Title
TEA: A Test Generation Algorithm for Designs with Timing Exceptions
Abstract
Timing exceptions are commonly used to indicate that the timing of certain paths have been relaxed so as to enable the design to meet timing closure. Generating scan-based test patterns without considering timing exceptions can lead to invalid test responses, resulting in unpredictable test quality impact. The existing simulation-based solution masks out unreliable signals after a test pattern is generated. If the signals required for detecting the target fault are unreliable and masked out, the generated test pattern fails to detect the target fault, and it is discarded. To achieve an acceptable test coverage, several iterations of test generation with a randomized decision-making process are typically required where different tests are generated for target faults. In this paper, an innovative deterministic ATPG algorithm called TEA (Timing Exception ATPG) is proposed to prevent the generated test patterns from being impacted by timing exceptions. The deterministic algorithm is compatible with the existing simulation-based approach. In this simulation environment, TEA is complete such that for a target fault, the test pattern generated is guaranteed to detect it. If a test pattern cannot be generated using TEA, the target fault is untestable given the timing exception paths in the design and the existing simulation environment. Compared to the existing simulation-based approach, using TEA can generate a more effective test set, improving test coverage, test pattern count, and the total ATPG run time significantly.
Year
DOI
Venue
2019
10.1109/ATS47505.2019.000-6
2019 IEEE 28th Asian Test Symposium (ATS)
Keywords
Field
DocType
Timing exceptions,False paths,Multi-cycle paths,ATPG
Code coverage,Automatic test pattern generation,Computer science,Test quality,Algorithm,Deterministic algorithm,Timing closure,Test set
Conference
ISSN
ISBN
Citations 
1081-7735
978-1-7281-2696-8
0
PageRank 
References 
Authors
0.34
7
7
Name
Order
Citations
PageRank
Naixing Wang101.69
Chen Wang225315.83
Kun-Han Tsai360040.79
Wu-tung Cheng41350121.45
Xijiang Lin568742.03
Mark Kassab665448.74
Irith Pomeranz73829336.84