Risk Based Testing of Open Source Software (OSS)

Abstract

Open Source Software (OSS) has become a strategic asset for a number of reasons, such as its short time-to-market software service and product delivery, reduced development and maintenance costs, introduction of innovative features and its customization capabilities. By 2016 an estimated 95% of all commercial software packages will include OSS components. This pervasive adoption is not without risks for an industry that has experienced significant failures in product quality, timelines and delivery costs. Exhaustive testing of any software system and, specifically, of open source software components is usually not feasible due to limitations in time and resources. In risk-based testing approach test cases are selected and scheduled based on software risk analysis. This research introduces the strategy of risk-based adaptive testing of OSS by combining information on the OSS community ecosystem with risk-driven tests selection and scheduling strategy. A key feature of the proposed approach is the monitoring and analysis of OSS community dynamics, including chats and email communications, blogs, repositories of bugs and fixes, and more. The community and its dynamics are then monitored to detect anomaly communication between the community members. Our approach is demonstrated in the XWiki OSS, a Java-based environment that allows for the storing of structured data and the execution of server side scripts within the wiki interface. We illustrate our concepts, methods and approach behind risk based testing.