A tracelab-based solution for identifying traceability links using LSI

Alhindawi, Nouh; Meqdadi, Omar; Bartman, Brian; Maletic, Jonathan I.

doi:10.1109/tefse.2013.6620159

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…The gold sets were constructed using the mappings between the source code and the features, which were made available by Eaddy et al [58]. These mappings 3 were produced by considering the sections of the ECMAScript specification as features, and associating them with software artifacts using the following prune dependency rule, created by Eaddy et al [58]: "A program element is relevant to a concern if it should be removed, or otherwise altered, when the concern is pruned. "…”

Section: Systemsmentioning

confidence: 99%

“…That being said, we tried to implement as many of the techniques that we could in order to show the efficacy and usefulness of TraceLab as a research tool in the domain of software evolution and maintenance. We are continuously working on driving new research projects with TraceLab [3,29,44,50,78,101,155,183] and encourage others to do so as well.…”

Section: Limitationsmentioning

confidence: 99%

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Configuring and Assembling Information Retrieval Based Solutions for Software Engineering Tasks

Dit

2016

2016 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Information Retrieval (IR) approaches are used to leverage textual or unstructured data generated during the software development process to support various software engineering (SE) tasks (e.g., concept location, traceability link recovery, change impact analysis, etc.). Two of the most important steps for applying IR techniques to support SE tasks are preprocessing the corpus and configuring the IR technique, and these steps can significantly influence the outcome and the amount of effort developers have to spend for these maintenance tasks. We present the use of Genetic Algorithms (GAs) to automatically configure and assemble an IR process to support SE tasks. The approach named IR-GA determines the (near) optimal solution to be used for each step of the IR process without requiring any training. We applied IR-GA on three different SE tasks and the results of the study indicate that IR-GA outperforms approaches previously used in the literature, and that it does not significantly differ from an ideal upper bound that could be achieved by a supervised approach and a combinatorial approach

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Section: Systemsmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

Configuring and Assembling Information Retrieval Based Solutions for Software Engineering Tasks

Dit

2016

2016 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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“…This is also done by extracting all the natural language information associated with a given source code; all the words used in include user documents (e.g., HTML,XML/docbook, LaTeX and Doxygen), build management documents (automake, cmake, and makefile), HowTo guides (e.g., FAQs), release and distribution documents (e.g.,ChangeLogs, whatsNew, README, and INSTALL guides), progress monitoring documents (TODO and STATUS), and extensible mechanisms (e.g., Python, Ruby, and Pearl bindings for an API) [2,8,9].…”

Section: Stepmentioning

confidence: 99%

“…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

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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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