Fault-coverage Maximizing March Tests for Memory Testing
- Resource Type
- Conference
- Authors
- Yun, Feng; Lin, Yunkun; Yunfei, Lou; Gao, Lei; Gera, Vaibhav; Li, Boxuan; Nekkanti, Vennela Chowdary; Pharande, Aditya Rajendra; Sheth, Kunal; Thommondru, Meghana; Ye, Guizhong; Gupta, Sandeep
- Source
- 2022 IEEE International Test Conference (ITC) ITC Test Conference (ITC), 2022 IEEE International. :529-533 Sep, 2022
- Subject
- Components, Circuits, Devices and Systems
Computing and Processing
Costs
Memory management
Testing
Memory test
Fault coverage maximization
March Tests
- Language
- ISSN
- 2378-2250
Every well-known march test for memories was generated to efficiently achieve 100% coverage of a target set of fault types. The question we pursue is: What to do if 100% coverage of the given target set cannot be achieved under tight constraints on test cost? We first study an obvious option: Remove some fault types from the given target set until a new or well-known test can cover 100% of the remaining fault types under the given test cost constraint. We find that this approach leaves significant room for improvement. We then pursue a different option and develop a new method which uses the original target set of fault types and generates a march test that maximizes the fault coverage under the given tight constraint on test cost. Our method generates fault-coverage maximizing tests for a wide range of target sets of fault types. A comparison with well-known march tests with equal lengths demonstrates that our new march tests provide significantly higher coverage for various sets of fault types. Importantly, our new march tests provide graceful decrease in fault coverage as we tighten constraints on test length. Hence our method and new march tests enable tradeoffs between test quality and test cost and provide a new direction of memory test research focused on fault-coverage-maximization.