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https://doi.org/10.21256/zhaw-26549| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | OntoTrace : a tool for supporting trace generation in software development by using ontology-based automatic reasoning |
| Authors: | Mosquera, David Ruiz, Marcela Pastor, Oscar Spielberger, Jürgen Fievet, Lucas |
| et. al: | No |
| DOI: | 10.1007/978-3-031-07481-3_9 10.21256/zhaw-26549 |
| Proceedings: | Intelligent Information Systems |
| Editors of the parent work: | De Weerdt, Jochen Polyvyanyy, Artem |
| Page(s): | 73 |
| Pages to: | 81 |
| Conference details: | 34th International Conference on Advanced Information Systems Engineering (CAiSE '22), Leuven, Belgium, 6-10 June 2022 |
| Issue Date: | Jun-2022 |
| Series: | Lecture Notes in Business Information Processing |
| Series volume: | 452 |
| Publisher / Ed. Institution: | Springer |
| Publisher / Ed. Institution: | Cham |
| ISBN: | 978-3-031-07480-6 978-3-031-07481-3 |
| Language: | English |
| Subjects: | Software traceability; Software traceability tool; Ontology; Trace generation; Automatic reasoning |
| Subject (DDC): | 005: Computer programming, programs and data 006: Special computer methods |
| Abstract: | Traceability in software development has gained interest due to its software maintainability and quality assurance benefits. Artifacts such as code, requirements, mockups, test cases, among others, are feasible trace sources/targets during the software development process. Existing scientific approaches support tasks like identifying untraced artifacts, establishing new traces, and validating existing traces. However, most approaches require input existing traceability data or are restricted to a certain application domain hindering their practical application. This contemporary challenge in information systems engineering calls for novel traceability solutions. In this paper, we present OntoTrace: a tool for supporting traceability tasks in software development projects by using ontology-based automatic reasoning. OntoTrace allows software development teams for inferring traceability-related data such as i) which are the traceable source/target artifacts; ii) which artifacts are not yet traced; and iii) given a specific artifact, which are the possible traces between it and other artifacts. We demonstrate how OntoTrace works in the context of the Swiss startup LogicFlow AG, supporting the traceability between functional/non-functional requirements and user interface test cases. We conclude the paper by reflecting on the experience from applying the approach in practice, and we draw on future challenges and next research endeavors. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/26549 |
| Fulltext version: | Submitted version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Applied Information Technology (InIT) |
| Published as part of the ZHAW project: | Machine Learning for Software User Interface Testing |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2022_Mosquera-etal_OntoTrace_CAiSE2022.pdf | Submitted Version | 744.89 kB | Adobe PDF |  View/Open |
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Mosquera, D., Ruiz, M., Pastor, O., Spielberger, J., & Fievet, L. (2022). OntoTrace : a tool for supporting trace generation in software development by using ontology-based automatic reasoning [Conference paper]. In J. De Weerdt & A. Polyvyanyy (Eds.), Intelligent Information Systems (pp. 73–81). Springer. https://doi.org/10.1007/978-3-031-07481-3_9
Mosquera, D. et al. (2022) ‘OntoTrace : a tool for supporting trace generation in software development by using ontology-based automatic reasoning’, in J. De Weerdt and A. Polyvyanyy (eds) Intelligent Information Systems. Cham: Springer, pp. 73–81. Available at: https://doi.org/10.1007/978-3-031-07481-3_9.
D. Mosquera, M. Ruiz, O. Pastor, J. Spielberger, and L. Fievet, “OntoTrace : a tool for supporting trace generation in software development by using ontology-based automatic reasoning,” in Intelligent Information Systems, Jun. 2022, pp. 73–81. doi: 10.1007/978-3-031-07481-3_9.
MOSQUERA, David, Marcela RUIZ, Oscar PASTOR, Jürgen SPIELBERGER und Lucas FIEVET, 2022. OntoTrace : a tool for supporting trace generation in software development by using ontology-based automatic reasoning. In: Jochen DE WEERDT und Artem POLYVYANYY (Hrsg.), Intelligent Information Systems. Conference paper. Cham: Springer. Juni 2022. S. 73–81. ISBN 978-3-031-07480-6
Mosquera, David, Marcela Ruiz, Oscar Pastor, Jürgen Spielberger, and Lucas Fievet. 2022. “OntoTrace : A Tool for Supporting Trace Generation in Software Development by Using Ontology-Based Automatic Reasoning.” Conference paper. In Intelligent Information Systems, edited by Jochen De Weerdt and Artem Polyvyanyy, 73–81. Cham: Springer. https://doi.org/10.1007/978-3-031-07481-3_9.
Mosquera, David, et al. “OntoTrace : A Tool for Supporting Trace Generation in Software Development by Using Ontology-Based Automatic Reasoning.” Intelligent Information Systems, edited by Jochen De Weerdt and Artem Polyvyanyy, Springer, 2022, pp. 73–81, https://doi.org/10.1007/978-3-031-07481-3_9.
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