Software Fault Localization: an Overview of Research, Techniques, and Tools

This chapter describes traditional and intuitive fault localization techniques, including program logging, assertions, breakpoints, and profiling. Many advanced fault localization techniques have surfaced recently using the idea of causality, which is related to philosophical theories with an objective to characterize the relationship between events/causes and a phenomenon/effect. The chapter aims to classify fault localization techniques into nine categories, including slicing‐based, spectrum‐based, statistics‐based, machine learning‐based, data mining‐based, IR‐based, model‐based, spreadsheet‐based techniques, and additional emerging techniques. It lists some of the popular subject programs that have been used in different case studies and discusses how these programs have evolved through the years. The chapter describes different evaluation metrics to assess the effectiveness of fault localization techniques. One challenge for many empirical studies on software fault localization is that they require appropriate tool support for automatic or semiautomatic data collection and suspiciousness computation. The chapter also presents an overview on the key concepts discussed in this book.