2015Unpublished venueRequires access

Automating Crash Report Analysis Using 'Exception-based Patterns' & 'Reference Assembly mapping'

Venkata Krishnan Paila, Jaile Sebes

Open publisher page 1 citations

Abstract

When a complex real-world application is deployed post-release, a number of crash reports are generated. As the number of clients using the product increases, so do the crash reports. Typically, the approach followed in many software organizations is to manually analyze a crash report to identify the erroneous module responsible for the crash. Naturally, when a large number of crash reports are generated daily, the development team requires a substantial amount of time to analyze all these reports. This in turn increases the turn-around time for crash report analysis which often leaves customers unhappy. In order to address this problem, we have developed an automated method to analyze a crash report and identify the erroneous module. This method is based on a novel algorithm that searches for exception-based patterns in crash reports and maps reference assemblies. We have applied this method to several thousand crash reports across four sub-systems of an industrial automation application. Results indicate that the algorithm not only achieves a high accuracy in finding the erroneous module and subsystem behind a crash, but also significantly reduces the turn-around time for crash report analysis.

About this research paper

What this paper is about

When a complex real-world application is deployed post-release, a number of crash reports are generated. As the number of clients using the product increases, so do the crash reports. Typically, the approach followed in many software organizations is to manually analyze a crash report to identify the erroneous module responsible for the crash. Naturally, when a large number of crash reports are generated daily, the development team requires a substantial amount of time to analyze all these reports. This in turn increases the turn-around time for crash report analysis which often leaves customers unhappy. In order to address this problem, we have developed an automated method to analyze a crash report and identify the erroneous module. This method is based on a novel algorithm that searches for exception-based patterns in crash reports and maps reference assemblies. We have applied this method to several thousand crash reports across four sub-systems of an industrial automation application. Results indicate that the algorithm not only achieves a high accuracy in finding the erroneous module and subsystem behind a crash, but also significantly reduces the turn-around time for crash report analysis.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

When a complex real-world application is deployed post-release, a number of crash reports are generated. As the number of clients using the product increases, so do the crash reports. Typically, the approach followed in many software organizations is to manually analyze a crash report to identify the erroneous module responsible for the crash. Naturally, when a large number of crash reports are generated daily, the development team requires a substantial amount of time to analyze all these reports. This in turn increases the turn-around time for crash report analysis which often leaves customers unhappy. In order to address this problem, we have developed an automated method to analyze a crash report and identify the erroneous module. This method is based on a novel algorithm that searches for exception-based patterns in crash reports and maps reference assemblies. We have applied this method to several thousand crash reports across four sub-systems of an industrial automation application. Results indicate that the algorithm not only achieves a high accuracy in finding the erroneous module and subsystem behind a crash, but also significantly reduces the turn-around time for crash report analysis.

Key concepts: Crash, Computer science, Automation, Software, Engineering, Operating system, Mechanical engineering

Related papers

Back to paper searchBrowse research topicsOriginal source
Automating Crash Report Analysis Using 'Exception-based Patterns' & 'Reference Assembly mapping' — Research Paper | ScholarLens