let new_core := evolve(system_array); % returns only the core of the new system top_indx := array_liml(system_array); btm_indx := array_limh(system_array); new_top := for i in top_indx, top_indx+k-1 top_bound_row := system_array[i] returns array of top_bound_row end for; new_btm := for i in btm_indx-k+1, btm_indx btm_bound_row := system_array[i] returns array of btm_bound_row end for; left_indx := array_liml(system_array); % assume all rows have same range right_indx := array_limh(system_array); long_core := for row in new_core at i left_bound_elts := for j in left_indx, left_indx+k-1 left_elts := system_array[i,j] returns array of left_elts end for; right_bound_elts := for j in right_indx-k+1, right_indx right_elts := system_array[i,j] returns array of right_elts end for; returns array of left_bound_elts || row || right_bound_elts end for; long_tall := new_top || long_core || new_btm in long_tall % The newly evolved system, complete with boundaries. end letNote: If you came close to an answer equivalent to this one, you're to be congratulated. This is a nontrivial piece of Sisal coding, and indicates a good understanding of all that's gone before. If you didn't, don't be discouraged. This sort of coding requires a change of mind-set from that needed for programming in other languages. We believe that, once you make the shift to thinking functionally, the Sisal language will make you a faster and more productive programmer. If you require further proof of this, try writing the above code fragment in your favorite imperative language, and see if you think it's shorter, neater, or easier to read.