TY - GEN
T1 - Mechanizing reasoning about large finite tables in a rewrite based theorem prover
AU - Kapur, Deepak
AU - Subramaniam, M.
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1998.
PY - 1998
Y1 - 1998
N2 - Finite tables are commonly used in many hardware and soft- ware applications. In most theorem provers, tables are typically axiomatized using predicates over the table indices. For proving conjectures expressed using such tables, provers often have to resort to brute force case analysis, usually based on indices of a table. Resulting proofs can be unnecessarily complicated and lengthy. They are often inefficient to generate as well as difficult to understand. Large tables are often man- ually abstracted using predicates, which is error-prone; furthermore, the correctness of abstractions must be ensured. An approach for modeling finite tables as a special data structure is proposed for use in Rewrite Rule Laboratory (RRL), a theorem prover for mechanizing equational reasoning and induction based on rewrite techniques. Dontcare entries in tables can be handled explicitly. This approach allows tables to be handled directly without having to resort to any abstraction mechanism. For efficiently processing large tables, concepts of a sparse and weakly sparse tables are introduced based on how frequently particular values appear as table entries. Sparsity in the tables is exploited in correctness proofs by doing case analyses on the table entries rather on the indices. The generated cases are used to deduce constraints on the table indices. Additional domain information about table indices can then be used to further simplify constraints on indices and check them. The methodology is illustrated using a nontrivial correctness proof of the hardware SRT division circuit performed in RRL. 1536 cases originally needed in the correctness proof are reduced to 12 top level cases by using the proposed approach. Each individual top level case generated is much simpler, even though it may have additional subcases. The proposed approach is likely to provide similar gains for applications such as hardware circuits for square root and other arithmetic functions, in which much larger and multiple lookup tables, having structure similar to the sparse structure of the SRT table, are used.
AB - Finite tables are commonly used in many hardware and soft- ware applications. In most theorem provers, tables are typically axiomatized using predicates over the table indices. For proving conjectures expressed using such tables, provers often have to resort to brute force case analysis, usually based on indices of a table. Resulting proofs can be unnecessarily complicated and lengthy. They are often inefficient to generate as well as difficult to understand. Large tables are often man- ually abstracted using predicates, which is error-prone; furthermore, the correctness of abstractions must be ensured. An approach for modeling finite tables as a special data structure is proposed for use in Rewrite Rule Laboratory (RRL), a theorem prover for mechanizing equational reasoning and induction based on rewrite techniques. Dontcare entries in tables can be handled explicitly. This approach allows tables to be handled directly without having to resort to any abstraction mechanism. For efficiently processing large tables, concepts of a sparse and weakly sparse tables are introduced based on how frequently particular values appear as table entries. Sparsity in the tables is exploited in correctness proofs by doing case analyses on the table entries rather on the indices. The generated cases are used to deduce constraints on the table indices. Additional domain information about table indices can then be used to further simplify constraints on indices and check them. The methodology is illustrated using a nontrivial correctness proof of the hardware SRT division circuit performed in RRL. 1536 cases originally needed in the correctness proof are reduced to 12 top level cases by using the proposed approach. Each individual top level case generated is much simpler, even though it may have additional subcases. The proposed approach is likely to provide similar gains for applications such as hardware circuits for square root and other arithmetic functions, in which much larger and multiple lookup tables, having structure similar to the sparse structure of the SRT table, are used.
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U2 - 10.1007/3-540-49366-2_3
DO - 10.1007/3-540-49366-2_3
M3 - Conference contribution
AN - SCOPUS:84947943679
SN - 3540653880
SN - 9783540653882
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 22
EP - 42
BT - Advances in Computing Science ASIAN 1998 - 4th Asian Computing Science Conference, Proceedings
A2 - Hsiang, Jieh
A2 - Ohori, Atsushi
PB - Springer Verlag
T2 - 4th Asian Computing Science Conference, ASIAN 1998
Y2 - 8 December 1998 through 10 December 1998
ER -