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Test coverage is sometimes used as a way to measure how thoroughly software is tested. Coverage is used by software developers and sometimes by vendors to indicate their confidence in the readiness of their software. This survey studies and compares 17 coverage-based testing tools focusing on, but not restricted to coverage measurement. We also survey additional features, including program prioritization for testing, assistance in debugging, automatic generation of test cases, and customization of test reports. Such features make tools more useful and practical, especially for large-scale, real-life commercial software applications. Our initial motivations were both to understand the available test coverage tools and to compare them to a tool that we have developed, called eXVantage 1 (a tool suite that includes code coverage testing, debugging, performance profiling, and reporting). Our study shows that each tool has its unique features tailored to its application domains. Therefore this study can be used to pick the right coverage testing tools depending on various requirements.

Abstract-There is a lack of published studies providing empirical support for the assumption at the heart of product line development, namely, that through structured reuse later products will be less fault-prone. This paper presents results from an empirical study of pre-release fault and change proneness from four products in an industrial software product line. The objectives of the study are (1) to determine the association between various software metrics, as well as their correlation with the number of faults at the component level; (2) to characterize the fault and change proneness at various degrees of reuse; and (3) to determine how existing products in the software product line affect the quality of subsequently developed products and our ability to make predictions. The research results confirm, in a software product line setting, the findings of others that faults are more highly correlated to change metrics than to static code metrics. Further, the results show that variation components unique to individual products have the highest fault density and are the most prone to change. The longitudinal aspect of our research indicates that new products in this software product line benefit from the development and testing of previous products. For this case study, the number of faults in variation components of new products is predicted accurately using a linear model built on data from the previous products.

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