Recent code-based cryptosystems rely, among other things, on the hardness of the decisional decoding problem. If the search version is well understood, both from practical and theoretical standpoints, the decision version has been less studied in the literature, and little is known about its relationships with the search version, especially for structured variants. On the other hand, in the world of Euclidean lattices, the situation is rather different, and many reductions exist, both for unstructured and structured versions of the underlying problems. For the latter versions, a powerful tool called the OHCP framework (for Oracle with Hidden Center Problem), which appears to be very general, has been introduced by Peikert et al. (STOC 2017) and has proved to be very useful as a black box inside reductions. In this work, we revisit this technique and extract the very essence of this framework, namely the Oracle Comparison Problem (OCP), to show how to recover the support of the error, solving an Oracle with Hidden Support Problem (OHSP), more suitable for code-based cryptography. This yields a new worst-case to average-case search-to-decision reduction for the Decoding Problem, as well as a new average-case to average-case reduction. We then turn to the structured versions and explain why this is not as straightforward as for Euclidean lattices. If we fail to give a search-to-decision reduction for structured codes, we believe that our work opens the way towards new reductions for structured codes, given that the OHCP framework proved to be so powerful in lattice-based cryptography. Furthermore, we also believe that this technique could be extended to codes endowed with other metrics, such as the rank metric, for which no reduction is known.