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Method and apparatus for adaptively learning test error sources to reduce the total number of test measurements required in real-time

  • US 6,324,486 B1
  • Filed: 03/01/1999
  • Issued: 11/27/2001
  • Est. Priority Date: 03/01/1999
  • Status: Expired due to Fees
First Claim
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1. A method for adaptively learning a set of real-time measurements to obtain in real-time during execution of an automated test, said method comprising the steps of:

  • measuring a current set of real-time measurements in real-time, said current set of real-time measurements comprising a subset of a full set of required measurements, each of said full set of required measurements being required to determine whether said test passed or failed;

    obtaining a current set of historical measurements, said current set of historical measurements comprising corresponding historical measurement values for each of said required measurements that are not included in said current set of real-time measurements;

    determining whether said test passed or failed based on said measured real-time measurements and said current set of historical measurements substituted for those required measurements that are not included in said current set of real-time measurements;

    if said test fails;

    choosing a current retry set of real-time measurements, said current retry set of real-time measurements comprising a subset of said required measurements different than said current set of real-time measurements;

    measuring said current retry set of real-time measurements in real-time obtaining a current retry set of historical measurements, said current retry set of historical measurements comprising corresponding historical measurement values for each of said required measurements that are not included in said current retry set of real-time measurements; and

    redetermining whether said test passed or failed based on said current retry set of real-time measurements and said current retry set of historical measurements.

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