2017
DOI: 10.1155/2017/4382348
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Using Hierarchical Latent Dirichlet Allocation to Construct Feature Tree for Program Comprehension

Abstract: Program comprehension is an important task faced by developers during software maintenance. With the increasing complexity of evolving systems, program comprehension becomes more and more difficult. In practice, programmers are accustomed to getting a general view of the features in a software system and then finding the interesting or necessary files to start the understanding process. Given a system, developers may need a general view of the system. The traditional view of a system is shown in a packageclass… Show more

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Cited by 3 publications
(2 citation statements)
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“…The average error value is the value obtained from the division between the number of error values (∑e) and the amount of data (P) [27], as shown in Equation 18.…”
Section: Error Average Valuementioning
confidence: 99%
“…The average error value is the value obtained from the division between the number of error values (∑e) and the amount of data (P) [27], as shown in Equation 18.…”
Section: Error Average Valuementioning
confidence: 99%
“…The researchers in [26] applied the hierarchical Latent Dirichlet Allocation (hLDA) model to analyze software program text and generate a feature tree to understand the software system, while the tree includes two hierarchies; feature hierarchy and file structure hierarchy. As the feature hierarchy for displaying the features from abstract to detailed levels and the file structure hierarchy for displaying the classes from whole to part.…”
Section: Related Workmentioning
confidence: 99%