These search algorithms and their accompanying search space can be extended to apply to software engineering methodologies. By analogy, a sequential methodology can be compared to a breadth-first search algorithm, a cyclical methodology to a depth-first search algorithm, and the WaterSluice methodology to a best-first search algorithm.

A solution in search space is the path from the initial node to the goal node. Many nodes visited may not be included in the solution path. On the other hand, a solution in software engineering methodology space is the entire DAG necessary to go from the initial problem statement to the final acceptance test.

Since the space is much larger than the solution path it is imperative to prune the search as much as possible. Pruning is affected by dynamic and non-monotonic considerations when the entire search space cannot be pre-composed.