* used in the tableau, but instead it its represented by another
* variable x' = M + x, where M is an arbitrarily large (positive)
* value. x' is therefore always non-negative, whatever the value of x.
- * Taking as initial smaple value x' = 0 corresponds to x = -M,
+ * Taking as initial sample value x' = 0 corresponds to x = -M,
* which is always smaller than any possible value of x.
*
* The big parameter trick is used in the main tableau and
}
/* Return the first known violated constraint, i.e., a non-negative
- * contraint that currently has an either obviously negative value
+ * constraint that currently has an either obviously negative value
* or a previously determined to be negative value.
*
* If any constraint has a negative coefficient for the big parameter,
/* Resolve all known or obviously violated constraints through pivoting.
* In particular, as long as we can find any violated constraint, we
- * look for a pivoting column that would result in the lexicographicallly
+ * look for a pivoting column that would result in the lexicographically
* smallest increment in the sample point. If there is no such column
* then the tableau is infeasible.
*/
return i < tab->n_sample;
}
-/* Add a div specifed by "div" to the tableau "tab" and return
+/* Add a div specified by "div" to the tableau "tab" and return
* 1 if the div is obviously non-negative.
*/
static int context_tab_add_div(struct isl_tab *tab, struct isl_vec *div,
* coefficient are integral, then there is nothing that can be done
* and the tableau has no integral solution.
* If, on the other hand, one or more of the other columns have rational
- * coeffcients, but the parameter coefficients are all integral, then
+ * coefficients, but the parameter coefficients are all integral, then
* we can perform a regular (non-parametric) cut.
* Finally, if there is any parameter coefficient that is non-integral,
* then we need to involve the context tableau. There are two cases here.
*
* Instead of constructing a basic map, this function calls a user
* defined function with the current context as a basic set and
- * an affine matrix reprenting the relation between the input and output.
+ * an affine matrix representing the relation between the input and output.
* The number of rows in this matrix is equal to one plus the number
* of output variables. The number of columns is equal to one plus
* the total dimension of the context, i.e., the number of parameters,