as Automatic Efficient Test Generator (AETG) (see, e.g., Cohen et al., 1996; Dalal et al., 1999). With AETG, one ignores the requirement of balance, and as a result one can identify designs that select fewer test cases that maintain coverage of the same pairwise (or k-wise) combinations of field values. In the test outlined above with seven fields, eight test cases are required. AETG, in contrast, generates the matrix of test inputs shown in Table 3 for the problem of 10 dichotomous fields. Here, even with an additional two fields, one is able to test all pairwise field values for all combinations of two fields with only six test inputs. In the case of 126 dichotomous fields, one needs only 10 test cases. There is a great deal of interesting mathematics associated with this new area of combinatorial design, with much more work remaining to be carried out.
For the problem mentioned at the outset of the presentation—13 fields, each with 3 possible values—AETG produces the array of test inputs shown in Table 4, with the given input values for the 13 fields. It was necessary to have 1.5 million inputs to cover all of the possible combinations of field values. With AETG, however, if one requires only test cases that cover all pairwise input values, one needs only the 15 test cases shown in Table 4. (It is, of course, important to consider the consequences of using a model of such modest size for problems in which the natural parameter space is of very high dimension. Therefore, sensitivity analysis is recommended to validate such an approach.)
It should be stressed that in real applications, the problems are typically more challenging since various complicating constraints operate when one is linking fields of inputs. Such complexity also can be accommodated with this methodology.
More broadly, AETG represents a game plan for efficiently generating test cases, running these cases to identify failures, analyzing the results, and making improvements to the software system, and then iterating this entire process to attain productivity and quality gains.
Jerry Huller at Raytheon has used this procedure and obtained a 67 percent cost savings and a 68 percent savings in development time. The effort required to carry out AETG is typically longer than is generally allocated to testing because the approach requires careful attention to the constraints, the various fields, and so on. Therefore, a cost-benefit argument must be made to support its use.