Abstract — Understanding the causes for failure is one of the bottlenecks in the educational process. Despite failure prediction has been pursued, models behind that prediction, most of the time, do not give a deep insight about failure causes. In this paper, we introduce a new method for mining fault trees automatically, and show that these models are a precious help on identifying direct and indirect causes for failure. An experimental study is presented in order to access the drawbacks of the proposed method. Keywords-mining behaviors, fault trees; pattern mining I
Fault tree analysis is a well-known technique in reliability engineering and risk assessment, which ...
We present a method to enhance fault localization for software systems based on a frequent pattern m...
We present a method to enhance fault localization for software systems based on a frequent pattern m...
Industries with safety-critical systems increasingly collect data on events occurring at the level o...
In manufacturing processes the automated identification of faulty operating conditions that might le...
Software is a ubiquitous component of our daily life. We often depend on the correct working of soft...
The problem of modeling knowledge about the fault behavior of a system and utilizing this model for ...
In recent years, error mining approaches were developed to help identify the most likely sources of ...
Software is a ubiquitous component of our daily life. We of-ten depend on the correct working of sof...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...
We present a decision tree learning approach to diagnosing failures in large Internet sites. We reco...
Software fault and effort prediction are important tasks to minimize costs of a software project. In...
This work presents a systematic, incremental approach to identifying causes of potential failures in...
Context: Software fault prediction has been an important research topic in the software engineering ...
Many industrial sectors have been collecting big sensor data. With recent technologies for processin...
Fault tree analysis is a well-known technique in reliability engineering and risk assessment, which ...
We present a method to enhance fault localization for software systems based on a frequent pattern m...
We present a method to enhance fault localization for software systems based on a frequent pattern m...
Industries with safety-critical systems increasingly collect data on events occurring at the level o...
In manufacturing processes the automated identification of faulty operating conditions that might le...
Software is a ubiquitous component of our daily life. We often depend on the correct working of soft...
The problem of modeling knowledge about the fault behavior of a system and utilizing this model for ...
In recent years, error mining approaches were developed to help identify the most likely sources of ...
Software is a ubiquitous component of our daily life. We of-ten depend on the correct working of sof...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...
We present a decision tree learning approach to diagnosing failures in large Internet sites. We reco...
Software fault and effort prediction are important tasks to minimize costs of a software project. In...
This work presents a systematic, incremental approach to identifying causes of potential failures in...
Context: Software fault prediction has been an important research topic in the software engineering ...
Many industrial sectors have been collecting big sensor data. With recent technologies for processin...
Fault tree analysis is a well-known technique in reliability engineering and risk assessment, which ...
We present a method to enhance fault localization for software systems based on a frequent pattern m...
We present a method to enhance fault localization for software systems based on a frequent pattern m...