Paper Info
Title
Crawling Bug Tracker for Semantic Bug Search
Abstract
The Web has become an important knowledge source for resolving system installation problems and for working around software bugs. In particular, web-based bug tracking systems offer large archives of useful troubleshooting advice. However, searching bug tracking systems can be time consuming since generic search engines do not take advantage of the semi-structured knowledge recorded in bug tracking systems. We present work towards a semantics-based bug search system which tries to take advantage of the semi-structured data found in many widely used bug tracking systems. We present a study of bug tracking systems and we describe how to crawl them in order to extract semi-structured data. We describe a unified data model to store bug tracking data. The model has been derived from the analysis of the most popular systems. Finally, we describe how the crawled data can be fed into a semantic search engine to facilitate semantic search.
Year
DOI
Venue
2008
10.1007/978-3-540-87353-2_5
DSOM
Keywords
Field
DocType
semantic search engine,crawling bug tracker,semi-structured data,semi-structured knowledge,software bug,semantics-based bug search system,generic search engine,unified data model,important knowledge source,web-based bug,semantic bug,semantic search,semi structured data,data model,search engine,tracking system
Troubleshooting,Crawling,Information retrieval,Semantic search,Computer science,Software bug,Tracking system,Bug tracking system,Data model,Semantics
Conference
Volume
ISSN
Citations 
5273
0302-9743
9
PageRank 
References 
Authors
0.55
9
3
Name
Order
Citations
PageRank
Ha Manh Tran14411.55
Georgi Chulkov2151.36
Jürgen Schönwälder336552.17