Name
Abstract | ||
|---|---|---|
Software traceability is a fundamentally important task in software engineering. The need for automated traceability increases as projects become more complex and as the number of artifacts increases. We propose an automated technique that combines traceability with a machine learning technique known as topic modeling. Our approach automatically records traceability links during the software development process and learns a probabilistic topic model over artifacts. The learned model allows for the semantic categorization of artifacts and the topical visualization of the software system. To test our approach, we have implemented several tools: an artifact search tool combining keyword-based search and topic modeling, a recording tool that performs prospective traceability, and a visualization tool that allows one to navigate the software architecture and view semantic topics associated with relevant artifacts and architectural components. We apply our approach to several data sets and discuss how topic modeling enhances software traceability, and vice versa. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1806799.1806817 | Software Engineering, 2010 ACM/IEEE 32nd International Conference |
Keywords | Field | DocType |
learning (artificial intelligence),probability,software engineering,automated traceability,machine learning technique,probabilistic topic model,semantic categorization,software architecture,software development process,software engineering,software traceability,topic modeling,topical visualization,latent dirichlet allocation,software architecture,software traceability,topic model | Software engineering,Computer science,Software construction,Software visualization,Software verification and validation,Software development,Goal-Driven Software Development Process,Traceability,Reverse semantic traceability,Requirements traceability | Conference |
Volume | ISSN | ISBN |
1 | 0270-5257 | 978-1-60558-719-6 |
Citations | PageRank | References |
132 | 3.80 | 36 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hazeline U. Asuncion | 1 | 132 | 3.80 |
| Arthur U. Asuncion | 2 | 132 | 3.80 |
| Richard N. Taylor | 3 | 5395 | 482.75 |