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Empirical Software Engineering

Erschienen in:

01.04.2010

Improving automated requirements trace retrieval: a study of term-based enhancement methods

verfasst von: Xuchang Zou, Raffaella Settimi, Jane Cleland-Huang

Erschienen in: Empirical Software Engineering | Ausgabe 2/2010

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Abstract

Automated requirements traceability methods that utilize Information Retrieval (IR) methods to generate and maintain traceability links are often more efficient than traditional manual approaches, however the traces they generate are imprecise and significant human effort is needed to evaluate and filter the results. This paper investigates and compares three term-based enhancement methods that are designed to improve the performance of a probabilistic automated tracing tool. Empirical studies show that the enhancement methods can be effective in increasing the accuracy of the retrieved traces; however the effectiveness of each method varies according to specific project characteristics. The analysis of such characteristics has lead to the development of two new project-level metrics which can be used to predict the effectiveness of each enhancement method for a given data set. A procedure to automatically extract critical keywords and phrases from a set of traceable artifacts is also presented to enhance the automated trace retrieval algorithm. The procedure is tested on two new datasets.

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Titel: Improving automated requirements trace retrieval: a study of term-based enhancement methods
verfasst von: Xuchang Zou
Raffaella Settimi
Jane Cleland-Huang
Publikationsdatum: 01.04.2010
Verlag: Springer US
Erschienen in: Empirical Software Engineering / Ausgabe 2/2010
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI: https://doi.org/10.1007/s10664-009-9114-z

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