### Table 1 Experimental results for error-free data sets (40 probes) number graph tree ambiguous mean

"... In PAGE 13: ... Hence an actual distance of 10 is supplied to the program as the distance interval [9:09; 11:0]. Table1 presents the results. Each input combination was run twenty times and collective statistics were tabu- lated.... ..."

### Table 3. Size characteristics of the free interval tree.

"... In PAGE 9: ... Space overhead due to the free interval tree A natural concern for mark-split collection is the additional space required for the maintenance of the tree of free intervals. Table3 shows the number of nodes of this tree, both the maximum during (second column) and the maximum at the end of garbage collection (third column). In our current implementation, each tree node occupies ve words.... In PAGE 9: ...eed 46,468 KB for this benchmark (cf. Table 2). In short, in the worst case for these benchmarks, the free interval tree requires roughly 1=4 the memory needed for the mark bits of a mark-sweep collector, and only 1=303 of the additional space that a copying collector would minimally require. The last two columns of Table3 show the total and average number of comparisons performed during the extended mark phase of mark-split; i.e.... ..."

### Table 1. Collective additive tree spanners of n-vertex graphs having balanced separa- tors of bounded size

"... In PAGE 7: ... Every graph with tree-width at most k is (1/2,k+1, 0)-decomposable. Table1 summarizes the results on collective additive tree spanners of graphs having balanced separators of bounded size. The results are obtained by com-... ..."

### Table 1 Routing labeling schemes obtained for special graph classes via collective additive tree spanners.

"... In PAGE 17: ...where p(n) is the time needed to find a balanced and bounded radius separator S and t(n) is the time needed to find a central vertex for S. Projecting this theorem to the particular graph classes considered in this paper, we obtain the following results summarized in Table1 . For circular-arc graphs, the labels are of size O(log2 n) bits per vertex since this size labels are needed to decide in constant time which tree T or Tu is good for routing for given source x and destination y.... ..."

### Table 1 The complexity status of TREE t-SPANNER on chordal graphs under diameter constraints.

"... In PAGE 3: ... Theorem 3 improves previous results on tree 3-spanners in interval graphs [20,22,27] andon split graphs [6,20,29]. The complexity status of T REE t-SPANNER on chordal graphs consideredin this paper is summarizedin Table1 andFig. 1.... ..."

### Table 4: Interval Graph Statistics (after Spilling).

1992

Cited by 49

### Table 2. Spill on interval graphs with holes.

"... In PAGE 6: ... Consider for example a furthest-first-like strategy on sub-intervals (see Figure 1 for an illustration of sub-intervals). To design such a heuristic, a spill everywhere solution might be considered to drive decisions: between several candidates that end the furthest, which one is the most suitable to be evicted in the future? Unfortunately, as summarized by Table2 , most instances of spill everywhere with holes are NP-complete for a basic block. We start with a result similar to Theorem 4: even with holes, the spill everywhere problem with few registers is polynomial.... ..."

### Table 1: Results of the paper on interval and chordal graphs

2006

Cited by 5

### Table 1 Interval graphs Circular-arc graphs

1998

Cited by 7

### Table 6(a): Number of times the % degradation of NSL (with respect to the best solutions) is within the interval (10, 20] across all graph types.

1997

"... In PAGE 8: ... Table 5(a) and Table 5(b) show the number of cases when this degradation was between 5 to 10%. Table6 (a) and Table 6(b) show the number of cases when the degradation was between 10 to 20%. Finally Table 7(a) and Table 7(b) show the number of cases when the degradation was more than 20%.... In PAGE 10: ...Table 6(a): Number of times the % degradation of NSL (with respect to the best solutions) is within the interval (10, 20] across all graph types. Algorithm LWB LCTD DSH BTDH PY CPFD LU MVA InTree OutTree ForkJoin Random 10150910 15 12 5 10 7 12 144511212 02024 9 9 16137 14 000000 Graph Types ALL 45 61 58 22 68 0 Table6 (b): Number of times the % degradation of NSL (with respect to the best solutions) is within the interval (10, 20] across all CCRs. Algorithm LWB LCTD DSH BTDH PY CPFD 0.... ..."

Cited by 1