Logic Built-In Self-Test: Design Techniques & Problem-Solving

1. Chapter 5 Logic Built-In Self-Test

2. What is this chapter about? • Introduce the basic concepts of logic BIST • BIST Design Rules • Test pattern generation and output response analysis techniques • Fault Coverage Enhancement • Various BIST timing control diagrams • A Design Practice

3. Introduction • What are the problems in today’s semiconductor testing? • Traditional test techniques become quite expensive • No longer provide sufficiently high fault coverage • Why do we need built-in self-test (BIST)? • For mission-critical applications • Detect un-modeled faults • Provide remote diagnosis

4. BIST Techniques Categories • Online BIST • Concurrent online BIST • Non Concurrent online BIST • Offline BIST • Functional offline BIST • Structural offline BIST

5. BIST Online Offline Functional Structural Concurrent A General Form of Logic BIST [Abramovici 1994] Non-concurrent Logic BIST Techniques

6. Test Pattern Generator (TPG) Logic Circuit Under Test BIST (CUT) Controller Output Response Analyzer (ORA) ATypical Logic BIST System Structural off-line BIST

7. BIST Design Rules Logic BIST requires much more stringent design restrictions when compared to conventional scan. Therefore, when designing a logic BIST system, it is essential that the circuit under test meet all scan design rules and BIST specific design rules, called BIST design rules.

8. Typical X-bounding Methods Methods for blocking an unknown (X) source

9. X-bounding Methods Depending on the nature of each unknown (X) source, several X-bounding methods can be appropriate for use. Common problems: (1) Increase the area of the design. (2) Impact timing.

10. Typical Unknown Sources • Analog Blocks • Adding bypass logic. • Adding control-only scan point • Memories and Non-Scan Storage Elements • Bypass logic • Initialization • Combinational Feedback Loops • Scan points

11. Typical Unknown Sources (cont’d) • Asynchronous Set/Reset Signals • using the existing scan enable (SE) signal to protect each shift operation and adding a set/reset clock point (SRCK) on each set/reset signal to test the set/reset circuitry. [Abdel-Hafez 2004]

12. Typical Unknown Sources (cont’d) • Asynchronous Set/Reset Signals Timing control diagram for testing data and set/reset faults

13. Typical Unknown Sources (cont’d) • Tri-State Buses • Re-synthesize each bus with multiplexers. • One-hot decoder A one-hot decoder for testing a tri-state bus with 2 drivers

14. Typical Unknown Sources (cont’d) • False Paths • 0-control point • 1-control point • Critical Paths • Adding an extra input pin to a selected combinational gate on the critical path.

15. Typical Unknown Sources (cont’d) • Multiple-Cycle Paths • 0-control point • 1-control point • Holding certain scan cell output states • Floating Ports • PI or PO must have a proper connection to Power (Vcc) or Ground (Vss). • Floating inputs to any internal modules must be avoided.

16. Typical Unknown Sources (cont’d) • Bi-directional I/O Ports • Fix the direction of each bi-directional I/O port to either input or output mode. Forcing a bi-directional port to output mode

17. Q Q D Q Q O T D D D R P CUT A G CK CK CK CK CK1 CK2 CK3 Re-Timing Races and hazards caused by clock skews may occur between the TPG and the (scan chain) inputs of the CUT as well as between the (scan chain) outputs of the CUT and the ORA. To avoid these potential problems and ease physical implementation, we recommend adding re-timing logic between the TPG and the CUT and between the CUT and the ORA. Re-timing logic among the TPG, CUT, and ORA

18. Test Pattern Generation • Test pattern generators (TPGs) constructed from linear feedback shift registers (LFSRs) • TPG • Exhaustive testing • Pseudo-random testing • Pseudo-exhaustive testing

19. hn-1 Sin-2 Si0 Sin-1 Si1 hn-2 h2 h1 Standard LFSR • Consists of n D flip-flops and a selected number of exclusive-OR (XOR) gates [Golomb 1982] An n-stage (external-XOR) standard LFSR

20. Si0 Sin-1 Si1 Sin-2 h1 h2 hn-2 hn-1 Modular LFSR • Each XOR gate placed between two adjacent D flip-flops [Golomb 1982] An n-stage (internal-XOR) modular LFSR

21. LFSR Properties • The internal structure of the n-stage LFSR can be described by a characteristic polynomial of degree n, f(x). hiis either 1 or 0,depending on the feedback path

22. LFSR Properties

23. LFSR Properties • Let Si represent the contents of the n-stage LFSR after shifts of the initial contents,S0,of the LFSR, and Si(x) be the polynomial representation of Si IfT is the smallest positive integer such that f(x) divides ,then the integer T is called the period of the LFSR.

24. LFSR Properties • If T = 2n −1, then the n-stage LFSR generating the maximum-length sequence is called a maximum-length LFSR. • Define a primitive polynomial of degree n as a polynomial that divides 1+xT, but not 1+xi, for any integer i < T, where T = 2n−1 [Colomb 1982].

25. 4-stage standard and modular LFSRs • 4-stage Standard LFSR • 4-stage Modular LFSR

26. 4-stage standard and modular LFSRs • The first test sequence repeats after 6 patterns • The second test sequence repeats after 15 patterns, the LFSRs have periods of 6 and 15, respectively. • This further implies that 1+x^6 can be divided by 1+x^2 +x^4, and 1+x^15 can be divided by 1+x+x^4.

27. 4-stage standard and modular LFSRs • A primitive polynomial is irreducible. Because T = 15 = 2n −1, • the characteristic polynomial, f(x) = 1+x+x4, used to construct the previous Figure is a primitive polynomial; thus, the modular LFSR is a maximum-length LFSR.

28. Finite field arithmetic • Arithmetic in a finite field is different from standard integer arithmetic. There are a limited number of elements in the finite field; all operations performed in the finite field result in an element within that field.

29. Finite field arithmetic • The finite field with pn elements is denoted GF(pn) and is also called the Galois Field, in honor of the founder of finite field theory, Évariste Galois. • A particular case is GF(2), where addition is exclusive OR (XOR) and multiplication is AND. Since the only invertible element is 1, division is the identity function

30. Finite field arithmetic • For example, the following are equivalent representations of the same value in a characteristic 2 finite field: • Polynomial: x6 + x4 + x + 1 • Binary: {01010011}

31. Finite field arithmetic • In a finite field with characteristic 2, addition modulo 2, subtraction modulo 2, and XOR are identical. Thus, • Polynomial: (x6 + x4 + x + 1) + (x7 + x6 + x3 + x) = x7 + x4 + x3 + 1 • Binary: {01010011} + {11001010} = {10011001}

32. Finite field arithmetic • Under regular addition of polynomials, the sum would contain a term 2x6, but that this term becomes 0x6 and is dropped when the answer is reduced modulo 2. • Here is a table with both the normal algebraic sum and the characteristic 2 finite field sum of a few polynomials:

33. Finite field arithmetic (Multiplication) • (x6 + x4 + x + 1)(x7 + x6 + x3 + x) = (x13 + x12 + x9 + x7) + (x11 + x10 + x7 + x5) + (x8 + x7 + x4 + x2) + (x7 + x6 + x3 + x) = x13 + x12 + x9 + x11 + x10 + x5 + x8 + x4 + x2 + x6 + x3 + x = x13 + x12 + x11 + x10 + x9 + x8 + x6 + x5 + x4 + x3 + x2 + x

34. Example: LFSR • G(X) = X3 + X1 + 1 represents an LFSR with feedback taps 3 and 1

35. LFSR • For example, we may be asked to find all sets of maximal-length feedback taps for an LFSR with m=3 registers. We do this as follows: The length of the m-sequences will be N=23-1=7. We know that the solution lies in all the primitive factors of polynomial X7+1. We use modulo-2 linear algebra (probably with the aid of a computer algorithm) to find the prime factors to be

36. Hybrid LFSR Fully decomposable iff both b(x) and c(x) have no common terms and there exists an integer j such that Assume: f(x) is fully decomposable A (hybrid) top-bottom LFSR [Wang 1988a] can be constructed: Indicate the XOR gate with one input Is connected to the feedback path, not between stages

37. 5-stage hybrid LFSRs (a) 5-stage top-bottom LFSR (b) 5-stage bottom-top LFSR

38. Hybrid LFSRs • Assume that a standard or modular LFSR uses m XOR gates, where m is an odd number. • If its characteristic polynomial, f(x), is fully decomposable, then a hybrid LFSR can be realized with only (m+1)/2 XOR gates.

39. Primitive polynomials list Primitive polynomials of degree n up to 100 Note: “24 4 3 1 0” means

40. Exhaustive Testing • Exhaustive Testing • Applying exhaustive patterns to an n-input combinational circuit under test (CUT) • Exhaustive pattern generator • Binary counter • Complete LFSR

41. Binary counter Example binary counter as EPG

42. Exhaustive Testing performance • Exhaustive Testing guarantees all detectable, combinational faults will be detected. • Test time maybe be prohibitively long if input number is larger than 20.

43. Pseudo-Random Testing • Pseudo-random pattern generator • Reduce test length but sacrifice the fault coverage • Difficult to determine the required test length and fault coverage

44. Pseudo-Random Testing • Maximum-length LFSR • RP-resistant problem • Weighted LFSR • Cellular Automata

45. Weighted LFSR Example weighted LFSR as PRPG

46. Cellular Automata • Provide more random test patterns • Provide high fault coverage in a random-pattern resistant (RP-resistant) circuit • Implementation advantage

47. ‘0’ Cell 0 Cell 1 Cell n-2 Cell n-1 ‘0’ Cellular Automata A general structure of an n-stage CA Each rule determines the next state of a cell based on the state of the cell and its neighbors

48. Cellular Automata

49. ‘0’ ‘0’ X0 X1 X2 X3 Example cellular automaton A 4-stage CA Test sequence 0 0 0 1 0 0 1 0 0 1 1 1 1 1 1 1 0 0 1 1 0 1 0 1 1 0 0 0 1 1 0 0 0 1 1 0 1 1 0 1 0 1 0 0 1 0 1 0 1 0 1 1 1 0 0 1 1 1 1 0

50. CA construction rules Construction rules for cellular automata of length n up to 53 [Hortensius 1989] *For n=7, Rule=152=001,101,010=1,101,010, where “0” denotes a rules 90 and “1” denotes a rule 150 cell, or vice versa