Software reliability prediction for open source software adoption systems based on early lifecycle measurements

Abstract

These days, the use of open source software is increasing, as is the importance of its role in many applications. According to the Gartner report, 80 percent of all commercial software will include elements of open-source technology by 2012. Currently, many commercial products use open source software (OSS) in many fields such as embedded systems, web management systems, and software development systems. Likewise, the study of open source software has been increasing in the software engineering arena. Many OSSs are being used in various fields as either a part or the whole of a software system. Also, various OSSs are being modified and adopted into software products with their own quality level. However, it is difficult to measure the quality of an OSS before use and to select the proper one. These difficulties come from OSS features such as a lack of bug information, unknown development schedules, and variable documentations. Conventional software reliability models are not adequate to assess the reliability of a software system in which an OSS is being adopted as a new add-on feature because the OSS can be modified while Commercial Off-The-Shelf (COTS) software cannot. This paper provides an approach toward a software reliability assessment of an OSS-adopted software system during the early stages of a software life-cycle. We identify the software factors that affect the reliability of a software system using the COCOMOII modeling methodology. The first step in the factor analysis is identifying the factors that affect the reliability of software systems. This step was done by analyzing such literature as IEEE Std982.1-1998. We selected 7 factors that can be used in OSS-adopted software systems. The main selection criteria are metric availability in OSS-adopted systems and product metric based measures. The second step in the factor analysis is a behavioral analysis. The behavioral analysis is used to determine how these metrics affect the reliability of so...