A network's fault diagnosability is the maximum number of nodes(or processors) that are allowed to fail, while still being able to be identified by analyzing the sydrome of mutual testing, under the well-known PMC diagnostic model. It is a crucial indicator of the network's reliability. The original definition of diagnosability is often too strict to realistically reflect a network's robustness, because it is limited by the network's minimum degree. To better measure the actual reliability, many variants of diagnosability have been proposed, with g-extra diagnosability being one of the most noticeable diagnostic strategies. In this paper, we determine both the diagnosability and g-extra diagnosability for Bicube $B{Q}_n$, a recently proposed variant of the classic hypercube. We first show that the diagnosability for $B{Q}_n$, the n-dimensional Bicube, is n; and then prove that the g-extra diagnosability for $B{Q}_n$ is $(g+1)n-g-\left(\begin{array}{c}g\\ 2\end{array}\right)$.

网络的故障可诊断性是在众所周知的PMC诊断模型下，允许故障的节点（或处理器）的最大数量，同时仍然可以通过分析相互测试的症状来识别。它是网络可靠性的关键指标。可诊断性的原始定义通常过于严格，以致无法现实地反映网络的健壮性，因为它受到网络最低程度的限制。为了更好地衡量实际可靠性，已经提出了许多可诊断性的变体，其中g-额外的可诊断性是最引人注目的诊断策略之一。在本文中，我们确定了Bicube的可诊断性和g额外的可诊断性$乙{问}_{ñ}$，是最近提出的经典超立方体的变体。我们首先证明$乙{问}_{ñ}$中，Ñ维Bicube，是Ñ ; 然后证明g的额外可诊断性$乙{问}_{ñ}$ 是 $（G+\mathrm{1个}）ñ-G-（\begin{array}{c}G\\ 2\end{array}）$。