Detecting system failures from durations and binary cues

Nir Shahar, Joachim Meyer*, Michael Hildebrandt, Vered Rafaely

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Durations are often used to judge the status of an invisible process. However, the apparent duration of an interval depends on the actual duration and on other variables, such as the workload during the interval and the persons expectations. An experiment dealt with the use of durations as an information source on the state of an invisible process and the effects of expectations and workload on decisions regarding the process. Eighty-nine participants observed a computerized simulation of a process which could be either intact or faulty, with intact processes ending on average sooner than faulty ones, and they had to indicate whether or not the process is intact and to estimate its duration. A binary cue with either intermediate or no validity indicated whether the process was supposedly intact or not, generating expectations about the duration of the process. Perceived durations and the decisions about the intactness of a process depended on the actual process duration, as well as on the expectations generated by the binary cue. In addition, task workload affected time estimates, but it had no effect on participants tendency to adhere to cue recommendations or their ability to distinguish between intact and faulty processes. Results show that users duration-based decisions about the status of a computerized process are affected by internal and external cues. While users can use durations as an information source, they should, whenever possible, be accompanied by additional indicators, lowering the inherent uncertainty in the duration estimation process.

Original languageEnglish
Pages (from-to)552-560
Number of pages9
JournalInternational Journal of Human Computer Studies
Issue number8
StatePublished - Aug 2012
Externally publishedYes


  • Apparent duration
  • Categorization decisions
  • Decision making
  • Failure detection
  • Signal detection theory
  • Time estimation


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