Helping analysts trace requirements:an objective look

Hayes, Jane Huffman; Dekhtyar, Alex; Sundaram, Senthil Karthikeyan; Howard, S.

doi:10.1109/icre.2004.1335682

Cited by 51 publications

(115 citation statements)

References 13 publications

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“…However, from the perspective of the analyst who must review the results and make final selections, result list B (and thus tool B) is far superior since it requires less perusing of invalid results. Also, the analyst may have a more positive perception of the tool as the results seem more trustworthy or believable [16,20]. As recall and precision cannot distinguish between tools A and B, more measures have to be introduced.…”

Section: For Results)mentioning

confidence: 99%

“…2 as a part of a requirements tracing tool called REquirements TRacing On target (RETRO) [16]. Each of the methods is enhanced with user feedback processing.…”

Section: Resultsmentioning

confidence: 99%

“…thesaurus, no secondary measures were collected. Hayes et al [16] found the secondary measures of Lag, DiffAR, and selectivity to be useful in evaluating the effectiveness of tfidf and tf-idf plus thesaurus with user feedback on a small dataset. Antoniol et al [1] examined traceability of requirements to code using two IR techniques (tf-idf and probabilistic IR).…”

Section: Secondary Measures: Related Workmentioning

confidence: 99%

“…3.1.1) [15,16,20], latent semantic indexing (LSI) (see Sect. 3.1.2) [13,40], and so-called keyword extraction methods [19].…”

Section: Vocabulary Basementioning

confidence: 99%

“…In our previous work [15,16,20], we studied approaches to automating the requirements tracing process by using Information Retrieval (IR) methods to propose candidate links between a pair of project artifacts as well as ways to incorporate automated traceability into the IV&V process [14,29].…”

Section: Introductionmentioning

confidence: 99%

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Assessing traceability of software engineering artifacts

et al. 2010

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The generation of traceability links or traceability matrices is vital to many software engineering activities. It is also person-power intensive, time-consuming, error-prone, and lacks tool support. The activities that require traceability information include, but are not limited to, risk analysis, impact analysis, criticality assessment, test coverage analysis, and verification and validation of software systems. Information Retrieval (IR) techniques have been shown to assist with the automated generation of traceability links by reducing the time it takes to generate the traceability mapping. Researchers have applied techniques such as Latent Semantic Indexing (LSI), vector space retrieval, and probabilistic IR and have enjoyed some success. This paper concentrates on examining issues not previously widely studied in the context of traceability: the importance of the vocabulary base used for tracing and the evaluation and assessment of traceability mappings and methods using secondary measures. We examine these areas and perform empirical studies to understand the importance of each to the traceability of software engineering artifacts.

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Section: For Results)mentioning

confidence: 99%

“…2 as a part of a requirements tracing tool called REquirements TRacing On target (RETRO) [16]. Each of the methods is enhanced with user feedback processing.…”

Section: Resultsmentioning

confidence: 99%