Abstract
We describe a data-mining approach to creating central
parts of loop invariants. The approach is based on
producing a trace table by recording the values of
program variables each time the condition of a loop is
evaluated. From this trace table, functional
dependencies between program variables can be extracted
which may play a vital role in loop invariants. The
extraction process is accomplished through the use of
genetic programming which performs a symbolic
regression on the data contained by the trace table. We
illustrate our approach with examples.
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