CACOP-a random pattern testability analyzer

Author

Jone, Wen-Ben ; Das, Sunil R.

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Chung-Cheng Univ., Taiwan

Volume

25

Issue

5

fYear

1995

fDate

5/1/1995 12:00:00 AM

Firstpage

865

Lastpage

871

Abstract

In this paper a new method called CACOP For the detection probability analyses of random test patterns is proposed. Considering computational complexity, CACOP is a compromise between O(n²) testability analyses like full-range cutting algorithm (FRCA) and linear time testability analyses like the controllability observability program (COP). By propagating bounds of controllabilities and observabilities, CACOP can determine the detection probability lower bound (DPLB) efficiently. The DPLBs derived by CACOP are potentially higher (and thus more accurate) than by FRCA; in addition, CACOP is computationally more efficient than FRCA. The conventional linear time testability analyses cannot guarantee the derivation of DPLBs. On the contrary, CACOP can achieve the goal with tolerable increase in computing complexity

Keywords

automatic testing; built-in self test; computational complexity; controllability; integrated circuit testing; logic testing; observability; probability; CACOP; O(n²) testability analyses; computational complexity; controllability observability program; detection probability; full-range cutting algorithm; linear time testability analyses; lower bound; random pattern testability analyzer; Algorithm design and analysis; Automatic testing; Built-in self-test; Circuit faults; Circuit testing; Computational modeling; Controllability; Frequency; Pattern analysis; Test pattern generators;

fLanguage

English

Journal_Title

Systems, Man and Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9472

Type

jour

DOI

10.1109/21.376499

Filename

376499