### Table 5: Random pattern testability

"... In PAGE 4: ...) 1000 randomly generated input vectors are applied to each circuit. In Table5 the resulting fault coverages are given in per cent. Here we only consider the classes C and T, since no obvious extension of CR for SOP and ESOPs exists and since CT and T have about the same testability properties.... ..."

### Table 2: Testability of nodes of digital full adder

"... In PAGE 3: ... Figure 5: Signal flow graph of the full-adder circuit including TTF values. In a similar way as indicated previously, the observabilities, controllabilities and testabilities of the different nodes have been calculated; the results of internal nodes are shown in Table2 . From this data, it is clear that the testability of node Y (italic) is the most problematic one, as result of its low observability.... ..."

### Table 1: Graph Properties

2000

Cited by 10

### Table 3: Graph properties

### Table 1 Modular Properties

"... In PAGE 3: ... So, the final list of quality parameters for CM tool architectural design comparison is: Flexibility, testability, portability, availability, simplicity, traceability for correctness and communication, and interoperability 10. Based on Table1 , entries for every architecture, for each of their components, an assessment of the five parameters degree of cohesion, coupling, fan-out, complexity and module size is done, and corresponding ratings, like, M1, M2, M3, MF1 and MF2 are determined with the help of Table 1. Number of components = n; For each component compute following: CMPX_n = MF1*MF2 ; SMP_n =1-CMPX_n; MOD_n = M1*M2*M3 ; COM_n = Sqrt(MOD_n*(10-CMPX_n) ; Here, M1,M2,M3, MF1 and MF2 referrers to a particular component.... In PAGE 3: ... So, the final list of quality parameters for CM tool architectural design comparison is: Flexibility, testability, portability, availability, simplicity, traceability for correctness and communication, and interoperability 10. Based on Table 1, entries for every architecture, for each of their components, an assessment of the five parameters degree of cohesion, coupling, fan-out, complexity and module size is done, and corresponding ratings, like, M1, M2, M3, MF1 and MF2 are determined with the help of Table1 . Number of components = n; For each component compute following: CMPX_n = MF1*MF2 ; SMP_n =1-CMPX_n; MOD_n = M1*M2*M3 ; COM_n = Sqrt(MOD_n*(10-CMPX_n) ; Here, M1,M2,M3, MF1 and MF2 referrers to a particular component.... ..."

### Table 2: Effect of considering testability during high level synthesis

1993

"... In PAGE 2: ... The longest loop in the S-graph has length 8. As can be expected, the data path is very hard to tes~ as indicated in Table2 by the row IIR.16 Orig.... ..."

Cited by 7

### Table 5n3a Random pattern testability

1997

"... In PAGE 4: ...n29 1000 randomly generated input vectors are applied to each circuit. In Table5 the resulting fault coverages are given in per cent. Here we only consider the classes C and Tn2c since no obvious extension of CR for SOP and ESOPs exists and since CT and T have about the same testability properties.... ..."

Cited by 1

### Table 1. Properties of the test graphs.

2005

"... In PAGE 5: ... Our test set consists of 19 graphs obtained from molecular dynamics and finite element applications [8, 13]. Table1 displays the structural properties of the test graphs, including maximum, mini- mum, and average degree. The table also displays the number of colors and the runtime in seconds used by a sequential FF algorithm when run on a single node of our test plat- form.... In PAGE 5: ... The table also displays the number of colors and the runtime in seconds used by a sequential FF algorithm when run on a single node of our test plat- form. All of the results presented in this section are average performance results over all of the graphs presented in Table1 . Each individual test is an average of 5 runs.... In PAGE 9: ... boundary vertices in parallel. Figure 4(a) shows the percentage of boundary vertices for the graphs in Table1 when using block partitioning with the natural vertex ordering (blue), and when using Metis (red). As one can see the number of boundary vertices increases with the number of processors being used.... In PAGE 9: ... 4. (a) Percentage of boundary vertices for graphs in Table1 (blue and red), and... ..."

Cited by 8

### Table 1. Properties of the test graphs

2005

"... In PAGE 6: ... Our test set consists of 19 graphs obtained from molecular dynamics and finite element applications [8, 13]. Table1 displays the structural properties of the test graphs, including maximum, mini- mum, and average degree. The table also displays the number of colors and the runtime in seconds used by a sequential FF algorithm when run on a single node of our test plat- form.... In PAGE 6: ... The table also displays the number of colors and the runtime in seconds used by a sequential FF algorithm when run on a single node of our test plat- form. All of the results presented in this section are average performance results over all of the graphs presented in Table1 . Each individual test is an average of 5 runs.... In PAGE 9: ... The core algorithm is a nontrivial way of coloring the boundary vertices in parallel. Figure 4(a) shows the percentage of boundary vertices for the graphs in Table1 when using block partitioning with the natural vertex order- ing, and when using Metis. As one can see the number of boundary vertices increases with the number of processors being used.... In PAGE 10: ...4. (a) Percentage of boundary vertices for graphs in Table1 (N = natural ordering, V = ordering given by Metis), and random graphs. (b) Speedup for random graphs of various average degrees 5Conclusion We have developed an efficient and truly scalable parallel graph coloring algorithm suitable for a distributed memory computer.... ..."

Cited by 8