Model-based testing of software has proved effective for automation of testing and efficient error discovery, by utilizing modeled behavior of the system under test and automated test case generation. One of the important challenges in model-based testing is locating the fundamental sources of encountered errors. A root cause analysis solution should be able to find the causes of errors among different components in a model-based testing process, while automating the analysis to eliminate daunting data-intensive manual work. We present a design for a Root Cause Analyzer (RCA) component, aimed at automated test analysis utilizing the outputs generated in a model-based testing process, and producing human and machine readable analysis reports...
In order to remain competitive, companies need to be constantly vigilant and aware of the current tr...
With the growth of system size and complexity, reliability has become a major concern for large-scal...
In this paper we present a new root cause analysis algorithm for discovering the most likely causes ...
Model-based testing of software has proved effective for automation of testing and efficient error d...
Due to the complex software and hardware architecture and the heterogenic environment they are used ...
International audienceToday's network operators strive to create self-healing cellular networks that...
Model-based testing (MBT) is a technique for generating test cases from test models. One of the bene...
Troubleshooting encompasses a variety of processes required for the solution of mobile network degra...
Software testing is an important process for ensuring the quality of the software. As the complexity...
The concept of model-based test was developed in order to reduce the production test effort for data...
This Master's Thesis describes one example on how to automatically generate tests for real-time prot...
Automated Software testing is becoming increasingly popular, which in turn creates more information ...
We apply machine learning to automate the root cause analysis in agile software testing environments...
System integration testing in the defense and aerospace industry is becoming increasingly complex. T...
Fault Diagnosis of power systems has attracted great attention in recent years. In the paper, the au...
In order to remain competitive, companies need to be constantly vigilant and aware of the current tr...
With the growth of system size and complexity, reliability has become a major concern for large-scal...
In this paper we present a new root cause analysis algorithm for discovering the most likely causes ...
Model-based testing of software has proved effective for automation of testing and efficient error d...
Due to the complex software and hardware architecture and the heterogenic environment they are used ...
International audienceToday's network operators strive to create self-healing cellular networks that...
Model-based testing (MBT) is a technique for generating test cases from test models. One of the bene...
Troubleshooting encompasses a variety of processes required for the solution of mobile network degra...
Software testing is an important process for ensuring the quality of the software. As the complexity...
The concept of model-based test was developed in order to reduce the production test effort for data...
This Master's Thesis describes one example on how to automatically generate tests for real-time prot...
Automated Software testing is becoming increasingly popular, which in turn creates more information ...
We apply machine learning to automate the root cause analysis in agile software testing environments...
System integration testing in the defense and aerospace industry is becoming increasingly complex. T...
Fault Diagnosis of power systems has attracted great attention in recent years. In the paper, the au...
In order to remain competitive, companies need to be constantly vigilant and aware of the current tr...
With the growth of system size and complexity, reliability has become a major concern for large-scal...
In this paper we present a new root cause analysis algorithm for discovering the most likely causes ...