Failure Proximity for Context-aware Applications

MPhil Thesis Defence


Title: "Failure Proximity for Context-aware Applications"

By

Miss Liping Gao


Abstract

The idea of failure clustering is to index all failures due to the same fault 
together. An effective failure clustering technique provides invaluable 
guidance to failure report analyses for both traditional applications and 
context-aware applications. Examples of these analyses include duplicate 
removal, failure prioritization, and patch suggestion. Underpinning an 
effective clustering technique is properly designed failure proximity. Failure 
proximity for conventional applications has been well studied. However, no such 
study has been conducted on context-aware applications. Existing failure 
proximity techniques commonly assume that the execution profiles of failing 
test runs due to different faults diverge. Unfortunately, this assumption does 
not necessarily hold for context-aware applications, which react to a continual 
data input stream capturing the contexts of their runtime environment.  We 
observe that only a few segments of the input stream are failure-inducing. 
Applying failure proximity techniques to the whole input streams that lead to 
failing test runs do not often result in significantly different execution 
profiles when these test runs trigger different faults. In this thesis, we 
propose to perform failure clustering by applying failure proximity techniques 
only to those failure-inducing segments. Our experiments show that our approach 
greatly improved the accuracy of failure proximity for context-aware 
applications. To the best of our knowledge, our work is the first attempt of 
studying the effectiveness of failure proximity for context-aware applications.


Date:			Friday, 5 August 2011

Time:			3:00pm – 5:00pm

Venue:			Room 3588
 			Lifts 27/28

Committee Members:	Prof. Shing-Chi Cheung (Supervisor)
 			Dr. Lin Gu (Chairperson)
 			Dr. Charles Zhang


**** ALL are Welcome ****