Handbook of software fault localization : foundations and advances /
edited by W. Eric Wong, T. H. Tse.
- 1 online resource (xviii, 590 pages) : illustrations (some color)
Includes bibliographical references and index.
Software Fault Localization: An Overview of Research, Techniques, and Tools -- Traditional Techniques for Software Fault Localization -- Slicing-based Techniques for Software Fault Localization -- Spectrum-based Techniques for Software Fault Localization -- Statistics-based Techniques for Software Fault Localization -- Machine Learning-based Techniques for Software Fault Localization -- Data Mining-based Techniques for Software Fault Localization -- Information Retrieval-based Techniques for Software Fault Localization -- Model-based Techniques for Software Fault Localization -- Software Fault Localization in Spreadsheets -- Theoretical Aspects of Software Fault Localization -- Software Fault Localization for Multiple Bugs -- Emerging Aspects of Software Fault Localization.
"Software fault localization is one of the most expensive activities in program debugging. It can be further divided into two major parts. The first part is to use a technique to identify suspicious code that may contain program bugs. The second part is for programmers to actually examine the identified code to decide whether it indeed contains bugs. Fault localization has historically been a manual task that has been recognized to be time consuming and tedious as well as prohibitively expensive, given the size and complexity of large-scale software systems today. Furthermore, manual fault localization relies heavily on the software developer's experience, judgment, and intuition to identify and prioritize code that is likely to be faulty. These limitations have led to a surge of interest in developing techniques that can partially or fully automate the localization of faults in software while reducing human input"--