Improving Feature Location by Enhancing Source Code with Stereotypes

Alhindawi, Nouh; Dragan, Natalia; Collard, Michael L.; Maletic, Jonathan I.

doi:10.1109/icsm.2013.41

Cited by 33 publications

(17 citation statements)

References 26 publications

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“…One way to do this is by enhancing components when users are hovering them with summaries of what each component is responsible for. We plan to use code summarization-techniques that are based on stereotypes [47,48].…”

Section: Discussionmentioning

confidence: 99%

A diagnosis-based approach to software comprehension

Perez

Abreu

2014

Proceedings of the 22nd International Conference on Program Comprehension

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Program comprehension is a time-consuming task performed during the process of reusing, reengineering, and enhancing existing systems. Currently, there are tools to assist in program comprehension by means of dynamic analysis, but, e.g., most cannot identify the topology and the interactions of a certain functionality in need of change, especially when used in large, real-world software applications. We propose an approach, coined Spectrum-based Feature Comprehension (SFC), that borrows techniques used for automatic software-fault-localization, which were proven to be effective even when debugging large applications in resourceconstrained environments. SFC analyses the program by exploiting run-time information from test case executions to compute the components that are important for a given feature (and whether a component is used to implement just one feature or more), helping software engineers to understand how a program is structured and what the functionality's dependencies are. We present a toolset, coined Pangolin, that implements SFC and displays its report to the user using an intuitive visualization. A user study with the open-source application Rhino is presented, demonstrating the efficiency of Pangolin in locating the components that should be inspected when changing a certain functionality.

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Section: Discussionmentioning

confidence: 99%

A diagnosis-based approach to software comprehension

Perez

Abreu

2014

Proceedings of the 22nd International Conference on Program Comprehension

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“…For our calculations of precision and recall, we classify use case documents describing features with large unused parts also as relevant (true), because they contain large regions that never have been performed and should be considered by the product owner when planning maintenance. Considering use case documents expressing partly unused features as relevant, our approach achieves an average precision (AP) 10 of 0.89, and taking only use case documents into account describing completely unused features, AP is 1, since our approach ranks both relevant use case documents highest. …”

Section: Rq2mentioning

confidence: 99%

“…An extensive survey on feature location is given by Dit et al [8]. Among the techniques proposed for this task are static and dynamic analyses [9] as well as text mining techniques [10], which is what we applied here. Text mining has been used for feature location, e.g., in [11] where features are located based on natural language documents.…”

Section: Related Workmentioning

confidence: 99%

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Which Features Do My Users (Not) Use?

Eder

Femmer

Hauptmann

et al. 2014

2014 IEEE International Conference on Software Maintenance and Evolution

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Abstract-Maintenance of unused features leads to unnecessary costs. Therefore, identifying unused features can help product owners to prioritize maintenance efforts. We present a tool that employs dynamic analyses and text mining techniques to identify use case documents describing unused features to approximate unnecessary features. We report on a preliminary study of an industrial business information system over the course of one year quantifying unused features and measuring the performance of the approach. It indicates the relevance of the problem and the capability of the presented approach to detect unused features.

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“…Both of the source code and the external documentation need to be broken up into the proper granularity to define the corpuses documents, which will be represented as vectors [2,9,[12][13][14]. Therefore, we split up the source code into documents with function granularity level.…”

Section: Total Of External Documents 11594mentioning

confidence: 99%

A Topic Modeling Based Solution for Confirming Software Documentation Quality

Alhindawi¹,

Al-Hazaimeh²,

Malkawi³

et al. 2016

ijacsa

Self Cite

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Abstract-this paper presents an approach for evaluating and confirming the quality of the external software documentation using topic modeling. Typically, the quality of the external documentation has to mirror precisely the organization of the source code. Therefore, the elements of such documentation should be strongly written, associated, and presented. In this paper, we use Latent Dirichlet Allocation (LDA) and HELLINGER DISTANCE to compute the similarities between the fragments of source code and the external documentation topics. These similarities are used in this paper to improve and advance the existing external documentation. Furthermore, these similarities can also be used for evaluating the new documenting process during the evolution phase of the software. The results show that the new approach yields state-of-the-art performance in evaluating and confirming the existing external documentations quality and superiority.

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Improving Feature Location by Enhancing Source Code with Stereotypes

Cited by 33 publications

References 26 publications

A diagnosis-based approach to software comprehension

A diagnosis-based approach to software comprehension

Which Features Do My Users (Not) Use?

A Topic Modeling Based Solution for Confirming Software Documentation Quality

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