University of Illinois Urbana-Champaign

Reusing software tests for configuration testing: A case study of the Hadoop project

Ang, Ran

Content Files
ANG-THESIS-2019.pdf

Permalink

https://hdl.handle.net/2142/106384

Description

Title
Reusing software tests for configuration testing: A case study of the Hadoop project
Author(s)
Ang, Ran
Issue Date
2019-12-09
Director of Research (if dissertation) or Advisor (if thesis)
Xu, Tianyin
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2020-03-02T22:15:15Z
Keyword(s)
  • Configuration Testing
  • Hadoop
Abstract
Configuration is an inseparable piece of today’s software development. Due to its dynamic nature and lack of standardized checking procedure, misconfiguration has been one of the dominant factors contributing to software failures in production and wide spread outages. Existing techniques (static validation, system tests, canaries, etc.) for detecting misconfigurations have limitations, either being too coarse grained and unable to precisely exercise the changed configuration value, or not considering the interaction between configuration and software source code. Configuration testing takes pages from traditional software testing practices to test software configurations in a similar vein as how software code is tested. This thesis makes a first step exploration towards configuration testing, focusing on analyzing feasibility and effectiveness of reusing existing source code tests to test configuration values. Through building a semi-automated infrastructure associating unit tests with configuration parameters, and later run the associated tests against injected correct and incorrect configuration values for each parameter, this thesis shows that reusing existing software test for configuration testing directly could yield an effective rate of 41.7% and 48.8%, for Hadoop Common and HDFS, respectively. Further, this thesis conducts in-depth analysis on tests that cannot be effectively reused, categorizes code patterns of these tests that have false positives or negatives, and provides examples on rewriting these tests.
Graduation Semester
2019-12
Type of Resource
text
Permalink
http://hdl.handle.net/2142/106384
Copyright and License Information
Copyright 2019 Ran Ang

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