Standard Template Library

Generic programming is an effective methodology for developing reusable software libraries. Many programming languages provide generics and have features for describing interfaces, but none completely support the idioms used in generic programming. To address this need we developed the language G. The central feature of G is the concept, a mechanism for organizing constraints on generics that is inspired by

Secara tradisional, matakuliah Struktur Data difokuskan pada detail implementasi dari sejumlah struktur data sederhana. Sebagai alternatif, diusulkan penggunaan Standard Template Library (STL) yang merupakan bagian dari pustaka baku C++. Dengan penggunaan STL, fokus matakuliah dapat digeser kepada pemilihan dan penggunaan struktur data sederhana secara tepat, serta perluasan ke arah struktur data yang lebih kompleks dan lebih dekat ke masalah nyata. Sebagai ilustrasi, ditunjukkan bahwa implementasi general tree, yang tingkat kesulitannya membuatnya kerap dihindari dalam pengajaran Struktur Data tradisional, dapat dengan mudah dilakukan dengan bantuan STL.

by Lie-Quan Lee In this thesis I present the Generic Graph Component Library (GGCL), a generic programming framework for graph data structures and graph algorithms. Following the theme of the Standard Template Library (STL), the graph algorithms in GGCL do not depend on the particular data structures upon which they operate, meaning a single algorithm can operate on arbitrary concrete representations of graphs. I describe the principal abstractions comprising the GGCL, the algorithms and data structures that it provides, and provide examples that demonstrate the use of GGCL to implement some common graph algorithms. Performance results are presented which demonstrate that the use of novel lightweight implementation techniques and static polymorphism in GGCL results in code which is significantly more efficient than similar libraries written using the objectoriented paradigm. To my father, my mother in memoriam, and my wife Yun

Algorithms are needed in every aspect of parallel computing. Genetic Programming is an evolutionary technique for automating the design of algorithms through iterative steps of mutation and crossover operations on an initial population of randomly generated computer programs. This paper describes a novel parallel genetic programming (GP) system inspired by the symbiogenesis model of evolution, wherein new organisms are generated through the absorption of different life-forms in addition to the usual mutation and crossover operations. Different organisms are expressed in this GP system through multiple program representations. Two program representations considered in this paper are the procedural representation (PR) and the tree representation (TR). Populations of these representations evolve separately. Individuals in each population migrate to the other and participate in evolution via representation change algorithms. Parallelism is achieved through use of the AutoMap/AutoLink MP...

Generics (templates) attempt to unify similar program structures to avoid explosion of redundant code. How well do generics serve this purpose in practice? We try to answer this question through empirical analysis from two case studies. First, we analyzed the Java Buffer library in which 68% of the code was redundant due to cloning. We were able to remove only 40% of the redundant code using the proposed Java generics. Unification failed because the variations between cloned classes were either non-type parametric or non- parametric. To analyze whether this problem is specific to Java generics, we investigated the C++ Standard Template Library (STL), an exemplary application of C++ templates, as our second case study. Even though C++ templates are more powerful, we still found substantial cloning. We believe that we are dealing with a fundamental phenomenon that will cause many other class libraries and application programs to suffer from the code redundancy problem.

Standard iteration mechanisms, even ones of such generality as those in the C++ Standard Template Library (STL), do not allow insertions to be made in a container during a traversal of the container. Since ad hoc ways of handling such iterations are tedious to program and error-prone, programmers should ideally have at their command an efficient generic solution. In earlier

The Standard Template Adaptive Parallel Library (STAPL) is a su-perset of C++'s Standard Template Library (STL) which allows high-productivity parallel programming in both distributed and shared mem-ory environments. This framework provides parallel equivalents of STL containers and algorithms enabling ease of development for parallel sys-tems. In this paper, we will discuss our methodology for implementing a fast and efficient matrix multiplication algorithm in STAPL. Our imple-mentation employs external linear algebra libraries, specifically the Basic Linear Algebra Subprograms (BLAS) library which includes highly opti-mized sequential matrix operations. The paper will describe the benefits of creating a parallel matrix multiplication algorithm whose library calls are specialized based on both the matrix storage and traversal. This spe-cialization technique ensures that the most appropriate implementation in terms of data access and structure will be used, resulting in increas...