This chapter illustrates the basic concepts of fault localization using a data mining technique. It utilizes the Trityp program to illustrate the general method. Formal concept analysis and association rule are two well-known methods for symbolic data mining. In their original inception, they both consider data in the form of an object-attribute table. In their original inception, they both consider data in the form of an object-attribute table. The chapter considers a debugging process in which a program is tested against different test cases. Two attributes, PASS and FAIL, represent the issue of the test case. The chapter extends the analysis of data mining for fault localization for the multiple fault situations. It addresses how data mining can be further applied to fault localization for GUI components. Unlike traditional software, GUI test cases are usually event sequences, and each individual event has a unique corresponding event handler.

翻译：本章阐述了一种利用数据挖掘技术进行故障定位的基本概念，并以Trityp程序为例说明其通用方法。形式概念分析与关联规则是符号数据挖掘中两种知名方法，其原始构想均将数据视为对象-属性表的形式。本章探讨了通过不同测试用例对程序进行测试的调试过程，其中PASS与FAIL两种属性表征测试用例的执行结果。研究将数据挖掘的故障定位分析扩展至多故障场景，并探讨了如何将数据挖掘进一步应用于图形用户界面组件的故障定位。与传统软件不同，GUI测试用例通常为事件序列，且每个独立事件都有唯一对应的事件处理程序。