Covana: Precise identification of problems in Pex

Xusheng Xiao, Tao Xie, Nikolai Tillmann, Jonathan De Halleux

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Achieving high structural coverage is an important goal of software testing. Instead of manually producing test inputs that achieve high structural coverage, testers or developers can employ tools built based on automated test-generation approaches, such as Pex, to automatically generate such test inputs. Although these tools can easily generate test inputs that achieve high structural coverage for simple programs, when applied on complex programs in practice, these tools face various problems, such as the problems of dealing with method calls to external libraries or generating method-call sequences to produce desired object states. Since these tools are currently not powerful enough to deal with these various problems in testing complex programs, we propose cooperative developer testing, where developers provide guidance to help tools achieve higher structural coverage. In this demo, we present Covana, a tool that precisely identifies and reports problems that prevent Pex from achieving high structural coverage. Covana identifies problems primarily by determining whether branch statements containing not-covered branches have data dependencies on problem candidates.

Original languageEnglish (US)
Title of host publicationICSE 2011 - 33rd International Conference on Software Engineering, Proceedings of the Conference
Pages1004-1006
Number of pages3
DOIs
StatePublished - 2011
Externally publishedYes
Event33rd International Conference on Software Engineering, ICSE 2011 - Waikiki, Honolulu, HI, United States
Duration: May 21 2011May 28 2011

Publication series

NameProceedings - International Conference on Software Engineering
ISSN (Print)0270-5257

Other

Other33rd International Conference on Software Engineering, ICSE 2011
Country/TerritoryUnited States
CityWaikiki, Honolulu, HI
Period5/21/115/28/11

Keywords

  • data dependency
  • dynamic symbolic execution
  • problem identification
  • structural test generation

ASJC Scopus subject areas

  • Software

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