Science & Engineering Research Support soCiety (SERSC)
The authors' interested in estimating the degree of software reliability based on software development project data. It is widely-known that several software development attributes which are measured can be used to evaluate and predict software reliability/quality via multi-variable analyses. In this paper, they focus on the data treatment method which is needed prior to the software reliability assessment, since the software development data sets often include missing data. This paper discusses the method of data preparation against missing data and their effectiveness by using the Random Forest as a multi-variable analysis.