Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

A Test Generation Method for Data Paths Using Easily Testable Functional Time Expansion Models and Controller Augmentation

Authors: Tetsuya Masuda; Jun Nishimaki; Toshinori Hosokawa; Hideo Fujiwara;

A Test Generation Method for Data Paths Using Easily Testable Functional Time Expansion Models and Controller Augmentation

Abstract

In recent years, various high-level test synthesis methods for data paths have been proposed for the improvement in design productivity and test cost reduction. Most of the approaches assume that controllers and data paths are isolated from each other, and hence the hardware overhead becomes large. On the other hand, the approach without separation of a controller and a data path usually decreases the testability. To resolve this problem, an approach that augments a controller by adding extra control functions to make a data path easily testable was proposed. However, the approach cannot always succeed in generating test sequences with high fault coverage if a general ATPG tool is used without knowing any information of augmented control functions. In this paper, we introduce "easily testable functional time expansion models for data paths", and propose a test generation method for data paths using easily testable functional time expansion models and controller augmentation such that easily testable functional time expansion models are controllable. Experimental results show the effectiveness of the proposed method for high level synthesis benchmark circuits.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    5
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!