The objective of the Byzantine margin of error is to protect against system component failures, with or without symptoms, preventing other components of the system from reaching an agreement if such an agreement is necessary for the system to function properly. Some astronaut flight systems such as SpaceX`s Dragon look at the Byzantine margin of error in their design. Several system architectures were designed around 1980, implementing the Byzantine margin of error. These include the „Draper s FTMP“, Honeywells MMFCS, and sri`s SIFT.  The problem of reaching a Byzantine consensus was conceived and formalized by Robert Shostak, who described it as the problem of interactive coherence. This work was done in 1978 as part of the NASA-sponsored SIFT project at the Computer Science Lab at SRI International. Sift (for Software Implemented Fault Tolerance) was the child of John Wensley`s brain and was based on the idea of using several versatile computers that would communicate in pairs of messages to reach consensus, even if some of these computers were defective. Several solutions were described by Lamport, Shostak and Pease in 1982.  They began by saying that the generals` problem can be reduced to the resolution of a „commander and lieutenant“ problem, in which loyal lieutenants must all act together and that their action must correspond to what the commander ordered, if the commander is loyal: the problem has been studied both in synchronous and asychronical communication. An example of BFT is Bitcoin, a peer-to-peer digital cash system.
 The Bitcoin network is working in parallel with the creation of a proof-of-work blockchain that allows the system to overcome Byzantine failures and obtain a coherent global view of the state of the system. Byzantine errors are considered the most common and difficult class of errors among error modes. The Fail-Stop-Fail mode takes the simplest end of the spectrum. While fail-stop error mode simply means that the only way to reach the defect is a node crash detected by other nodes, Byzantine errors do not involve constraints, meaning that the undone node can generate any data, including data that make it appear as a functional node. Thus, Byzantine errors can confuse error detection systems, making the margin of error more difficult. Despite the analogy, a Byzantine failure is not necessarily a security problem with hostile human interventions: it can be the result of electrical or software errors. Configuration: Faced with a n-Displaystyle n-Component system of which t`displaystyle is dishonest to you and a single point-to-point channel is accepted between all components. After PBFT, several BFT protocols have been introduced to improve its robustness and performance. That`s how.
B Q/U HQ, Zyzzyva, and ABstracts addressed performance and cost issues; whereas other protocols such as Aardvark and RBFT have addressed their robustness problems.