In this paper, we discuss various connections between the smallest eigenvalue of the adjacency matrix of a graph and its structure. There are several techniques for obtaining upper bounds on the smallest eigenvalue, and some of them are based on Rayleigh quotients, Cauchy interlacing using induced subgraphs, and Haemers interlacing with vertex partitions and quotient matrices. In this paper, we are interested in obtaining lower bounds for the smallest eigenvalue. Motivated by results on line graphs and generalized line graphs, we show how graph decompositions can be used to obtain such lower bounds.A 3 = rA + s(J − I) + tI for some nonnegative integers r, s, t depending on n, k, a, c. ThusThus, z is at least as large as the minimum root of the cubic x 3 − rx + s − t. Two of the roots are θ and τ , inherited from (5), and the other is necessarily −(θ + τ ) = c − a since the coefficient of x 2 is 0. Thus, λ(G) = z ≥ min{c − a, τ }. Therefore, taking G (3) in Theorem 2.1 gives λ(G) = τ when G is a strongly regular graph such that τ ≤ c − a. In particular, λ(G) = τ when a ≤ c, a condition that must be satisfied by at least one of a strongly regular graph and its complement.