Interactive Traceability Links Visualization using Hierarchical Trace Map

Aung, TWW; Huo, H; Sui, Y

Interactive Traceability Links Visualization using Hierarchical Trace Map

Aung, TWW

Huo, H

Sui, Y

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019, 2019, pp. 367 - 369
Issue Date:: 2019-09-01

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Field	Value	Language
dc.contributor.author	Aung, TWW https://orcid.org/0000-0001-7300-1264
dc.contributor.author	Huo, H https://orcid.org/0000-0003-2440-714X
dc.contributor.author	Sui, Y https://orcid.org/0000-0002-9510-6574
dc.date.issued	2019-09-01	en_US
dc.identifier.citation	Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019, 2019, pp. 367 - 369	en_US
dc.identifier.isbn	9781728130941	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137280
dc.description.abstract	© 2019 IEEE. Traceability links between various software artifacts of a system aid software engineers in system comprehension, verification and change impact analysis. Establishing trace links between software artifacts manually is an error-prone and costly task. Recently, studies in automated traceability link recovery area have received broad attention in the software maintenance community aiming to overcome the challenges of manual trace links maintenance process. In these studies, the trace links results generated by an automated trace recovery approach are presented either in a bland textual matrix format (e.g., tabular format) or two-dimensional graphical formats (e.g. tree view, hierarchical leaf node). Therefore, it is challenging for software engineers to explore the inter-relationships between various artifacts at once (e.g., which test cases and source code files/methods are related to a particular requirement). In this position paper, we propose a hierarchical trace map visualization technique to explore inter-relationships between various artifacts at once naturally and intuitively.	en_US
dc.relation.ispartof	Proceedings - 2019 IEEE International Conference on Software Maintenance and Evolution, ICSME 2019	en_US
dc.relation.isbasedon	10.1109/ICSME.2019.00059	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Interactive Traceability Links Visualization using Hierarchical Trace Map	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2021-09-01T00:00:00+1000
pubs.publication-status	Published	en_US

Abstract:

© 2019 IEEE. Traceability links between various software artifacts of a system aid software engineers in system comprehension, verification and change impact analysis. Establishing trace links between software artifacts manually is an error-prone and costly task. Recently, studies in automated traceability link recovery area have received broad attention in the software maintenance community aiming to overcome the challenges of manual trace links maintenance process. In these studies, the trace links results generated by an automated trace recovery approach are presented either in a bland textual matrix format (e.g., tabular format) or two-dimensional graphical formats (e.g. tree view, hierarchical leaf node). Therefore, it is challenging for software engineers to explore the inter-relationships between various artifacts at once (e.g., which test cases and source code files/methods are related to a particular requirement). In this position paper, we propose a hierarchical trace map visualization technique to explore inter-relationships between various artifacts at once naturally and intuitively.

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http://hdl.handle.net/10453/137280