scholarly journals A Dynamic Fault Localization Technique with Noise Reduction for Java Programs

2011 ◽  
Author(s):  
Jian Xu ◽  
W.K. Chan ◽  
Zhenyu Zhang ◽  
T.H. Tse ◽  
Shanping Li
Keyword(s):  
Noise Reduction ◽  
Fault Localization ◽  
Localization Technique ◽  
Java Programs

scholarly journals A general noise-reduction framework for fault localization of Java programs

2013 ◽  
Vol 55 (5) ◽  
pp. 880-896 ◽  
Author(s):  
Jian Xu ◽  
Zhenyu Zhang ◽  
W.K. Chan ◽  
T.H. Tse ◽  
Shanping Li
Keyword(s):  
Noise Reduction ◽  
Fault Localization ◽  
Java Programs

MuSim: Mutation-based Fault Localization Using Test Case Proximity

2021 ◽  
Vol 31 (05) ◽  
pp. 725-744
Author(s):  
Arpita Dutta ◽  
Amit Jha ◽  
Rajib Mall
Keyword(s):  
Fault Localization ◽  
Test Case ◽  
Test Cases ◽  
Similarity Metrics ◽  
Localization Technique ◽  
Evaluation Metric

Fault localization techniques aim to localize faulty statements using the information gathered from both passed and failed test cases. We present a mutation-based fault localization technique called MuSim. MuSim identifies the faulty statement based on its computed proximity to different mutants. We study the performance of MuSim by using four different similarity metrics. To satisfactorily measure the effectiveness of our proposed approach, we present a new evaluation metric called Mut_Score. Based on this metric, on an average, MuSim is 33.21% more effective than existing fault localization techniques such as DStar, Tarantula, Crosstab, Ochiai.

Fault Detection Technique Based on Fine Grained Slicing Spectrum

2014 ◽  
Vol 543-547 ◽  
pp. 963-966
Author(s):  
Xi Guo
Keyword(s):  
Fault Detection ◽  
Fault Localization ◽  
Experimental Results ◽  
Detection Technique ◽  
Test Coverage ◽  
Localization Technique ◽  
Fine Grained ◽  
Software Errors ◽  
Check Points ◽  
Target Program

Test coverage information is usually used to compute the suspiciousness to locate the software errors in the current fault localization techniques, but this technique usually do not consider the reliance information within the target program, and the precision is also very low. A novel fault localization technique based on fine grained slicing spectrum is proposed in this paper, which can increase the efficiency of fault localization. This technique analyzes the reliance information under fine grained level, and selects the check points which are prone to be faulty, and the faulty statements is located according to the suspicious result. Experimental results show that this technique has better efficiency than the current techniques.

Noise Reduction for Spectrum-based Fault Localization

2013 ◽  
Vol 6 (5) ◽  
pp. 117-126 ◽  
Author(s):  
Patrick Daniel ◽  
Kwan Yong Sim
Keyword(s):  
Noise Reduction ◽  
Fault Localization
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