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In recent years, software applications are widely used in the healthcare domain for diagnosing, scanning, generating reports and in treating various diseases. As healthcare systems are safety-critical systems, it should be highly reliable. It is one of the major concerns in healthcare systems as defects in healthcare applications might lead to serious injury or death. So the reliability of software plays a very important role in the healthcare domain. Reliability is one of the most significant attributes for computing software quality. It tells us about the failures occurred during the execution of the software. Unlike hardware reliability, it is very difficult to measure software reliability due to the complexity of the software. Standard way of reliability measurement such as the Mean Time To Failure (MTTF) and Mean Time between Failures (MTBF) can’t be an effective way of measurement in an integrated environment. As the reliability test points are more text based, some quantitative text analysis has to be done to measure reliability. In this paper, a model is proposed to arrive at accurate reliability of the healthcare application. Failure data is collected from various data points to analyze the reliability of healthcare application. A tool is used to parse the failure data from the applications which are in the form of log files. Further, this data is represented in a graphical format which helps us arrive at the current reliability status of the application and also help business to decide on how much to invest on quality roadmap.


High Reliability, Healthcare Applications, Hospitals, Patient Safety, Software Quality.