### Table 1: Problem report severities.

2003

"... In PAGE 66: ... The analyzer makes the necessary corrections, and sets the severity to a value that is in line with the other problems reported. Table1 shows the seven possible severities in a descending order from the most severe to the least severe. Table 1: Problem report severities.... ..."

### Table 2: Several orbits problems

"... In PAGE 6: ... 4.3 RESULTS ON SEVERAL ORBITS PROBLEMS Table2 presents the results on the subset of several orbits problems (same presentation than for table 1). Concerning these problems : RDS fails on all problems except 1502, because of the high arity constraint (an anytime version would be able in fact to deliver solutions); BFBB performs a little better than RDS, but becomes limited by the size of the problems (extra computing time may improve results); DFBB because of its anytime capabilities, is able to produce solutions for all problems, but with a low quality compared to TS or even GR.... ..."

### Table 1: PERFECT Club static characterization Recall that constant propagation performs two primary functions for us, it nds constant uses and defs of variables, and it nds predicates which can be evaluated at compile-time. These two functions are only loosely interdependent so we chose to measure both of them. We could count programmer variables which have constant value, but this isn apos;t meaningful. For example, a particular variable might have several di erent constant values within a procedure or it might be constant only over part of a procedure. Speci cally, we count all uses and all defs which have a constant lattice value and we count all predicates which can be evaluated 5ccm, linpackd, qcd and track have procedure calls with an incorrect number of arguments. This breaks interprocedural analysis so they are discarded. 6bdna, o52 and track have the same problem. 7euler, mhd2d and shear have the same problem.

1994

Cited by 1

### Table 5.1. Comparison of the asymptotic running times of the Tabulation Algorithm, the Compressed-Tabulation Algorithm, and the Horwitz-Reps-BinkleyAlgorithm for three different classes of interprocedural dataflow- analysis problems.

1995

Cited by 260

### Table 5.1. Comparison of the asymptotic running times of the Tabulation Algorithm, the Compressed-Tabulation Algorithm, and the Horwitz-Reps-BinkleyAlgorithm for three different classes of interprocedural dataflow- analysis problems.

1995

Cited by 260

### Table 5.1. Comparison of the asymptotic running times of the Tabulation Algorithm, the Compressed-Tabulation Algorithm, and the Horwitz-Reps-BinkleyAlgorithm for three different classes of interprocedural dataflow- analysis problems.

1995

Cited by 260

### Table 2 Results for several long thin problems.

2002

"... In PAGE 36: ...n section 9. These problems have a maximum clause size of four. The cuts have very small cost, indicating the importance of the problem formulation and the ordering. The test results for the maxmin and dpmaxmin problems can also be found in Table 1 and Table2 . Here again QsatCNF far outperforms SATO and GRASP, and gives small solution times.... ..."

### Table 1 Characteristics for several long thin problems.

2002

"... In PAGE 36: ... Both series of problems use a structure- preserving translation so that the maximum number of variables per clause is three. The test results for these problems are given in Table1 and Table 2. It is interesting that cmpadd64 with a good renumbering can have an average cost of cut of only 11; some of our other renumberings reduced this value to 8.... In PAGE 36: ...n section 9. These problems have a maximum clause size of four. The cuts have very small cost, indicating the importance of the problem formulation and the ordering. The test results for the maxmin and dpmaxmin problems can also be found in Table1 and Table 2. Here again QsatCNF far outperforms SATO and GRASP, and gives small solution times.... ..."

### Table 2: Summary of results for several problems

"... In PAGE 4: ... We notice that when the fully parallel solution was achieved, the complexity of the algorithms becomes one of the dis- tinguishing elements on this comparison. Table2 shows a comparison of different practical exper- 1ILP was used to represent methods with complexity equivalent to an Integer Linear Programming solution, or eventually to an LP algorithm. 2U was used, in the rotation heuristic, to representan user input defin- ing the numberof iterations of the algorithm.... ..."

### Table IV: Interprocedural Analysis Statistics

1996

Cited by 69