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  • Optimizing Testing Efficiency with Error-Prone Path Identification and Genetic Algorithms

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    Author(s)
    Birt, James
    Sitte, Renate
    Griffith University Author(s)
    Sitte, Renate
    Birt, James
    Year published
    2004
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    Abstract
    We present a method for optimizing software testing efficiency by identifying the most error prone path clusters in a program. We do this by developing variable length genetic algorithms that optimize and select the software path clusters which are weighted with sources of error indexes. Although various methods have been applied to detecting and reducing errors in a whole system, there is little research into partitioning a system into smaller error prone domains for testing. Exhaustive software testing is rarely possible because it becomes intractable for even medium sized software. Typically only parts of a program can ...
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    We present a method for optimizing software testing efficiency by identifying the most error prone path clusters in a program. We do this by developing variable length genetic algorithms that optimize and select the software path clusters which are weighted with sources of error indexes. Although various methods have been applied to detecting and reducing errors in a whole system, there is little research into partitioning a system into smaller error prone domains for testing. Exhaustive software testing is rarely possible because it becomes intractable for even medium sized software. Typically only parts of a program can be tested, but these parts are not necessarily the most error prone. Therefore, we are developing a more selective approach to testing by focusing on those parts that are most likely to contain faults, so that the most error prone paths can be tested first. By identifying the most error prone paths, the testing efficiency can be increased.
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    Conference Title
    Proceedings 2004 Australian Software Engineering Conference (ASWEC2004)
    Publisher URI
    http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1290463
    DOI
    https://doi.org/10.1109/ASWEC.2004.1290463
    Copyright Statement
    © 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Publication URI
    http://hdl.handle.net/10072/2100
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    • Conference outputs

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