRectanglex FIBs identified from drawing shapes software variants
- 16. The IFIBs from software source code Feature implementation block 1 Software Identifier (package, class, method or attribute) Software X
- 17. Software 1 Software 2 Software n Feature implementation block 1 Feature block Software Identifier (package, class, method or attribute) Component Service Feature Software A Single software Software family
- 18. Software 1 Software 2 Software n Feature implementation block 1 Software Identifier (package, class, method or attribute) Software A Single software Software family
- 19. Experimentation
- 20. Experimental Results • Figure 7 shows the word cloud extracted from the activity diagram implementation block. The most frequent word across this block is activity and diagram.
- 23. State Feature naming via the feature model: State Feature naming via FeatureClouds approach: State Feature model (partial) ArgoUML State …. Feature implementation block (partial) Recall metric = 1, and precision metric = 1 Word cloud (partial) ……. ………. …. …….. State …………. FigStubState FigForkState . . Manually Feature naming: State Fig. 8. FIB, word cloud, manual feature name, named feature by FeatureClouds, recall and precision metrics for state feature of ArgoUML software
- 24. State Manual feature name FigStubState GoStateToOutgoingTrans FigForkState GoStateMachineToState PropPanelUMLStateDiagram FigHistoryState PredIsStartState GoStateMachineToTop GoStateMachineToTransition StateDiagramPropPanelFactory GoClassifierToStateMachine ActionStateDiagram GoStateToIncomingTrans PredIsFinalState FigConcurrentRegion UMLStateDiagram FigCompositeState ActionCreatePseudostate FigSubmachineState GoStatemachineToDiagram FigBranchState GoBehavioralFeatureToStateDiagram FigSimpleState FigDeepHistoryState FigInitialState SelectionState GoCompositeStateToSubvertex FigJunctionState FigSynchState FigState FigJoinState ButtonActionNewEffect InitStateDiagram FigShallowHistoryState GoProjectToStateMachine State Named feature by FeatureClouds Feature model ArgoUML State …. Feature implementation block Recall metric = 1 & precision metric = 1 Word cloud
- 25. State Collaboration Activity Use case Sequence Deployment Class Cognitive support Logging Diagrams ArgoUML Mandatory Optional Legend: Fig. 5. ArgoUML FM [21].
- 26. Inputs Feature implementation blocks Software product variants Single software product Feature implementation identification FeatureClouds Creating word cloud Extracting identifier names (words) Splitting words Returning words to their roots Identifying words arrangement Determining word weights Outputs Feature implementation block names A B C D E F X X Feature naming Feature implementation block Feature name Word cloud
- 27. Conclusion FeatureClouds is an approach that employs a word cloud visualization technique to provide feature names for the IFIBs from a set of product variants or single software. It is constructed for assisting software engineers in feature naming. We evaluated it in numerous case studies such as ArgoUML and drawing shapes software. The findings show its soundness in feature naming. The findings of FeatureClouds have shown some limitations for the feature naming process. For instance, the suggested approach has returned irrelevant names to some blocks, and this occurs when identifiers are not properly named by software programmers. Thus, the retrieved feature name may not be appropriate or reflect feature role or functionality in the software system. Also, WordNet or camel-case method may not be trustworthy in all cases to return the word root or to split identifier name. Thus, these methods should be enhanced and improved with other methods. In the current approach, we give the same weights for all software identifiers types that make up the IFIB.
- 28. Future work As future work direction, we plan to assess the use of word weights for different software identifier types (i.e., package, class, method, and attribute). For instance, in the IFIB, the word that belongs to the class name has more importance (i.e., weight) than the word that belongs to the attribute name
- 29. References
- 30. References
- 31. References
- 32. FeatureClouds: Naming the Identified Feature Implementation Blocks from Software Source Code Using Word Clouds Ra'Fat Al-Msie'deen, Hamzeh Eyal Salman, Anas H. Blasi, and Mohammed A. Alsuwaiket Department of Software Engineering, Faculty of IT, Mutah University, Mutah 61710, Karak, Jordan E-mail address: [email protected] https://rafat66.github.io/Al-Msie-Deen/