# What kind of tests are sufficient: Some personal thoughts **URL:** \ **Category:** General Usage\ **Tags:** testing\ **Created:** [January 9, 2024, 6:17am UTC](https://discourse.julialang.org/t/what-kind-of-tests-are-sufficient-some-personal-thoughts/108549 "2024-01-09T06:17:09Z")\ **Posts on this page:** 1\ **Showing post:** 16

**Author:** ![Zaikun](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/zaikun/32/44262_2.png) [@Zaikun](https://discourse.julialang.org/u/Zaikun)\ **Post date:** [January 23, 2024, 3:20pm UTC](https://discourse.julialang.org/t/what-kind-of-tests-are-sufficient-some-personal-thoughts/108549/16 "2024-01-23T15:20:58Z")

> I think you misunderstand my point: in general, optimization problems do not have algorithms that guarantee a (global) optimum. Some special cases exist (eg convex problems), but generally no matter how excellent and bug-free an implementation is, for every general algorithm you can devise a problem where the global optimum is not found. No, I didn’t. [I know your point very well](https://discourse.julialang.org/t/why-nelder-mead-minimization-without-minimal-property-check/102236/24). Indeed, even for the algorithms that guarantee a global solution in theory, and even if such an algorithm is applied to a convex problem, you most likely only obtain an approximate solution within finite time — even this is usually based on the assumption that your code is doing real-number calculation, whereas it really performs only floating-point arithmetic. However, this is irrelevant to the topic discussed here. > We all like to believe that our work matters, but perhaps this is taking it too far 😉 Thank you for pointing this trivial fact out, although it is again a topic unrelated to the discussion. Thanks. --- _[View the full topic](https://discourse.julialang.org/t/what-kind-of-tests-are-sufficient-some-personal-thoughts/108549)._