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DTSTART:19700927T020000
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CATEGORIES:ECS Seminars
CONTACT:Philip Oliver
DESCRIPTION:Fixing bugs is a lengthy process which currently requires sever
 al manual steps to be undertaken by a developer. Bugs often cause crashes\
 , which results in a program being abruptly exited. Reproducing a crash of
 ten takes a significant amount of time during this process\, as it require
 s a developer to identify where the crash occurred and where the taint beg
 an\, thus leading to the crash. Several tools\, such as EvoCrash\, STAR\, 
 and Beacon\, have been created to automate this process. EvoCrash and Beac
 on employ an evolutionary approach\; generating test cases to reproduce th
 e crash over a number of generations and are guided by a fitness function.
  In contrast\,\nSTAR uses the static analysis technique\, symbolic executi
 on\, to perform the reproduction. This PhD identifies several areas of wor
 k where there is currently no or little research. Objectives identified in
 clude creating a benchmark dataset\, performing an empirical evaluation on
  fitness functions for crash reproduction\, and combining both evolutionar
 y and static approaches to reduce search spaces and increase the effective
 ness of automated crash reproduction tools. If successful\, this research 
 will significantly reduce the time taken to reproduce and fix a crash\, in
 creasing the velocity and reliability of agile processes.\n
DTEND;TZID=Pacific/Auckland:20220228T153000
DTSTAMP:20260416T072855Z
DTSTART;TZID=Pacific/Auckland:20220228T143000
LOCATION:Zoom   https://vuw.zoom.us/my/ecspostgrad 
ORGANIZER:Philip Oliver
SUMMARY:Philip Oliver - Improving Automated Crash Reproduction for JavaScri
 pt
UID:seminar_ecs1300_20220224123811
URL:
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