1350	 The Augmented Predictive Analyzer for Context-Free Languages-Its Relative Efficiency	 It has been proven by Greibach that for a given context-free grammar G a standard-form grammar Gs can be constructed which generates the same languages as is generated by G and whose rules are all of the form Z -- cY ... Y m m O where Z and Y i are intermediate symbols and c a terminal symbol. Since the predictive analyzer at Harvard uses a standard-form grammar it can accept the language of any context-free Grammar G given an equivalent standard-form grammar Gs. The structural descriptions SD Gs X assigned to a given sentence X by the predictive analyzer however are usually different from the structural descriptions SD G X assigned to the same sentence by the original context-free grammar G from which Gs is derived. In Section an algorithm originally due to Abbott is described standard-form grammar each of whose rules is in standard form supplemented by additional information describing its derivation from the original context-free grammar. A technique for performing the SD Gs X to SD G X transformation effectively is also described. In section the augmented predictive analyzer as a parsing algorithm for arbitrary context-free languages is compared with two other parsing algorithms a selective top-to-bottom algorithm similar to Irons error correcting parse algorithm and an immediate constituent analyzer which is an extension of Sakai-Cocke s algorithm for normal grammars. The comparison is based upon several criteria of efficiency covering core-storage requirements complexities of the programs and processing time.
