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关键词： 数据结构   能力培养   实践教学   教学管理  

摘要： 数据结构是计算机科学与技术专业的核心基础课程。该课程知识和方法对编程能力的提高以及后续课程的学习起着至关重要的作用。教师以培养学生分析问题能力和实践能力为目标,练好过硬的实践本领。现结合该课程的教学内容,提出教学改进措施,对于提高本科生的创新能力与实践能力具有重要的现实意义。

关键词： 计算机图形学   数学结构   应用途径  

摘要： 信息技术飞速发展,计算机图形学科的理论体系不断丰富。数据结构在计算机图形学中的应用较为常见,具体探讨了数据结构的应用路径,以期为有识之士提供参考。

关键词： 数据结构   学生成绩管理   程序设计  

摘要： 数据结构是计算机科学与技术专业最为重要的专业基础课程。本文利用数据结构以及C语言,设计了一个学生成绩管理系统,该系统实现了对学生成绩的插入、删除、查找和排序等功能,既方便老师快速了解学生学习情况,又可以将该应用实例用于教学中,使学生对该课程内容有较深入的理解,提高学生解决实际问题的能力。

关键词： OnlineJudge   数据结构   程序设计   教学方法  

摘要： 本文课题组结合学校实际,将Online Judge系统应用于数据结构教学中,把数据结构的考核从笔试改为机试,每次课前通过Online Judge系统对学生进行10分钟测试检查学生课下的训练情况,课程改革以学生为中心,以提高学生程序设计能力为导向,通过近几年的教学实践表明,在数据结构课程教学中使用Online Judge系统,有效提高了学生的编程水平,取得了较好的教学效果。

关键词： Educational tool   Program visualisation   Algorithm visualisation   Data structure   Computer science education  

摘要： Algorithm Visualisation (AV) tool is commonly used to learn data structures. However, since that tool does not address technical details, some students may not know how to implement the data structures. This paper integrates the AV tool with Program Visualisation (PV) tool to help the students understanding the data structures' implementation. The integration (which is implemented as a tool named DS-PITON) works similarly as a PV tool except that the data structures are visualised with the AV tool. Through quasi experiments, it can be stated that DS-PITON helps students to get better assessment score and to complete their assessment faster (even though the impact on completion time can work in reverse on slow-paced students). Further, according to a questionnaire survey, the students believe that DS-PITON helps them learning data structure materials. (C) 2019 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University.

关键词： compact data structure   quadtree   k(2)-tree   k(2)-raster   DACs   3D-CALIC   M-CALIC   hyperspectral images  

摘要： This paper proposes a lossless coder for real-time processing and compression of hyperspectral images. After applying either a predictor or a differential encoder to reduce the bit rate of an image by exploiting the close similarity in pixels between neighboring bands, it uses a compact data structure called k(2)-raster to further reduce the bit rate. The advantage of using such a data structure is its compactness, with a size that is comparable to that produced by some classical compression algorithms and yet still providing direct access to its content for query without any need for full decompression. Experiments show that using k(2)-raster alone already achieves much lower rates (up to 55% reduction), and with preprocessing, the rates are further reduced up to 64%. Finally, we provide experimental results that show that the predictor is able to produce higher rates reduction than differential encoding.

关键词： Authenticated data structures   Scalability   Cloud   Integrity   Pipeline   Fork-linearisability  

摘要： Public cloud storage services are widely adopted for their scalability and low cost. However, delegating the management of the storage has serious implications from the security point of view. We focus on integrity verification of query results based on the use of Authenticated Data Structures (ADS). An ADS enables efficient updates of a cryptographic digest, when data changes, and efficient query verification against this digest. Since, the digest can be updated (and usually signed) exclusively with the intervention of a trusted party, the adoption of this approach is source of a serious performance degradation, in particular when the trusted party is far from the server that stores the ADS. In this paper, we show a protocol for a key-value storage service that provides ADS-enabled integrity-protected queries and updates without impairing scalability, even in the presence of large network latencies between trusted clients and an untrusted server. Our solution complies with the principle of the cloud paradigm in which services should be able to arbitrarily scale with respect to number of clients, requests rates, and data size keeping response time limited. We formally prove that our approach is able to detect server misbehaviour in a setting whose consistency rules are only slightly weaker than those guaranteed by previous results. We provide experimental evidence for the feasibility and scalability of our approach. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Sparse Data Structures   GPU Computing  

摘要： 3D visual computing data are often spatially sparse. To exploit such sparsity, people have developed hierarchical sparse data structures, such as multilevel sparse voxel grids, particles, and 3D hash tables. However, developing and using these high-performance sparse data structures is challenging, due to their intrinsic complexity and overhead. We propose Taichi, a new data-oriented programming language for efficiently authoring, accessing, and maintaining such data structures. The language offers a high-level, data structure-agnostic interface for writing computation code. The user independently specifies the data structure. We provide several elementary components with different sparsity properties that can be arbitrarily composed to create a wide range of multi-level sparse data structures. This decoupling of data structures from computation makes it easy to experiment with different data structures without changing computation code, and allows users to write computation as if they are working with a dense array. Our compiler then uses the semantics of the data structure and index analysis to automatically optimize for locality, remove redundant operations for coherent accesses, maintain sparsity and memory allocations, and generate efficient parallel and vectorized instructions for CPUs and GPUs. Our approach yields competitive performance on common computational kernels such as stencil applications, neighbor lookups, and particle scattering. We demonstrate our language by implementing simulation, rendering, and vision tasks including a material point method simulation, finite element analysis, a multigrid Poisson solver for pressure projection, volumetric path tracing, and 3D convolution on sparse grids. Our computation-data structure decoupling allows us to quickly experiment with different data arrangements, and to develop high-performance data structures tailored for specific computational tasks. With 1/10 th as many lines of code, we achieve 4.55x higher p

关键词： C语言-程序设计-数据结构  

ISBN: (数字)9787302532057 ISBN: (纸本)9787302532057

摘要： 本书系统地介绍了各种常用的数据结构与算法的基本理论和基本方法，共8章。其中第1章为绪论，引人数据、数据结构、抽象数据类型和算法等基本概念；第2-6章从抽象数据类型的角度讨论各种常用的数据结构及其应用，包括线性表、栈、队列、串、数组、广义表、树和二叉树以及图等；第7章和第8章分别讨论查找和排序的各种实现方法及其综合分析比较。

关键词： 数据结构   实践教学   教学质量  

摘要： 《数据结构与算法》是一门训练学生思维、培养学生程序设计技能的课程,对学生理论转化实践的能力要求很高,因此这门课程的实践教学尤为重要。但该课程实践教学普遍在课程安排、网络资源利用以及实训内容设置方面存在问题。本文针对现存问题提出应对策略,并用以实际教学,通过教学结果验证策略的可行性以及在提升教学质量方面的成效。