Current program generators usually operate in a greedy manner in the sense that a program must be generated in its entirety before it can be used. If generation time is scarce, or if the input to the generator is subject to modification, it may be better to be more cautious and to generate only those parts of the program that are indispensable for processing the particular data at hand. We call this lazy program generation . Another, closely related strategy is incremental program generation . When its input is modified, an incremental generator will try to make a corresponding modification in its output rather than generate a completely new program. It may be advantageous to use a combination of both strategies in program generators that have to operate in a highly dynamic and/or interactive environment.

It is common practice to specify textual patterns by means of a set of regular expressions and to transform this set into a finite automaton to be used for the scanning of input strings. In many applications, the cost of this preprocessing phase can be amortized over many uses of the constructed automaton. In this paper new techniques for lazy and incremental scanner generation are presented. The lazy technique postpones the construction of parts of the automaton until they are really needed during the scanning of input. The incremental technique allows modifications to the original set of regular expressions to be made and reuses major parts of the previous automaton. This is interesting in applications such as environments for the interactive development of language definitions in which modifications to the definition of lexical syntax and the uses of the generated scanners alternate frequently.

An LR-based parser generator for arbitrary context-free grammars that generates parsers by need and handles modifications to its input grammar by updating the parser it has generated so far is described. The need for these techniques is discussed in the context of interactive language definition environments. All required algorithms are presented. Measurements are given comparing their performance with that of conventional techniques.>

An LR-based parser generator for arbitrary context-free grammars is described, which generates parsers by need and processes grammar modifications by updating already existing parsers. We motivate the need for these techniques in the context of interactive language definition environments, present all required algorithms, and give measurements comparing their performance with that of conventional techniques.