In order to reduce the test cost, built-in self test (BIST) is widely used. One of the serious problems of BIST is that the compacted signature in BIST has very little information for fault diagnosis. Especially, it is difficult to determine which tests detect a fault. Therefore, it is important to develop an efficient fault diagnosis method by using incompletely identified pass/fail information. Where the incompletely identified pass/fail information means that a failing test block consists of at least one failing test and some passing tests, and all of the tests in passing test blocks are the passing test. In this paper, we propose a method to locate open faults by using incompletely identified pass/fail information. Experimental results for ISCAS'85 and ITC'99 benchmark circuits show that the number of candidate faults becomes less than 5 in many cases.

With the increasing complexity of LSI, Built-In Self Test (BIST) is a promising technique for production testing. We herein propose a method for diagnosing multiple stuck-at faults based on the compressed responses from BIST. We refer to fault diagnosis based on the ambiguous test pattern set obtained by the compressed responses of BIST as post-BIST fault diagnosis [1]. In the present paper, we propose an effective method by which to perform post-BIST fault diagnosis for multiple stuck-at faults. The efficiency of the success ratio and the feasibility of diagnosing large circuits are discussed.

In general, we do not know which fault model can explain the cause of the faulty values at the primary outputs in a circuit under test before starting diagnosis. Moreover, under Built-In Self Test (BIST) environment, it is difficult to know which primary output has a faulty value on the application of a failing test pattern. In this paper, we propose an effective diagnosis method on multiple fault models, based on only pass/fail information on the applied test patterns. The proposed method deduces both the fault model and the fault location based on the number of detections for the single stuck-at fault at each line, by performing single stuck-at fault simulation with both passing and failing test patterns. To improve the ability of fault diagnosis, our method uses the logic values of lines and the condition whether the stuck-at faults at the lines are detected or not by passing and failing test patterns. Experimental results show that our method can accurately identify the fault models (stuck-at fault model, AND/OR bridging fault model, dominance bridging fault model, or open fault model) for 90% faulty circuits and that the faulty sites are located within two candidate faults.