NDLI: Semantic fault diagnosis: automatic natural-language fault descriptions

Content Provider	ACM Digital Library
Author	Jones, James A. DiGiuseppe, Nicholas
Abstract	Before a fault can be fixed, it first must be understood. However, understanding why a system fails is often a difficult and time consuming process. While current automated-debugging techniques provide assistance in knowing where a fault is, developers are left unaided in understanding what a fault is, and why the system is failing. We present Semantic Fault Diagnosis (SFD), a technique that leverages lexicographic and dynamic information to automatically capture natural-language fault descriptors. SFD utilizes class names, method names, variable expressions, developer comments, and keywords from the source code to describe a fault. SFD can be used immediately after observing a failing execution and requires no input from developers or bug reports. In addition we present motivating examples and results from a SFD prototype to serve as a proof of concept.
Starting Page	1
Ending Page	4
Page Count	4
File Format	PDF
ISBN	9781450316149
DOI	10.1145/2393596.2393623
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-11-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Program comprehension Maintenance Testing
Content Type	Text
Resource Type	Article

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Semantic fault diagnosis: automatic natural-language fault descriptions