Building test oracles by clustering failures

Rafig Almaghairbe, Marc Roper

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

3 Citations (Scopus)
151 Downloads (Pure)

Abstract

In recent years, software testing research has produced notable advances in the area of automated test data generation, but the corresponding oracle problem (a mechanism for determine the (in)correctness of an executed test case) is still a major problem. In this paper, we present a preliminary study which investigates the application of anomaly detection techniques (based on clustering) to automatically build an oracle using a system’s input/output pairs, based on the hypothesis that failures will tend to group into small clusters. The fault detection capability of the approach is evaluated on two systems and the findings reveal that failing outputs do indeed tend to congregate in small clusters, suggesting that the approach is feasible and has the potential to reduce by an order of magnitude the numbers of outputs that would need to be manually examined following a test run.
Original languageEnglish
Title of host publication2015 IEEE/ACM 10th International Workshop on Automation of Software Test (AST)
PublisherIEEE
Pages3-7
Number of pages5
DOIs
Publication statusPublished - 2015

Keywords

  • software testing
  • automated test data generation
  • oracle problem
  • anomaly detection techniques
  • fault detection

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