In this chapter, diversity is closely examined with respect to problem instances that are both tunably difficult and that exhibit varying rates of code growth. The results strongly support a causal hypothesis relating code growth and diversity. This hypothesis is also supported by previous literature and further experiments using a constructed model of code growth and problem difficulty. While furthering the understanding of diversity and problem difficulty, this chapter also provides important insights that suggest new ways of addressing the issue of bloat.

- 1 Code Growth and Problem Difficulty
- 2 Regression Problems and Increased Difficulty

- 3 Experimental Investigation
- 4 Binomial-3 and Random Polynomial Results

- 5 Discussion of a Causal Model

- 6 Summary