I often have my PhD students re-implement ideas to gain skills and to verify a method works. It is possible to publish these efforts, but it isn't easy. It typically involves comparing multiple methods on datasets they haven't been tested on before to see how well the results generalize beyond the original paper. It is hard to publish in prestigious venues with this approach, but we have had some success. Replication and comarison makes for a good MS or early PhD project, but later PhD students have to showcase an ability to create new algorithms. In my lab, we try very hard to not cherry pick and to do good work that generalizes.