Attribute grammars have been used for many language-oriented tasks, including the formal description of semantics and the implementation of compilation tasks from simple type checking through code generation. Despite their successful use, attribute grammars have some disadvantages, including the monolithic nature of the grammar and the fixed factoring of all attribute descriptions by a single set of grammar productions. Attribute pattern sets provide a more expressive attribution system by using pattern matching, instead of grammar productions, to perform case analysis. Attribute pattern sets can be implemented in terms of attribute grammars in a way that maintains the dependency structure of the attribute system, making it straightforward to convert many of the practical results from attribute grammar theory to similar results for attribute pattern sets.

Abstract Predictability is a basic requirement for compilers of floating‐point code—it must be possible to determine the exact floating‐point operations that will be executed for a particular source‐level construction. Experience shows that many compilers fail to provide predictability, either because of an inadequate understanding of its importance or from an attempt to produce locally better code. Predictability can be attained through careful attention to code generation and a knowledge of the common pitfalls. Most language standards do not completely define the precision of floating‐point operations, and so a good compiler must also make a good choice in assigning precisions of subexpression computation. Choosing the widest precision that will be used in the expression usually gives the best trade‐off between efficiency and accuracy. Finally, certain optimizations are particularly useful for floating‐point and should be included in a compiler aimed at scientific computation. But predictability is more important than efficiency; obtaining incorrect answers fast helps no one.