SAS-AF User's Guide: release 6.03 edition
SAS-AF User's Guide: release 6.03 edition
Scalable statistical bug isolation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Why Programs Fail: A Guide to Systematic Debugging
Why Programs Fail: A Guide to Systematic Debugging
SOBER: statistical model-based bug localization
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Cooperative bug isolation
Statistical debugging: simultaneous identification of multiple bugs
ICML '06 Proceedings of the 23rd international conference on Machine learning
Statistical debugging using compound boolean predicates
Proceedings of the 2007 international symposium on Software testing and analysis
Context-aware statistical debugging: from bug predictors to faulty control flow paths
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Argus: online statistical bug detection
FASE'06 Proceedings of the 9th international conference on Fundamental Approaches to Software Engineering
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The aim of this paper is to introduce a new statistical approach for software fault localization. To this end, a novel weighted predicate tree, P-network, has been introduced. The main contribution of the paper is to consider the behavior of branch statements, namely predicates, together, in failing and passing executions and detect those predicates having different behavior as fault relevant predicates. In order to assess the difference in behaviors of predicates together a null hypothesis testing has been used. The predicates with higher different ratios in failing and passing runs are selected as the nodes of the P- network. By using a BFS method on P-network all faulty predicates could be found. After that, by ranking the faulty predicates we are able to find the most relevant faulty ones, which might help the debugger easily locate the bug. The experiments on Siemens test suite reveal promising results.