학술논문

Root Cause Analysis Using Sequence Alignment and Latent Semantic Indexing
Document Type
Conference
Source
19th Australian Conference on Software Engineering (aswec 2008) Software Engineering, 2008. ASWEC 2008. 19th Australian Conference on. :367-376 Mar, 2008
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Indexing
Testing
Fault diagnosis
Information retrieval
Frequency
Large scale integration
Data analysis
Australia
Software engineering
Failure analysis
Fault Diagnosis
Sequence Alignment
API
Latent Semantic Indexing
Root Cause Analysis
Language
ISSN
1530-0803
2377-5408
Abstract
Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior. Equally important is the aspect of diagnosing (finding root-cause of) faults encountered. In this article, we address the problem of identifying the root cause of failure from the test sequences that caused failure. Taking analogies from biological sequence alignment and information retrieval domains we propose two approaches for finding the root cause of failure. The first approachis to align all the test sequences pertaining to a fault and identifying the common pattern among these sequences. The other approach is based on an information retrieval technique viz., the latent semantic indexing (LSI). Our experiments and analysis showed that the sequence alignment based approach has the potential to aid significantly in identifying the root cause of failure. The LSI based approach automatically clusters the test sequences based on their functionality, which assists in determining the different manifestations of a fault.