Abstract. Aging-related bugs can lead to software aging, whose performance is the slow response on software system though the software does not crash. This paper aims to propose the measurement method of software health to quantitatively show the impact of aging-related bugs on software. The effect of the bugs and the elements were analyzed. The Gaussian mixture model was developed to measure the degree of software health, which provide the basis for the software failure alarming and failure prediction. Finally, the details of the method were shown by a case study on Hadoop Distributed File System.

Software health management is defined as a technology that applies the principles and techniques similar to the one used for system heath management to software systems. The goal of software health management is to maintain software system function and performance and improve software system availability and reliability, even when software system meets health problem. System health management has been a well-established discipline in aerospace systems, and many systems called health management systems have been developed on board. But software health management has not been a formal discipline yet and the concept of 'software health' has not been formed. This paper mainly takes the Hadoop distributed file system as the research object, analyzes and studies some health issues including the definition and connotation of software health. HDFS health assessment framework is also presented, which is based on the analysis of the design principles.