We have a partial converse. It's not quite as strong as allowing only finitely many or only isolated zeros of the second derivative, but it's strong enough.
For a function $f \colon I \to \mathbb{R}$, where $I \subset \mathbb{R}$ is an open interval, possibly $I = \mathbb{R}$, convexity can be formulated as
$$\bigl(\forall u,v,w \in I\bigr)\left(u < v < w \Rightarrow \frac{f(v)-f(u)}{v-u} \leqslant \frac{f(w)-f(v)}{w-v}\right)$$
and strict convexity with the strict inequality.
For a differentiable function $f$, these conditions can be seen to be equivalent to
- $f$ is convex if and only if the derivative $f'$ is non-decreasing,
- $f$ is strictly convex if and only if $f'$ is strictly increasing.
For a twice continuously differentiable function $f$, the above can be easily seen to be equivalent to
- $f$ is convex if and only if $f'' \geqslant 0$ everywhere,
- $f$ is strictly convex if and only if $f'' \geqslant 0$ everywhere and $f''$ does not vanish on any non-empty open interval $J \subset I$.