By Timothy Budd
Presents the result of an research into the problems raised through the improvement of a compiler for APL, a really excessive point computing device programming language. APL provides a few novel difficulties for a compiler author: susceptible variable typing, run time adjustments in variable form, and a number of primitive operations. throughout the integration of numerous lately built compiler development concepts, similar to info circulation research, and a unique and area effective call for pushed or lazy assessment method of code new release, the writer has been in a position to produce a real compiler for the language whereas nonetheless preserving the felxibility and straightforwardness which are the hallmarks of APL.
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Extra resources for An APL Compiler
In this chapter we describe the algorithms used in the generated code for some of the simpler space efficient functions. Algorithms used by more complicated space efficient functions are described in the following two chapters. 1. Assignment The assignment function is notable for being one of only four functions that can appear at the top of a parse tree; the other three functions are assignment to quad, the branching arrow, and function call. l The last chapter described in broad terms the code generated for assignment.
I +=(0 =((i6 + 1) % (i5 + 1))); This statement includes code produced by two iota functions, a residue dyadic scalar function, the constant 0, a dyadic scalar test for equality, and a reduction operator. With the exception of the reduction, all these functions produced expression trees instead of code. The reduction operator finally traversed the tree to pr<:>duce the code you see. Had lazy code generation not been used, many more lines of code would have been necessary. The examples shown in the appendices illustrate other instances of this optimization being employed to generate much more efficient C code.
Temp temp Other functions causing similar problems are outer product and the left argument to dyadic rotation. There is another situation in which it is debatable whether one should use the space efficient demand driven evaluation technique. When printing an array, most APLs uses the smallest amount of space necessary to display the results neatly. Thus, an array of 0 or 1 values might display as follows: 3. Code Generation Overview 43 100 1 1 0 110 1 o1 o0 1 0 101 1 If one of the values in the array is neither a 0 nor a 1 but instead an integer value, the spacing of the entire output is adjusted accordingly: 1 0 o 1 1 1437 o 0 1 0 o 1 1 o 1 1 o o 1 1 To do this requires that the system save the entire array of values to be output in a temporary location, and compute the maximum size of any element prior to printing the first value.