ion in Sather STEPHAN MURER, STEPHEN OMOHUNDRO, DAVID STOUTAMIRE, and CLEMENS SZYPERSKI International Computer Science Institute Sather extends the notion of an iterator in a powerful new way. We argue that iteration abstractions belong in class interfaces on an equal footing with routines. Sather iterators were derived from CLU iterators but are much more flexible and better suited for object-oriented programming. We retain the property that iterators are structured, i.e. strictly bound to a controlling structured statement. We motivate and describe the construct along with several simple examples. We compare it with iteration based on CLU iterators, cursors, riders, streams, series, generators, coroutines, blocks, closures, and lambda expressions. Finally, we describe experiences with iterators in the Sather compiler and libraries. Categories and Subject Descriptors: D.1.5 [Programming Techniques]: Object-oriented Programming; D.3.3 [Programming Languages]: Language Constructs and Fe...

In this paper the major components of every programming language are identified as: (1) the elementary program state-ment, (2) mechanisms for linking elementary statements together, (3) the means by which a program can obtain data inputs. Several alternative forms of each of these components are also described, compared and evaluated. Many examples, fre-quently from list processing languages, illustrate the forms described. The advantages, disadvantages and factors influencing the choice of a form of component for a language are dis-cussed, and the paper concludes with the suggestion that programming languages evolve toward one which will permit all the most convenient ways of structuring programs, organiz-ing systems and referencing data. 1.

languages to coexist within a single computer system.

A key decision when developing in-memory computing applications is choice of a mechanism to store and retrieve strings. The most efficient current data structures for this task are the hash table with move-to-front chains and the burst trie, both of which use linked lists as a substructure, and variants of binary search tree. These data structures are computationally efficient, but typical implementations use large numbers of nodes and pointers to manage strings, which is not efficient in use of cache. In this article, we explore two alternatives to the standard representation: the simple expedient of including the string in its node, and, for linked lists, the more drastic step of replacing each list of nodes by a contiguous array of characters. Our experiments show that, for large sets of strings, the improvement is dramatic. For hashing, in the best case the total space overhead is reduced to less than 1 bit per string. For the burst trie, over 300MB of strings can be stored in a total of under 200MB of memory with significantly improved search time. These results, on a variety of data sets, show that cache-friendly variants of fundamental data structures can yield remarkable gains in performance.