Enhancing candidate link generation for requirements tracing: The cluster hypothesis revisited

Niu, Nan; Mahmoud, Anas

doi:10.1109/re.2012.6345842

Cited by 44 publications

(34 citation statements)

References 25 publications

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“…To locate more accurately "where" the code base should be refactored, we synthesize clustering-based link retrieval [13] with the as-needed traceability information captured in issue tracking repositories [4]. To determine more precisely "what" refactoring(s) should be applied to the identified places, we develop a new scheme by first examining requirements semantics as they relate to implementation, then leveraging the semantic characterization to uncover the problems in the code (i.e., bad smells [7]) that may impede the fulfillment of the requirements, and finally choosing the type of refactorings that can remove the bad smells.…”

Section: Introductionmentioning

confidence: 99%

Traceability-enabled refactoring for managing just-in-time requirements

Niu

Bhowmik

Liu

et al. 2014

2014 IEEE 22nd International Requirements Engineering Conference (RE)

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Abstract-Just-in-time requirements management, characterized by lightweight representation and continuous refinement of requirements, fits many iterative and incremental development projects. Being lightweight and flexible, however, can cause wasteful and procrastinated implementation, leaving certain stakeholder goals not satisfied. This paper proposes traceabilityenabled refactoring aimed at fulfilling more requirements fully. We make a novel use of requirements traceability to accurately locate where the software should be refactored, and develop a new scheme to precisely determine what refactorings should be applied to the identified places. Our approach is evaluated through an industrial study. The results show that our approach recommends refactorings more appropriately than a contemporary recommender.

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Section: Introductionmentioning

confidence: 99%

Traceability-enabled refactoring for managing just-in-time requirements

Niu

Bhowmik

Liu

et al. 2014

2014 IEEE 22nd International Requirements Engineering Conference (RE)

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“…On the basis of major assumptions of the cluster hypothesis, the research assumptions are generated within this phase. On the basis of relevance of information required [23], the documents that behave similarly are present within similar clusters.…”

Section: Proposed Methodologymentioning

confidence: 99%

Null function classification using NFR matrix and decision tree

Hoshmand

Kang

2018

IJET

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This research work is based on the classification of the functions which are required and which is not required for the efficient development of the software. The motivation of this work is to identify non required functions to reduce development cost and efforts. The classification is the technique which can classify data into certain number of classes. The NFR matrix is the existing technique which can classify the Null functions. To classify the null functions NFR use clustering method which can modify to increase accuracy of classification. In the existing method NFR matrix is used for the null function classification, it use the clustering for the classification. In this work, decision tree will based with the clustering. It take input result of clustering and generate classified result.

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“…One major drawback of Information retrieval approaches, in particular, TF-IDF similarity scoring, is the huge amount of false positives candidate links that are generated [17]. In the literature, this is handled through the use of an arbitrary cut-off value upon the document's score below which, the document is not considered as a valuable candidate link [18].…”

Section: Hybridizing Mde and Ir In The Toolmentioning

confidence: 99%

“…Tackling the candidate link generation is a major issue in the IR community. Niu and Mahmoud proposed to rely on clustering algorithm to sort between good and bad quality clusters [17]. Our approach is based on a pre-processing enrichment of the documents, synchronized with the model information and can be seen as a complementary work.…”

Section: Related Workmentioning

confidence: 99%