### Table 3. Formal definition of the Hoshen-Kopelman finite state machine.

1997

"... In PAGE 11: ... to Q. That is, (q; a) is a state for each state q and input symbol a. The transition function, , is defined as a set of 3-tuples (Sc, a, Sn) where Sc is the current machine state, a is an element of the token alphabet, and Sn is the new machine state. Table3 formally defines the Hoshen-Kopelman finite state machine (FSM) used in this work. The FSM begins in S0 and continues until a final state is reached.... ..."

Cited by 3

### Table 1: Specification finite state machine used for experiments

in finite

2006

"... In PAGE 10: ... 6 A case study A case study is designed to evaluate the effectiveness of the proposed method. A reduced, completely specified and strongly connected specification FSM M is defined in Table1 where the machine has five states. The input set is I = {a, b, c, d} and output set O = {x, y}.... ..."

### Table 3. An exercise using an external theorem prover

2003

Cited by 6

### Table 3. An exercise using an external theorem prover

2003

Cited by 6

### Table 2: Unique input/output circuit sequences for each state of the finite state machine shown in Table 1.

in finite

2006

"... In PAGE 10: ... The input set is I = {a, b, c, d} and output set O = {x, y}. In order to simplify the analysis, a set of UIOCs (shown in Table2 ) is used for state verification. For each state, the first UIOC sequence is used for the generation of the test sequence.... ..."

### Table 1: How Theorem Provers Store Theorems This paper proposes a method by which a theorem prover can use digital signatures to detect any modi cations made to a theorem while outside the system. Using this method it is no longer necessary to store theorems toget- her with their proofs in order to ensure the security of the theorem prover. Furthermore it is perfectly safe to store theorems in a documented format. These two features make the method an ideal basis for exchanging results between di erent proof tools.

1996

"... In PAGE 3: ... Furthermore, this technique can not be used to share results with other systems, since proofs can usually be checked only by the system in which they were developed. Table1 pre- sents a summary of the methods by which various theorem provers store and reuse results.... ..."

### Table 3: Summary of Propositional Logic Theorem Provers

1996

"... In PAGE 30: ....1.1.5 Summary of Propositional logic theorem proving The following Table3 is a summary of the theorem provers just described. The information is based on readings from [17, 19, 16, 5, 12]... ..."

### Table 4. Experiments with cooperating theorem provers

"... In PAGE 7: ...s in Section 3.2. All in all, we tackled 81 provable problems. Results can be found in Table4 . Results of SPASS, SETHEO using the weighted depth bound (SETHEO wd), and SETHEO using the depth bound (SETHEO d) are displayed in columns 2{4.... In PAGE 7: ...Table 4. Experiments with cooperating theorem provers Table4 reveals the high potential of cooperation. The number of solved problems could be increased, additionally the runtimes could be decreased.... ..."

### Table 2: Results for benchmarks using a CHR min solver extending a finite domain solver.

2003

"... In PAGE 11: ... We use four versions of the CHR code, the base ver- sion uses simple lists to store CHR constraints and rechecks each rule whenever a variables domain changes (as in Ex- ample 8), spec specializes the re-execution (as described in Example 12), tree uses tree indexes (implemented as in Ex- ample 25) and both does both. The results in Table2 show that specialization is very important when there are no in- dexes available. Even when there are no partners to try to join with re-execution, specialization improves around 30%.... ..."

Cited by 6

### Table 2: Results for benchmarks using a CHR min solver extending a finite domain solver.

2003

"... In PAGE 11: ... We use four versions of the CHR code, the base ver- sion uses simple lists to store CHR constraints and rechecks each rule whenever a variables domain changes (as in Ex- ample 8), spec specializes the re-execution (as described in Example 12), tree uses tree indexes (implemented as in Ex- ample 25) and both does both. The results in Table2 show that specialization is very important when there are no in- dexes available. Even when there are no partners to try to join with re-execution, specialization improves around 30%.... ..."

Cited by 6