Content analysis of APL defined functions
APL '75 Proceedings of seventh international conference on APL
APL '79 Proceedings of the international conference on APL: part 1
An automatic adaptive integration routine in APL
ACM SIGAPL APL Quote Quad
Reducing computational complexity with array predicates
APL '98 Proceedings of the APL98 conference on Array processing language
A performance comparison between an APL interpreter and compiler
APL '83 Proceedings of the international conference on APL
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This paper describes a study of the performance of APL. The study was carried out by placing code in an existing APL interpreter (APLUM running on a CDC CYBER 175 computer) to monitor the distribution of data types, element counts, and ranks of arrays. The effect of reference counts on data blocks was also monitored. Although the results of the study may not be surprising, they are very interesting. For example, it turns out that nearly half of all allocations of data are made for scalars or one-element vectors, and that although the over-all average number of elements in APL arrays is 30, most users achieve average element counts of around 10. From these figures, it can be shown that set-up time dominates the execution of APL expressions.