NASA anomaly databases are rich resources of software failure data in the field. These data are often captured in natural language that is not appropriate for trending or statistical analyses. This fast abstract describes a feasibility study of applying 60 natural language processing techniques for automatically classifying anomaly data to enable trend analyses. © 2013 IEEE.
Falessi, D., Layman, L. (2013). Automated classification of NASA anomalies using natural language processing techniques. In 2013 IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2013 (pp.5-6). 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/ISSREW.2013.6688849].
Automated classification of NASA anomalies using natural language processing techniques
Falessi D.;
2013-01-01
Abstract
NASA anomaly databases are rich resources of software failure data in the field. These data are often captured in natural language that is not appropriate for trending or statistical analyses. This fast abstract describes a feasibility study of applying 60 natural language processing techniques for automatically classifying anomaly data to enable trend analyses. © 2013 IEEE.| File | Dimensione | Formato | |
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