Use of decision tables in computer programming
Communications of the ACM
Conversion of decision tables to computer programs
Communications of the ACM
Conversion of limited-entry decision tables to computer programs
Communications of the ACM
A procedure for converting logic table conditions into an efficient sequence of test instructions
Communications of the ACM
Criteria for Selecting a Variable in the Construction of Efficient Decision Trees
IEEE Transactions on Computers
Optimal Partitioning for Classification and Regression Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Designing Storage Efficient Decision Trees
IEEE Transactions on Computers
Translation of Decision Tables
ACM Computing Surveys (CSUR)
ACM Computing Surveys (CSUR)
Optimal conversion of extended-entry decision tables with general cost criteria
Communications of the ACM
The synthetic approach to decision table conversion
Communications of the ACM
Combining decision rules in a decision table
Communications of the ACM
Ambiguity in limited entry decision tables
Communications of the ACM
Optimization of imprecise decision tables
ACM-SE 18 Proceedings of the 18th annual Southeast regional conference
Conversion of limited-entry decision tables into optimal decision trees: fundamental concepts
ACM SIGPLAN Notices - Special issue on decision tables
Some aspects of decision table conversion techniques
ACM SIGPLAN Notices - Special issue on decision tables
Compiling optimized code from decision tables
IBM Journal of Research and Development
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Given the number of words of computer storage required by the individual tests in a limited-entry decision table, it is sometimes desirable to find an equivalent computer program with minimum total storage requirement. In this paper an algorithm is developed to do this. The rules in the decision table are grouped into action sets, so that several rules with the same actions need not be distinguished. Moreover, if certain combinations of conditions can be excluded from consideration, the algorithm will take advantage of this extra information. The algorithm is initially developed for computer programs possessing a treelike form and then extended to a wider class of programs. The algorithm can be combined with one which finds an equivalent computer program with minimum average processing time, and thus used to find an equivalent computer program which minimizes a cost function which is nondecreasing in both average processing time and total storage requirement.