We attempt to develop a general theory of robust processing for natural language, and especially Machine Translation purposes. That is, a general characterization of methods by which processes can be made resistant to malfunctioning of various kinds. We distinguish three sources of malfunction: (a) deviant inputs, (b) deviant outputs, and (c) deviant pairings of input and output, and describe the assumptions that guide our discussion (sections 1 and 2). We classify existing approaches to (a)and (b)-robustness, noting that not only do such approaches fail to provide a solution to (c)-type problems, but that the natural consequence of these solutions is to make (c)-type malfunctions harder to detect (section 3) In the final section (4) we outline possible solutions to (c)-type malfunctions.