This paper describes some computer programing techniques for taking advantage of the sparsity of the admittance matrix. The techniques are based on two main ideas; (1) determination of a sequence of operations which results in anear minimum of memory and computing. (2) preservation of these operations for repetition. Use of these techniques makes it possible to obtain significant reductions in memory and processing time for many network analysis programs. Claims are substantiated by actual results.