下载文档原格式
计算机英语常用词汇（计算机科学版）2009-04-18 10:16:24分类：（一个进程的）激活activation（of a procedure）活动服务器界面Active Server Pages，ASP角色Actors实参actual parameterAda（一种基于pascal的程序设计语言）自适应词典编码adaptive dictionary encoding适配器模式adaptor pattern（存储单元的）地址address（of memory cell）地址多项式address polynomialAdleman，Leonard管理员administratorAdobe系统Adobe Systems代理agentAlexander，Christopher代数编码理论Algebraic coding theory算法algorithm算法的发现discovery of算法的有效性/正确性complexity / efficiency of算法的表示representation of算法的检验verification of算法分析algorithm analysis反网络域名抢注消费者保护法案the Anticybersquatting Consumer Protection Act 防病毒软件antivirus softwareAPL A Programming Language的缩写，是用于远程终端的一种程序语言苹果计算机公司Apple Computer，Inc.Applet（Java程序）应用层（因特网）application layer应用编程接口（API）Application Programmer Interface应用软件Application software谓词的变元argument（of a predicate）亚里斯多德（Aristotle）移位Arithmetic shift数组Array异构数组heterogeneous同构数组homogeneous人工智能Artificial intelligence人工神经网络Artificial neural networkASCII.参见美国信息交换标准码Asimo机器人ASP见活动服务器界面汇编程序Assembler汇编语言Assembly language断言Assertion赋值语句Assignment statement关联Association关联分析Association analysis美国计算机协会（ACM）Association for Computing Machinery联想记忆Associative memoryAtanasoff-Berry machine（Atanasoff 和Clifford Berry完成的一台16位加法器）Atanasoff，John（人名）美国电话电报公司（AT&T）阿思隆（处理器）Athlon（cpu）属性Attribute审计软件Auditing Software授权Authentication基于神经网络的自主式地面车辆Autonomous Land Vehicle in a Neural Net（ALVINN）平均情况分析Average-case analysis公理Axiom（神经的）轴突AxonBBabbage，Charles（人名）回溯法Backtracking平衡树法Balanced tree带宽Bandwidth基本要素语言Bare Bones language通用的Universality of栈底Base（of stack）递归的结束条件Base case（recursion）二进制Base Two. See Binary system基本输入/输出系统Basic Input/Output System基本路径测试Basis path testing批处理Batch processing贝多芬第五交响曲Beethoven’s Fifth Symphony基于行为的智能Behavior-based intelligence贝尔实验室Bell Laboratories基准测试BenchmarkBeta测试Beta testingBeta版Beta versionBurners-Lee，Tim（人名）Berry，Clifford（人名）最优情况分析Best-case analysis大写O标记Big O notation大Θ标记Big theta notation二进制文件Binary file（FTP）二进制记数法（参见二进制系统）Binary notation. See Binary system二分查找算法Binary search algorithm有效性complexity of二进制系统Binary system二叉树Binary tree生物信息学BioinformaticsBIOS（参见基本输入/输出系统）位Bit位图Bit map每秒比特数Bits per second（bps）黑盒测试Black-box testing（循环）体Body（of a loop）乔治.布尔Boole，George布尔数据类型Boolean data type布尔运算Boolean operations引导Booting引导程序BootstrapBourne shell（UNIX shell）栈底Bottom（of stack）自上而下的方法Bottom-up methodology边界值分析Boundary value analysisBps（参见每秒比特数）分枝Branch（tree）广度优先搜索Breadth-first search网桥Bridge宽带Broadband浏览器Browser冒泡排序算法Bubble sort algorithm存储桶（散列）Bucket（hashing）缓冲区Buffer总线Bus总线型网络拓扑结构Bus network topology奥古斯塔•艾达•拜伦Byron，Augusta Ada字节Byte字节码BytecodeCCC++C#高速缓冲存储器Cache memory调用（进程）Call（procedure）Camel样式Camel casing卡内基-梅隆大学Carnegie-Mellon University一种电子邮件监测系统，美国FBI将其应用扩展到调查恐怖活动和计算机犯罪中Carnivore 回车Carriage return带有冲突检测的载波侦听多路访问Carrier Sense，Multiple Access with Collision Detection（CSMA/CD）串联回滚Cascading rollbackCASE.（参见计算机辅助软件工程）Case控制结构Case control structureCASE工具CASE toolsCD（参见光盘）CD-DA（参见数字音频光盘）存储单元Cell（memory）赛扬（处理器）Celeron（cpu）中央处理器Central processing unit（CPU）欧洲粒子物理研究所CERNCERT（参见计算机应急响应小组）证书Certificate证书颁发机构Certificate authorityCGI（参见公共网关接口）性格伦理Character-based ethics字符型数据Character data type检验字节Check byte校验和Check sum孩子（树中）Children（in a tree）芯片Chip色度ChrominanceChurch，Alonzo丘奇-图灵论题Church-Turing thesis循环序列Circular queue循环移位Circular shiftCISC（参见复杂指令集计算机）类Class类型描述Class description类图Class diagram类型识别Class discrimination.NET框架类库Class library（.NET Framework）职责协作卡片（CRC卡）Class-responsibility-collaboration（CRC）cards 子句形式Clause form客户机Client客户机/服务器模式Client/Server model客户端Client-side时钟Clock封闭网络Closed network封闭世界假设Closed-world assumption云（因特网）Cloud（Internet）Clowes，M. B.（人名）聚类分析Cluster analysis群集（散列）Clustering（hashing）COBOL（面向商业的通用语言，Common Business—Oriented Language）代码生成器Code generator代码生成Code generation代码优化Code optimization强制数据类型转换Coercion内聚（模块）Cohesion（intramodule）协作图Collaboration diagram碰撞（散列）Collision（hashing）Colossus（在汤米．弗劳尔（Tommy Flowers）的指导下建造于英国“巨人”机器）列主序Column major order注释Comments提交点Commit point提交/回滚协议Commit/rollback protocolCommodore（苹果计算机公司1976年生产的计算机）公共网关接口Common gateway interface（CGI）通信辅助强制法案Communication Assistance for Law Enforcement Act（CALEA）光盘Compact disk（CD）数字音频光盘Compact disk-digital audio（CD-DA）编译器Compiler补码Complement复杂指令集计算机Complex instruction set computer（CISC）复杂性/有效性Complexity/Efficiency二分查找算法of binary search插入排序算法of insertion sort归并排序算法of merge sort顺序查找算法of sequential search组件（数组的）Component（of an array）组件（软件的）Component（of software）组件构架Component architecture组件装配员Component assemblerCompuServe（美国一公司，研制出GIF）可计算函数Computable function计算机辅助设计Computer-aided design（CAD）计算机辅助软件工程Computer-aided software engineering（CASE）计算机应急响应小组Computer Emergency Response Team（CERT）计算机欺诈和滥用法Computer Fraud Abuse Act计算机科学（定义）Computer Science（definition）计算机与社会Computer Society串联Concatenation并发处理Concurrent processing条件转移Conditional jump无连接协议Connectionless protocol结果伦理Consequence-based ethics常量Constant构造函数Constructor上下文切换Context switch上下文分析Contextual analysis邻接表（参见列表）Contiguous list. See List合同伦理Contract-based ethics控制耦合Control coupling控制器Controller重复迭代结构控制Control of repetitive structures iteration（looping）递归recursion控制语句Control statements控制部件Control unit小甜饼Cookies版权、著作权Copyright law磁芯Core磁芯大战Core wars国家地区码顶级域名Country-code TLD耦合（模块内部）Coupling（intermodule）CPU（参见中央处理器）CRC卡（参见职责协作卡片）临界区Critical region跨平台软件Cross-platform softwareC外壳C shellCSMA/CD（参见中带有冲突检测的载波侦听多路访问）网络域名抢注Cybersquatting循环冗余校验和校验Cyclic redundancy checks柱面CylinderD达特默斯学院Dartmouth collegeDarwin，Charles数据库Database数据库管理系统Database management system（DBMS）数据库模型Database model数据压缩Data compression数据耦合Data coupling多维数据集Data cubes数据字典Data dictionary数据流程图Dataflow diagram数据独立性Data independence数据挖掘Data mining数据结构Data structure静态和动态Dynamic vs. static数据类型Data type布尔型Boolean字符型Character浮点型Float整型Integer实型Real数据仓库Data warehouse死锁Deadlock避免死锁Deadlock avoidance死锁检测/改正Deadlock detection/correction调试Debugging陈述性知识Declarative knowledge声明型范型Declarative paradigm声明语句Declarative statements装饰者模式Decorator pattern解密密钥Decryption keys缺陷测试Defect testing美国国防部高级研究计划局Defense Advanced Research Projects Agency（DARPA）结束条件（递归）Degenerative case（recursion）树突Dendrite拒绝服务Denial of service深度（树）Depth（of a tree）深度优先搜索Depth-first search设计模式Design pattern设备驱动程序Device driverDewey，John字典编码Dictionary encoding差分机Difference engine差分编码Differential encoding数字（和模拟）Digital（vs. analog）数码照相机Digital camera数字签名Digital signature数字用户线路Digital subscriber line（DSL）数字化视频光盘Digital versatile disk（DVD）数字变焦Digital zoomDijkstra，E. W.哲学家进餐Dining philosophers直接寻址Direct addressing有向图Directed graph直接内存存取Direct memory access（DMA）目录Directory目录路径Directory pathDisclaimer离散余弦变换Discrete cosine transform磁盘Diskette磁盘存储器（磁带）Disk storage（magnetic）调遣程序Dispatcher分布式数据库Distributed database分布式系统Distributed systemDMA（参见直接内存存取）DNS（参见域名系统）DOCTOR（ELIZA）程序文档Documentation注释说明by comment statements域Domain域名Domain name域名系统Domain name system点分十进制记法Dotted decimal notationDRAM（参见动态存储器）Dual-core cpu职责伦理Duty-based ethicsDVD（参见数字化视频光盘）动态存储器Dynamic memoryEEckert, J. Presper轮廓增强Edge enhancement托马斯.爱迪生Edison, Thomas编辑EditorEffective有效输入（处理单元）Effective input (of a processing unit)8块拼图游戏Eight-puzzle电子通信隐私法案Electronic Communication Privacy Act (ECPA) 电子邮件Email封装Encapsulation加密密钥Encryption keys文件结束End-of-file (EOF)电子数字积分计算机ENIAC企业JavaBeans Enterprise JavaBeans实体-关系图Entity-relationship diagramELIZA程序EOF（参见文件结束）纠错编码Error-correcting code以太网Ethernet伦理Ethics欧几里得Euclid欧几里得算法Euclidean algorithm欧几里得几何Euclidean geometry偶校验Even parity事件驱动软件Event-driven software进化规划Evolutionary programming进化式原型法Evolutionary prototyping进化机器人学Evolutionary roboticsException余码记数法Excess notation排它锁Exclusive lock异或Exclusive or (XOR)专家系统Expert system显式耦合Explicit coupling指数域Exponent field指数时间Exponential time可扩展标记语言Extensible Markup Language (XML) 极限编程Extreme programmingF阶乘Factorial斐波纳契数列Fibonacci sequence字段（记录）Field (in a record)FIFO（参见先进先出）文件File文件描述符File descriptor文件管理系统File manager文件服务器File server文件传输协议File transfer protocol (FTP)防火墙Firewall火线FireWire第一代程序语言First-generation language先进先出First in, first out (FIFO)一阶谓词逻辑First-order predicate logic固定格式语言Fixed-format languageFlash闪存驱动器Flash drive闪存Flash memory平面文件Flat file触发器Flip-flop浮点记数法Floating-point notation规范化形式normalized form软盘Floppy disk流程图Flowchart汤米.弗劳尔Flowers, Tommy文件夹Folder创建子进程Forking形式语言Formal language形参Formal parameter格式化（磁盘）Formatting (a disk)For语句FORTRAN框架问题Frame problem结构（.NET）Framework (.Net)自由格式语言Free-format language频率相关编码Frequency-dependent encoding频率模糊Frequency maskingFTP（参见文件传输协议）FTP安全版本FTPSFTP服务器FTP serverFTP站点FTP site完整树Full tree函数Function抽象abstract计算computation of程序单元program unit功能内聚Functional cohesion函数型范型Functional paradigmGG5（处理器）G5 (cpu)Gandhi, Mahatma（人名）垃圾回收Garbage collection门Gate网关GatewayGB（参见吉字节）Gbps（参见Giga-bps）General Motors通用寄存器General-purpose register代（关于程序设计语言）Generations (of programming languages) 遗传算法Genetic algorithms约吉位GibiGIF（Graphic Interchange Format的缩写）千兆比特/秒Giga-bps吉字节Gigabyte千兆赫Gigahertz白盒测试Glass-box testing全局数据Global data全局变量Global variable基于目标的行为Goal directed behaviorGodel, Kurt歌德尔不完全性定理Godel’s incompleteness theoremGoto语句Goto statement语法Grammar图Graph图形用户接口Graphical user interface (GUI)图论Graph theory最大公因子Greatest common divisor GUI（参见图形用户接口）H停机问题Halting problem Hamming, R. W.汉明距离Hamming distance握手Handshaking硬盘Hard disk硬件Hardware哈佛大学Harvard University散列函数Hash function散列文件Hash file散列表Hash table散列Hashing头（列表）Head (of a list)磁头划道Head crash头指针Head pointer堆排序算法Heap sort algorithm Heathkit（经销计算机的公司）帮助包Help packages赫兹Hertz (Hz)异构树组Heterogeneous array启发式Heuristic十六进制记数法Hexadecimal notation 高位端High-order end登山系统Hill climbing赫尔曼.何勒里斯Hollerith, Herman主页Home page同构数组Homogeneous array本田公司（Honda）跳数值Hop count霍普菲尔德网络Hopfield networks Hopper, Grace主机Host主机地址Host address热区Hot spotHTML（参见超文本标记语言）HTTP（参见超文本传输协议）HTTP的安全版本HTTPS集线器Hub霍夫曼代码Huffman code Huffman, David A.超链接Hyperlink超媒体Hypermedia超文本Hypertext超文本传输协议Hypertext Transfer Protocol (HTTP)超文本标记语言Hypertext Markup LanguageIIBMICANN（参见Internet Corporation for Assigned Names and Numbers）电气和电子工程师学会美国计算机协会IEEE Computer SocietyIEEE 802标准IEEE 802 standard标识符IdentifiersIf语句if statement第I帧I-frame图像分析Image analysis图像处理Image processingIMAP（参见Internet邮件访问协议）Imitation （learning by）立即寻址Immediate addressing命令型范型Imperative paradigm命令语句Imperative statements显式耦合Implicit coupling不一致（声明）Inconsistent (statements)错误决算问题Incorrect summary problem增量模型Incremental model孵化期（解决问题）Incubation period (problem solving)索引文件Indexed file索引Indices间接寻址Indirect addressing推理法则Inference rule信息提取Information extraction信息检索Information retrieval继承Inheritance输入/输出Input/output (I/O)输入/输出指令（机器层）Input/output instructions (machine level)iRobot Roomba真空吸尘器IRobot Roomba vacuum cleaner插入排序算法Insertion sort algorithm复杂度complexity of实例（类）Instance (of a class)实例（数据类型）Instance (of a data type)变量实例Instance variable美国电气及电子工程师协会Institute of Electrical and Electronics Engineers (IEEE) 无线电工程师协会Institute of Radio Engineers指令指针Instruction pointer指令寄存器Instruction register整型数据Integer data type英特尔Intel交互式处理Interactive processing（联合国）国际法院International Court of Justice国际标准化组织International Organization for Standardization (ISO)互联网Internet因特网Internet (the)下一代互联网Internet 2因特网赋名和编号公司Internet Corporation for Assigned Names and Numbers (ICANN) Interent邮件访问协议Internet mail access protocol网际协议Internet protocol (IP)因特网服务提供商Internet service provider解释器Interpreter进程间通信Interprocess communication中断Interrupt中断屏蔽指令Interrupt disable instruction中断允许指令Interrupt enable instruction中断处理Interrupt handlerI/O. （参见Input/Output）输入/输出边界I/O bound爱荷华州大学Iowa State College (University)IP 参见Internet Protocol）See Internet ProtocolIP 地址IP address版本为4的IP IPv4版本为6的IP IPv6IQ 测试IQ testISO 参见International Organization for Standardization）ISP （参见Internet service provider）迭代结构Iterative structures人名Iverson, Kenneth E.J约瑟夫．雅卡尔Jacquard, Joseph人名Jacquard loomJava语言JavaJavaBeansJavaScript 语言JavaScriptJava 服务器页面JavaServer Pages作业控制语言JCL (job control language)作业Job作业队列Job queueJobs, Steve连接运算（数据库运算）JOIN (database operation)联合图像专家组Joint Photographic Experts Group联合图像专家组JPEGJSP （参见JavaServer Pages）KKB. 参见KilobyteKbps. 参见Kilo-bps内核KernelKey (cryptography)关键字段Key field关键字Key words约千位Kibi约兆字节Kibibyte清除（一个进程）Kill (a process)千比特Kilo-bps (Kbps)千字节Kilobyte背包问题Knapsack problemKorn 外壳Korn shellLLAN 参见Local area network语言扩展Language extensions后进先出Last in, first out (LIFO)等待时间Latency time叶结点Leaf node最低有效位Least significant bit左孩子指针Left child pointer人名Lempel, AbrahamLZW编码Lempel-Ziv-Welsh encoding人名Leonardo da Vinci词法分析Lexical analysis词法分析器Lexical analyzer基于2为底的对数Lg (logarithm base two) Liebniz, Gottfried WilhelmLIFO. 参见Last in, first out线性代数Linear algebra线性输入Line feed语言学Linguistics链路层Link layer (Internet)Linux 操作系统LinuxLISP程序设计语言LISP表List邻接contiguous链linked字面量Literal负载平衡Load balancing负载因子（哈希文件）Load factor (hash file) 局域网Local area network (LAN)本地变量Local variables锁定协议Locking protocol基于2为底的对数Logarithm (base 2)逻辑内聚Logical cohesion逻辑推理Logical deduction逻辑记录Logical record逻辑移位Logical shift逻辑程序设计Logic programming注册Login长除法Long division algorithm先行进位加法器Lookahead carry adder外观Look and feel循环Loop循环变量Loop invariant循环结构Loop structures. See Iteratice structure 指环王Lord of the Rings无损压缩Lossless compression无损解压Lossless decomposition有损压缩Lossy compression更新丢失问题Lost update problemLotus开发公司Lotus Development Corporation Lotus 1-2-3 软件Lotus 1-2-3Loveless, Ada低位端Low-order end亮度LuminanceM机器周期Machine cycle机器无关Machine independence机器指令Machine instructions加ADD与AND分支BRANCH停止HALT中断屏蔽Interrupt disable中断允许Interrupt enable输入/输出I/O转移JUMP加载LOAD或OR循环ROTATE移位SHIFT存储STORE测试并置位Test-and-set异或XOR (exclusive or)机器语言Machine language苹果公司开发的一种操作系统Mac OS公司名Macromedia磁盘Magnetic disk磁带Magnetic tape邮件服务器Mail server主存Main memory恶意软件MalwareMAN. 参见Metropolitan area network曼切斯特编码Manchester encoding尾数域Mantissa field多对多关系Many-to-many relationship马克一号Mark I标记语言Markup language掩码Mask屏蔽Masking大容量存储Mass storage主文件Master file矩阵理论Matrix theory人名Mauchly, JohnMB. 参见MegabyteMbps. 参见Mega-bps人名McCarthy, JohnMD5（信息-摘要算法，message-digest algorithm 5的缩写）约兆位（megabinary）的缩写Mebi约兆位Mebibyte一百万比特/秒Mega-bps (Mbps)兆字节Megabyte兆赫Megahertz成员函数Member function内存泄露Memory leak内存管理Memory manager存储器映射输入/输出Memory mapped I/O合并算法Merge algorithm合并排序算法Merge sort algorithm复杂度Complexity of元推理Meta-reasoning方法Method度量学Metric城域网Metropolitan area network (MAN)微秒Microsecond微软公司Microsoft CorporationMIDI. 参见Musical Instrument Digital InterfaceMiller, George A.毫秒Millisecond多指令流多数据流MIMD调制解调器Modem取模Mod模块化表示法Modular notation模块化Modularity模块ModuleMondrian, Piet监控程序Monitor莫尔电子工程学院Moore School of Engineering马赛克软件公司Mosaic Software最高有效位Most significant bit主板Motherboard运动图像专家组Motion Picture Experts Group (MPEG)摩托罗拉公司Motorola鼠标MouseMPEG layer3的缩写MP3MPEG. 参见Motion Picture Experts Group微软DOS操作系统MS-DOS多路技术Multiplexing多任务Multitasking乐器数字化接口Musical Instruments Digital Interface (MIDI)互斥Mutual exclusion一种关系数据库系统MySQLN名字服务器Name server与非NAND毫微秒Nanosecond(美国)国家航空和宇宙航行局火星探路者NASA Mars rover自然语言Natual language自然语言处理Natural language processing.NET框架NET (.NET Framework)网景通信公司Netscape Communications, Inc.网络Network网络拓扑结构Network topologies网络标识符Network identifier网络层Network layer (Internet)网络虚拟终端Network Virtual Terminal (NVT)神经元Neuron神经网络Neural network (biological)艾萨克牛顿Newton, Isaac空指针NIL pointer结点Node不确定性算法Nondeterministic algorithm非确定性多项式问题Nondeterministic polynomial (NP) problems 保密协议Nondisclosure agreement无损分解Nonloss decomposition非终结符Nonterminal或非NOR规范化形式Normalized form非NOT美国Novell公司Novell, Inc.NP problems. 参见Nondeterministic polynomial problems NP完全问题NP-complete problem空指针NULL pointer数值分析Numerical analysisO对象Object面向对象数据库Object-oriented database面向对象范型Object-oriented paradigm面向对象程序设计Object-oriented programming目标程序Object program奇校验Odd parity脱机Off-line一对多关系One-to-many relationship一对一关系One-to-one relationship联机On-lineOOP 参见Object-oriented programming操作码Op-code开放式网络Open network开放源码开发Open-source development打开（文件操作）Open (file operation)开放系统互联Open System Interconnect (OSI)操作数Operand操作系统Operating system运算符优先级Operator precedence光学变焦Optical zoom或OROrwell, George (Eric Blair)OSI 参见Open System Interconnect开放系统互联参考模型OSI reference model孤立点分析Outlier analysis溢出错误Overflow error重载OverloadingPP 参见Polynomial problemsP2P 参见Peer-to-peer model分组Packet页面（内存）Page (memory)页面调度Paging并行算法Parallel algorithm并行通信Parallel communication并行处理Parallel processing参数Parameter按引用传递passed by reference按值传递passed by value按值——结果传递passed by value-result父结点Parent node帕累托原理Pareto principlePareto, Vilfredo（人名）奇偶校验位Parity bit语法分析器Parser语法分析树Parse tree分解Parsing布莱斯.帕斯卡Pascal, Blaise（人名）Pascal样式Pascal casing密码Password专利法Patent lawPC 参见Personal computer点对点模式Peer-to peer model奔腾（CPU）Pentium (cpu)面向性能的的研究Performance oriented research 一致性（对象）Persisent (object)个人计算机Personal computer (PC)个人数字助理Personal digital assistant (PDA) PGP 参见Pretty good privacy电子黑饵Phishing个人主页超文本处理器PHP Hypertext Processor 物理记录Physical record流水线技术Pipelining像素Pixel有计划的淘汰Planned obsolescence柏拉图PlatoPoincare.H（人名）指针PointerPolya, G.（人名）多态Polymorphism多项式问题Polynomial problems弹出（栈操作）Pop（stack operation）POP3参见Post Office Protocol-version端口（输入/输出）Port (I/O)端口号Port number埃米尔•波斯特Post, Emil邮局协议3 Post Office Protocol-version 3 (POP3)PostScript（由Adobe系统公司研制开发的一种描绘字符以及一般图画数据的方法）测试循环Posttest loopPowerPC（国际商用机器公司（IBM）和摩托罗拉公司联合开发的系列处理器）优先级（运算符）Precedence (of operators)预设条件（正确性证明）Preconditions (proof of correctness)谓词Predicate前测试循环Pretest loopPretty good privacy（基于RSA公匙加密体系的邮件加密软件，PGP）质数Prime number原语Primitive基本数据类型Primitive data type打印服务器Print server隐私法案Privacy Act of私钥Private key特权指令Privileged instructions特权级Privilege levels问题求解Problem solving过程性知识Procedural knowledge过程型范型Procedural paradigm过程Procedure过程调用Procedure call过程头Procedure’s header进程Process处理单元Processing unit (neural net)进程状态Process state进程切换Process switch进程表Process table产生式系统Production system控制系统control system目标状态goal state产生式production开始状态start state状态图state graph程序Program程序员Programmer程序计数器Program counter编程语言Programming language程序设计范型Programming paradigms投影（数据库操作）PROJECT（database operation）Prolog（程序设计语言Prolog）反证法Proof by contradiction正确性证明Proof of correctness专用网络Proprietary network协议Protocol原型Prototype代理服务器Proxy server伪代码Pseudocode公钥Public key公钥加密Public-key encryption压栈（栈操作）Push (stack operation)Q队列Queue快速排序算法Quick sort algorithmRRadio Shack（一种计算机）小数点Radix pointRAM 参见Random access memory随机存储器Random access memory (RAM)快速原型法Rapid prototypingRavel, Maurice（人名）响应式机器人Reactive robot只读存储器Read-only memory (ROM)读操作Read operation就绪（进程）Ready (process)实数数据类型Real data type实时处理Real-time processing现实世界知识Real-world knowledge递归Recursion递归函数理论Recursive function theory递归结构Recursive structures精简指令集计算机Reduced instruvtion set computer (RISC) 引用Reference反射作用Reflex action再生电路Refresh circuit区域发现Region finding寄存器Register注册服务商Registrar强化学习Reinforcement (learing by)关系（数据库）Relation (database)关系数据库模型Relational database model相对编址Relative addressing相对编码Relative encoding可靠的协议Reliable protocolrepeat循环结构Repeat control structure中继器Repeater需求（软件）Requirements (of software)保留字Reserved words消解Resolution消解式Resolvent履责技术Responsible technology右孩子指针Right-child pointer环形拓扑Ring topology行波加法器Ripple adderRISC 参见Reduced instruction set computer风险论坛Risks forumRitchie, Dennis（人名）Rivest, Ron（人名）RMI 参见Remote method invocation一个机器人足球队的国际性比赛Robocup机器人学RoboticsRogerian论点Rogerian thesis回滚Roll backROM参见Read-only memory根结点Root node根指针Root pointer旋转Rotation旋转延迟Rotation delay舍入误差Round-off error路由器Router行主序Row major orderRSA算法RSA algorithm行程长度编码Run-length encodingS可缩放字体Scalable fonts比例缩放Scaling调度程序Scheduler模式Schema作用域（某一变量）Scope (of a variable) SDRAM. 参见Synchronous DRAM搜索引擎Search engine搜索树Search tree第二代语言Second-generation language扇区Sector安全壳Secure shell (SSH)安全套接字层Secure sockets layer (SSL)安全Security寻道时间Seek time选取（数据库操作）SELECT (database operation) 选择排序算法Selection sort algorithm选择服务Selective Service自引用Self-reference自终止的程序Self-terminating program语义分析Semantic analysis语义网Semantic net语义学Semantics语义网络Semantic Web信号量SemaphoreSempron(cpu)（AMD公司生产的CPU）哨兵Sentinel顺序文件Sequential file序列模式分析Sequential pattern analysis顺序查找算法Sequential search algorithm复杂度complexity of串行通信Serial communication服务器Server服务器端Server-side小服务程序Servlet集合理论Set theorySGML 参见Standard Generalized Markup Language Shamir, Adi（人名）共享锁Shared lock外壳Shell兄弟结点（树）Siblings (in a tree)符号位Sign bit单指令流多数据流SIMD面向模拟的研究Simulation oriented research单指令流单数据流SISDSloan, Alfred（人名）滤波Smoothing嗅探软件Sniffing software社会保障局Social Security Administration软件Software软件分析员Software analyst软件工程Software engineering软件生命周期Software life cycle软件需求文档Software requirements document 软件检验Software verification源版本Source (version of web page)源程序Source program空间复杂性Space complexity兜售信息（垃圾邮件）Spam垃圾邮件过滤器Spam filters专用寄存器Special-purpose register规格说明（软件）Specifications (of software)欺骗Spoofing假脱机Spooling电子制表软件系统Spreadsheet systems间谍软件SpywareSQL 参见Structured Query LanguageSSH 参见Secure shellSSL 参见Secure sockets layer栈Stack栈指针Stack pointer标准通用标记语言Standard Generalized Markup Language (SGML) 标准模板库Standard Template Library (STL)星型网络拓扑Star network topology挨饿Starvation状态State进程of process产生式系统of production system图灵机of Turing machine状态图State graph状态字Status word逐步求精Stepwise refinementStibitz, George（人名）存储程序概念Stored program concept流Stream强人工智能Strong AI强类型Strongly typed人名Stroustrup, Bjarne结构图Structure chart结构化程序设计Structured programming结构化查询语言Structured Query Language (SQL)结构化审查Structured walkthrough子程序Subprogram子例程Subroutine子模式Subschema实质相似Substantial similarity子树Subtree后继函数Successor functionSun Microsystems公司Sun Microsystems超级用户Super user监督学习Supervised training交换机Switch符号表Symbol table突触Synapse同步动态存储器Synchronous DRAM句法分析Syntactic analysis语法Syntax语法图Syntax diagram系统文档System documentation系统需求System requirements系统软件System software系统规格说明System specificationsSystem/360 (IBM)(IBM公司推出的System/360系列的计算机)T标记Tag (in markup language)表尾Tail (of a list)尾指针Tail pointer任务TaskTCP参见Transmission Control ProtocolTCP/IP协议组TCP/IP protocols技术文档Technical documentation远程登录Telnet暂时模糊Temporal masking终结符Terminal (in a syntax diagram)终端结点Terminal node结束条件Termination condition测试并置位指令Test-and-set instruction测试Testing (software)文本编辑Text editor文本文件Text file文本文件Text file (FTP)上世纪80年代中期，医学界使用的一台基于计算机技术的电子加速放射治疗仪Therac-25 第三代语言Third-generation languageThoreau, Henry David（人名）线程Thread阈值Threshold吞吐量Throughput抛弃式原型法Throwaway prototyping图象数据压缩系统Tagged Image File Format的缩写TIFF时间复杂性Time complexity分时机制Time-sharing时间片Time sliceTLD 参见Top-level domain令牌Token (in a network)令牌Token (in a translator)令牌环协议Token ring protocol自上而下方法Top-down methodology顶级域名Top-level domain (TLD)栈顶Top of stack拓扑结构（网络）Topology (of a network)Torvalds, Linus（人名）汉诺塔Towers of Hanoi磁道Track商业秘密法案Trade secret law训练集Training set事务文件Transaction file无理函数Transcendental functions传输速率Transfer rate翻译Translation翻译器Translator传输控制协议Transmission Control Protocol (TCP)运输层Transport layer (Internet)旅行商问题Traveling salesman problem树Tree三角函数Trigonometric functions特洛伊木马Trojan horseTrueType（一种描绘如何绘制文本符号的系统，由微软公司和苹果计算机公司研制开发）截断误差Truncation error元组（关系）Tuple (in a relation)阿兰•M•图灵Turing, Alan M.图灵可计算的Turing computable图灵机Turing machine图灵测试Turing test键开系统Turn key system二进制补码（two’s complement）记数法Two’s complement notationType 参见Data typeUUDP 参见User Datagram ProtocolUML 参见Unified Modeling Language无条件转移Unconditional jump由硬件及软件的多家主导厂商共同研制开发的代码Unicode单一化Unification统一建模语言Unified Modeling Language (UML)统一资源定位符Uniform resource locator (URL)通用程序设计语言Universal programming language通用串行总线Universal serial bus (USB)赫尔辛基大学University of Helsinki宾西法尼亚大学University of PennsylvaniaUNIX（Mac OS的核心，Mac OS是苹果公司发布的归类于微型机的一种操作系统）无人机Unmanned Aerial Vehicle (UAV)不可解问题Unsolvable problemURL 参见Uniform resource locator美国爱国者法案USA PATRIOT ActUSB 参见Universal serial bus美国国防部U.S. Department of Defense用例Use case用例图Use case diagram用户数据报协议User Datagram Protocol (UDP)用户自定义数据类型User-defined data type用户文档User documentation功利主义Utilitarianism实用软件Utility softwareV确认测试Validation testing变量Variable变长编码Variable-length codes矢量（图像表示）Vector (image representation)检验（软件）Verification (of software)虚拟内存Virtual memory病毒VirusVisual Basic（微软开发的一种面向对象的程序设计语言）网络电话Voice over InternetVoice over IP 参见Voice over Internet网络电话VOIP. Voice over Internetvon Helmholtz, H. （人名）冯．诺依曼体系结构von Neumann architecture冯．诺依曼阻塞von Neumann bottleneck冯．诺伊曼，约翰von Neumann, JohnWW3 参见World Wide WebW3C 参见World Wide Web ConsortiumWAN 参见Wide area network等待（进程）Wating (process)Waltz, D. （人名）瀑布模型Waterfall model弱人工智能Weak AI万维网Web网页Web page万维网服务器Web server网站Website权（处理单元）Weight (in a processing unit)加权和Weighted sumWeizenbaum, Joseph（人名）Welsh, Terry（人名）While控制结构While control structure广域网Wide area network (WAN)窗口管理程序Window manager窗口（图形用户接口中的）Window (in GUI)窗口（操作系统）Windows (operating system)字处理程序Word processor。
有关计算机课程的英语作文The Transformative Power of Computer Science Education.In the rapidly evolving digital landscape, the importance of computer science education has become increasingly apparent. It is no longer merely a domain for the technically inclined or those seeking careers in technology; rather, it has become a fundamental skill that equips individuals with the ability to navigate and contribute to the modern world. The reach of computer science extends across all industries, from healthcare to finance, entertainment to education, and beyond.1. Bridging the Gap between Technology and Everyday Life.Computer science is the language of our digital world.It is the medium through which we interact with smartphones, social media platforms, and the countless apps and devices that have become integral to our daily lives. Understandingcomputer science is crucial in harnessing the power of these tools effectively and responsibly.2. Enhancing Creativity and Problem-Solving Skills.Computer science education isn't just about coding;it's about problem-solving and creativity. Programming requires a unique blend of logic, analysis, and innovation. It encourages students to think outside the box, to approach problems from multiple angles, and to create solutions that are not only functional but also elegant and efficient.3. Preparing Students for the Future of Work.The job market is rapidly changing, and computer science skills are increasingly in demand. Fields as diverse as data analysis, cybersecurity, and artificial intelligence rely on a strong foundation in computer science. By equipping students with these skills, we are preparing them to not just secure jobs but to thrive in the evolving workforce.4. Driving Innovation and Entrepreneurship.Computer science education fosters a culture of innovation and entrepreneurship. It encourages students to identify problems, design solutions, and bring those solutions to market. This process not only sharpens their technical skills but also cultivates a mindset of risk-taking and creativity, essential for driving positive change in any industry.5. Enhancing Global Collaboration and Connectivity.In the age of the internet, computer science is a universal language. It breaks down barriers and allows individuals from diverse backgrounds to collaborate and share ideas seamlessly. By learning computer science, students gain access to a global community of peers and mentors, expanding their horizons and enhancing their understanding of diverse perspectives.6. Empowering Social Good.Computer science education isn't just about building apps or creating games; it can also be a powerful tool for social change. Students can use their skills to develop solutions that address pressing issues like poverty,climate change, and inequality. By harnessing the power of technology for good, they can create positive impacts that extend far beyond the confines of a traditional classroom.In conclusion, computer science education is not just about teaching coding or programming languages; it's about equipping students with the skills and mindset to navigate the rapidly changing world. It's about fostering creativity, problem-solving, and innovation. It's about preparing them for the future of work and about giving them the tools to make a positive impact on society. As we move into an increasingly digital future, the value of computer science education becomes increasingly apparent. It is a critical component of a comprehensive education that prepares students for success in the 21st century.。
对计算机发展的设想英文回答：The rapid advancement of computer technology has revolutionized various aspects of human life, transforming the way we communicate, learn, work, and entertain ourselves. As we look towards the future, it is exciting to speculate on the potential developments and innovationsthat could shape the next generation of computing.One significant area of exploration lies in the convergence of artificial intelligence (AI) and quantum computing. AI-powered systems are already demonstrating remarkable capabilities in areas such as natural language processing, image recognition, and decision-making. When combined with the immense computational power of quantum computers, AI systems could potentially solve complex problems that are currently intractable for classical computers. This could lead to breakthroughs in fields such as drug discovery, materials science, and financialmodeling.Another promising area is the development of neuromorphic computing, which aims to mimic the structure and functionality of the human brain. Neuromorphic chipsare designed to process and store information in a manner similar to biological neurons, enabling them to perform complex tasks such as pattern recognition, learning, and adaptation. By harnessing the power of neuromorphic computing, we could create computers that are moreefficient, intelligent, and capable of handling tasks that are currently beyond the reach of traditional computing systems.Furthermore, the concept of edge computing is gaining traction. Edge computing involves distributingcomputational resources and data storage closer to the devices and users that need them. This approach reduces latency and improves performance for real-time applications, such as autonomous vehicles, smart cities, and industrial automation. By bringing computing closer to the edge, wecan enable faster response times, reduce bandwidthrequirements, and improve overall system efficiency.Additionally, the rise of virtual and augmented reality (VR/AR) is transforming the way we interact with thedigital world. VR/AR headsets allow us to experience immersive virtual environments and overlay digital information onto the real world. As VR/AR technology continues to advance, we can expect to see even more innovative applications in fields such as gaming, education, healthcare, and remote collaboration.In terms of hardware, the development of new materials and fabrication techniques is pushing the boundaries of computing performance. Carbon nanotubes, graphene, andother advanced materials are enabling the creation of smaller, faster, and more energy-efficient devices. Additionally, the emergence of 3D printing and additive manufacturing is revolutionizing the way we design and produce computer components, allowing for greater customization and flexibility.Finally, it is important to consider the ethical andsocietal implications of rapid technological advancements. As computers become more powerful and autonomous, we needto address issues such as data privacy, job displacement, and the potential misuse of technology. By engaging in responsible innovation and fostering collaboration between technologists, policymakers, and ethicists, we can harness the transformative power of computing while mitigating potential risks.中文回答：随着计算机技术的飞速发展，各个方面的彻底改变人们的生活，改变了人们交流、学习、工作和娱乐方式。
《计算机专业英语》随着信息技术的飞速发展，计算机行业已成为当今社会的主流行业之一。
在这个行业中，英语作为全球通用语言，对于计算机专业的学生来说，掌握专业英语显得尤为重要。
本文将从以下几个方面阐述《计算机专业英语》的重要性。
一、行业需求在计算机行业，英语是一种必备的语言工具。
无论是软件开发、网络工程、信息安全，还是大数据、人工智能等领域，都需要大量的专业英语人才。
具备专业英语能力的计算机专业学生，将拥有更广阔的职业发展空间和更多的就业机会。
二、技术交流与合作在全球化的今天，计算机行业的技术交流与合作日益频繁。
很多先进的技术和解决方案都源自英语国家，因此，计算机专业英语成为了我们与世界各地同行进行交流的桥梁。
掌握专业英语，能够更好地学习和借鉴国际先进技术，有助于提升我国计算机行业的技术水平和国际竞争力。
三、学术研究与深造对于计算机专业的学生来说，学术研究与深造是必不可少的。
而在国际期刊和会议上发表论文，是学术研究的重要环节。
掌握专业英语，可以帮助学生更好地阅读英文文献、跟踪国际前沿技术，从而在国际学术界获得更多的话语权。
四、个人发展与提升对于个人来说，掌握专业英语也是一种重要的能力。
在日常生活中，我们可以通过阅读英文原著、观看英文电影和参加英语角等方式，提高自己的英语水平，丰富自己的文化素养。
拥有良好的英语沟通能力，可以帮助我们更好地融入国际化的社会环境。
《计算机专业英语》对于计算机专业的学生来说至关重要。
它不仅是求职就业的敲门砖，更是掌握未来科技的关键。
在信息时代，让我们共同努力，提高自己的专业英语能力，为推动我国计算机行业的发展贡献自己的力量。
《计算机专业英语》作业随着计算机技术的飞速发展，计算机专业英语的学习变得越来越重要。
在当今的信息化时代，掌握好专业英语不仅能帮助我们更好地与世界接轨，还能提升我们在职场上的竞争力。
因此，本篇文章将探讨如何完成《计算机专业英语》这门课程的作业。
一、明确作业要求在开始写作业之前，首先要明确作业的要求。
计算机专业论文范文Title: The Application of Artificial Intelligence in Computer Vision。
Abstract:With the rapid development of artificial intelligence (AI) technology, the application of AI in computer vision has become increasingly popular. This paper aims to explore the current state of AI technology in computer vision, and its potential impact on various industries. Through a comprehensive review of existing literature and case studies, this paper provides an in-depth analysis of the advantages and challenges of using AI in computer vision. The findings of this study suggest that AI has the potential to revolutionize the way we perceive and interact with visual information, and has the potential to significantly impact industries such as healthcare, automotive, and retail.1. Introduction。
The field of computer vision has made significant advancements in recent years, largely due to the integration of artificial intelligence (AI) technology. AI has the capacity to process and analyze visual information in ways that were previously thought to be impossible. This has led to a surge in the development and application of AI in computer vision, with the potential to revolutionize various industries. This paper aims to provide an overview of the current state of AI technology in computer vision, and its potential impact on different industries.2. The Current State of AI in Computer Vision。
从第二语言习得相关理论看计算机辅助外语学习的利弊摘要：本文以第二语言习得五大要素之间的关系，以及Krashen的输入假设和情感过滤假设理论为基础，对计算机辅助语言学习的优点以及存在的问题进行探讨，并提出了一些建议。
关键词：计算机辅助语言学习第二语言习得英语教学CALL (computer-assisted language learning 计算机辅助语言学习)泛指一切以计算机为媒介进行学习或教学的活动。
随着信息技术的发展，CALL在大学英语教学中正发挥着越来越重要的作用。
许多高校纷纷建立起多媒体语言实验室，越来越多的英语语言学习者开始使用CALL。
然而，CALL带给学习者的是利还是弊？下面，就以SLA (Second Language Acquisition第二语言习得)的相关理论为基础，对CALL进行分析。
一、第二语言习得的相关理论1．SLA五大要素间的关系SLA 中有五大要素，环境因素，语言输入，学习者间差异，学习过程和语言输出。
其中，环境因素主要指学习者所处的社会、文化背景以及所接触的语言环境。
语言输入指学习者通过各种渠道所获取的语言信息。
学习者差异则包括团体动力、年龄、语言学习能力、认知类型、动机和个性等[1]。
学习过程是学习者使用各种认知策略对其所获得的语言输入进行筛选，并将其融合到已有的知识体系中进行吸收和掌握的过程。
这些策略可归纳为学习策略(learning strategy)，表达策略(production strategy)和交际策略(communication strategy) [1]。
输出则是学习者利用目的语进行的说读写等行为。
这五大要素紧密联系，共同影响第二语言的习得。
图1[1]展示了这五大要素间的相互关系：如图1所示，环境因素影响语言输入和学习过程。
学习者差异影响语言输入的数量和质量，同时也影响学习策略的应用。
学习者通过使用各种策略获得输入的数据，然而输入本身也会影响学习者交际策略的使用。
25Computer AssistedLanguage Learning (CALL)PAUL GRUBA25.1IntroductionSimply stated, Computer Assisted Language Learning (CALL) can be defined as “the search for and study of applications of the computer in language teach-ing and learning” (Levy, 1997, p. 1). Although earlier practitioners relied on acronyms such as CAI (computer-aided instruction), CAL (computer-assisted learning), CELL (computer-enhanced language learning) and TELL(technology-enhanced language learning), CALL is now widely regarded as the centralacronym to refer to studies concerned with second language and computer tech-nology. Other terms, however, continue to be introduced to focus on particular uses of the computer. For example, individual learning through adaptive com-puter systems, promoted as intelligent CALL (ICALL), and web-enhanced language learning (WELL), is used by educators who promote Internet-based activities. A European Community group has formed under the banner ICT4LT (Information and Communication Technologies for Language Teachers). For their part, Warschauer and Kern (2000) prefer to use the term NBLT (net-worked-based language teaching) to encompass a broader range of the inter-connected computers; whereas Debski (2000) has coined the term PrOCALL (project-oriented CALL) to highlight large-scale collaborative activities. Chapelle (2001), on the other hand, employs the acronym CASLA (computer applica-tions in second language acquisition) to serve as an umbrella phrase that pulls together research in CALL, computer-assisted language assessment (CALT), and computer-assisted second language acquisition research (CASLR). Overall, the main objective of CALL is to “improve the learning capacity of those who are being taught a language through computerized means”(Cameron, 1999a, p. 2). Note that such a definition focuses particularly on language learning, not language teaching, while at the same time the use of the computer forces reconsideration of traditional stakeholder roles: learners, teachers, and researchers have each had to adapt to the demands and opportun-ities afforded by a range of new technologies. With the advent of networked624Paul Grubacomputers and the Internet, in particular, learners are increasingly called upon to design and execute their own computer-based activities.The growing availability of Internet access has prompted CALL instructors to move away from stand-alone workstations and more toward networked computers (e.g., Debski, 2000; Warschauer & Kern, 2000). Socio-collaborative approaches to teaching and learning are replacing communicative ones, and debates about pedagogy now center on aspects of learner autonomy, collab-orative project design, and appropriate assessment practices. CALL educators are also being challenged to keep pace with rapid change and innovation to meet concerns about evolving technologies, professional development, and rising student levels of electronic literacy. Issues of power, access, and equity are also gaining wider prominence and debate in the CALL community (Warschauer, 1998).Much of the current debate amongst CALL researchers concerns the establish-ment of a coherent agenda for research. The lack of a clear theoretical framework has long dogged the maturation of CALL (Levy, 1997) and investigators are now seeking to “take stock” of what has been accomplished (Cameron, 1999a, p. 9) in order to strengthen methodological approaches and define priorities for investigation (Chapelle, 1997; Motteram, 1999; Salaberry, 1999).To put current issues of CALL into perspective, this chapter begins with an attempt to locate the disciplinary influences on this emerging area of study.A history of CALL, roughly divided into Structural, Communicative, and Integrative stages, is then presented. In turn, the chapter then examines theroles of computers, students, instructors, and researchers in CALL, and con-cludes with a critical discussion of recent developments.25.2Overview of CALLAs with the broader field of applied linguistics, CALL can be located at the cross-roads of a number of disciplines. Levy (1997, pp. 47–75) regards the studies in psychology, artificial intelligence, computational linguistics, instructional tech-nology, and human–computer interaction as primary influences. Although Levy is aware that the area can be framed somewhat differently, he draws on these five cross-disciplinary fields to as a way to structure the knowledge base.Studies in psychology, for example, contribute insights about programmed instruction and cognition as they relate to CALL; research in computational linguistics informs work to do with machine translation, natural language processing, and concordance.In her extensive review, Chapelle (2001, pp. 27–43) places CALL within six computer-related sub-disciplines: educational technology, computer-supported collaborative learning (CSCL), artificial intelligence, computational linguistics, corpus linguistics, and computer-assisted assessment. Unlike Levy (1997), Chapelle argues that studies in human–computer interaction have had little impact on CALL and sees educational technology as a much more significantthe area distinctComputer Assisted Language Learning (CALL)625 formation of professional organizations and journals specifically devoted to the emerging field. According to Chapelle (2001, p. 15), the Australian journal On-CALL appeared in the mid-1980s. Across the Atlantic, ReCALLfirst appeared in 1988, and this was followed by Computer Assisted Language Learning: An International Journal two years later. In North America, CÆLL Journal specifically targeted computer use in English as a second language (ESL) con-texts from its release in 1989. Other journals that helped frame CALL research include The CALICO Journal and IALL Journal of Language Learning Technologies. Annual professional conferences, most prominently Euro-CALL, have also helped to solidify the emerging field.25.2.1 A brief historyAlthough Delcloque (2000) has embarked on an ongoing project to detail the history of CALL, sections of three books (Ahmad et al., 1985, pp. 27–44; Chapelle, 2001, pp. 1–26; Levy, 1997, pp. 13–46) provide extensive accounts of developments in the area. Ahmad et al. (1985) consider the work conducted in the United States and Britain in the years 1965–85. In one early project carried out at Stanford University, instructors created self-instructional materials for Slavic language learning and delivered them via a mainframe computer. Another group at the University of Illinois developed a system named Programmed Logic for Automated Teaching Operations (PLATO), in which teachers were able to write a Russian-English translation course. Thecomputer program was able to provide both drills and marking for student work as well as an authoring component for instructors. The PLATO system later expanded to include a number of foreign languages and offered them in increasingly technically sophisticated ways. Although high costs prohibited their widespread use, mainframe computer applications throughout the 1960s and 1970s were developed to the point of interactive features to help students read specialist scientific texts. With the arrival of the “microcomputer boom”in the late 1970s, however, expensive mainframe computer usage was phased out. Developers and instructors alike began to shift their attention to personal computers.From the early 1980s, increased computer availability fuelled a growing interest in CALL. Teachers were able to write or modify computer applica-tions to suit specific language learning situations; as a result, more and more students were exposed to them both at home and on campus. In his review, Levy (1997) highlights the Time-Shared, Interactive, Computer Controlled Information Television (TICCIT) project initiated at Brigham Young Univer-sity in 1971 as one of the first examples of multimedia-based instruction. Here, computers had the capacity to integrate text, audio, and video that could be controlled by the learner. The TICCIT system was based on an explicit theory of instructional design that allowed instructors to add content but, unfortu-nately, not to decide how to teach with the now programmed materials. Levy (1997) also singles out the Athena Language Learning Project based atIn this626Paul Grubaapproaches to language teaching underpinned the development of a multimedia authoring environment and an integration of techniques based on research in artificial intelligence. One significant part of this project was the full integra-tion of language teachers in the development process; that is, project managers promoted teaching and learning with computers above software design and instructional theory.As personal computers became easier to use, Storyboard and HyperCard became influential authoring programs during the early 1980s. Levy pays particular attention to teacher-programmers as they began to work out their own CALL practices. Materials were often designed as single activities and included simulation, text reconstruction, gap-filling, speed-reading, and vocabulary games (Levy, 1997, p. 23). By the end of the 1980s, CALL practi-tioners had produced a substantial body of work that focused mainly on pedagogical computer use. Critics at the time, however, began to question the effectiveness of such practices and suggested a much deeper examination of CALL activities and materials (Dunkel, 1991, pp. 24–5).From the start of the 1990s, teachers began to make greater use of networked computers, and by mid-decade the explosive growth of the Internet prompted CALL educators to increasingly adopt socio-collaborative modes of learning. In her recent overview, Chapelle (2001) notes that Internet usage prompted not only a much greater access to resources, but also provided the motivation for developers to create sophisticated materials that would hopefully attract large audiences. Classroom-based CALL activities could include learnercommunities throughout the world through email, virtual environments, and shared domains. Pedagogical discussions of CALL have thus shifted to exploration of such communities and their use of collaborative activities (e.g., Debski & Levy, 1999; Warschauer & Kern, 1999) but, once again, research in this era was critiqued for its absence of a focused agenda (Chapelle, 1997). In the mid-1990s, an Australian national report found that “With minor exceptions, the application of technology in language teaching and learning has been fragmented, frequently idiosyncratic, topic oriented and largely based on distributive technologies” (Australian National Board of Employment, Educa-tion and Training, 1996, p. 195). On a similar note, Chapelle (2001, p. 175) concluded with that the twentieth century was “a time of idiosyncratic learn-ing, quirky software development, and naive experimentation” for second language learning and computers.25.2.2Major theoretical perspectivesTrends in CALL roughly parallel those in other areas of applied linguistics. Starting with the structural and behaviorist models that manifested in audio-lingual approaches to language learning, CALL educators then explored aspects of communicative approaches to language learning. Socio-cognitive theories of instruction are now an integral part of CALL. Table 25.1 summar-izes key aspects of CALL over 30 years. This table provides a way to organizeTable 25.1Key aspects of theoretical perspectives in CALLRole of the computerTechnology focusTheory of learningModel and processof instructionView of second languageacquisitionDominant approaches tosecondlanguage teachingLearner statusPrincipal use of computersin CALLPrincipal learning objectiveof CALLPrimary research concernSource:Based on Warschauer (2000a), with Crook (1994), Koschmann (1996), Ullmer (1994)Integrative CALL(twenty-first century)Unified information management system; as a “toolbox”Group orchestration Sociocultural theories of learningCollaborative learning;“intra-action”Socio-cognitive (developed in social interaction)Content based; specific purposesCollaborativeAuthentic discourseAnd agencyInstruction as enacted practice, team “coficiency”Structural CALL (1970s–1980s) Information carrier; as a “tutor”Materials delivery BehavioristProgrammed instruction; assimilationStructural (a formal system)Grammar-translation & audiolingual DependantDrill and practice AccuracyInstructional efficacy, instructional competence Communicative CALL (1980s–1990s) Workstation; as a “pupil”Cognitive augmentation Information processing theory; cognitive constructivist learning Interactive, discovery-based learning; interaction Cognitive (a mentally constructed system)Communicative language teachingIndependent Communicative exercisesAnd fluency Instructional transfer,learner proficiency628Paul Grubathe rather fluid categories that characterize the development of CALL. Practi-tioners in the era of structural CALL placed a strong emphasis on grammar and they employed the use of mainframe computers to help students gain accuracy in their language usage. Grammar-translation and audio-lingual methods, grounded in behaviorism, went hand in hand with programmed instruction. Students were able to repeat drills with the seemingly tireless and patient computer-as-tutor, and instruction appeared to be at an upmost efficiency. Crook (1994, p. 12) sees the tutorial metaphor as a central preoccu-pation in the “computer-assisted instruction” (CAI) tradition of educational technologies. The goals of CAI developers were centered on making responses uniquely fitted to individual learner needs and delivering helpful, customized feedback through “intelligent tutorial systems.”Crook (1994, pp. 13–16) examines the tutorial role of computers and the popularity of drill exercises. First, he notes, computers never truly became “intelligent” because of the inherent difficulties in constructing algorithms that could sensitively respond to learner profiles. At the time, the sophistic-ated hardware needed to attempt this goal was available almost exclusively in military and industrial training contexts. Nonetheless, Crook writes, tutorial drills have a continued appeal to educators for two reasons: (1) teachers uncomfortable with innovative uses in technology “may well adopt the com-paratively easy solution of focusing their commitment on straightforward, self contained programs” (p. 14); and (2) many instructors feel that repeated exposures to certain practices and structures are beneficial to students.Crook’s observations can be applied to the CALL context. Indeed, Decoo and Colpaert (1999, p. 56) point out that there is “a mass of learners who are deeply embedded in fixed educational structures and who are asking for and welcoming effective forms of tutorial CALL matching those structures.” They urge researchers to re-evaluate the role of the computer in drills and practice for classroom activities which are time-consuming and repetitive. Richmond (1999) argues that a true picture of CALL resembles a split between “dedicated” and “integrated” streams. Much more widely practiced,“dedicated CALL” largely consists of using stand-alone programs to drill and practice items of grammar, vocabulary, and syntax. Richmond argues that the complexity and costs of software, as well as a host of technical problems, has shied teachers and students away from more integrated uses of the computer. The popularity of “dedicated CALL” has prompted researchers to continue to develop increasingly sophisticated tutorial applications that aid vocabulary acquisition, improve the writing in character-based languages, and build sustained interactions with target materials (e.g., Hamburger, Schoelles, & Reeder, 1999). Over the long term, Richmond predicts, the increased ease of software use and greater access to networks will bring the “dedicated”practices closer to “integrated” ones.Following an overall shift in teaching methods aligned with cognitive constructivist theories of learning, practices in communicative CALL soughtComputer Assisted Language Learning (CALL)629 to help students develop their own mental models through use of the target language. Exercises were designed to guide meaningful peer interactions and promote fluency. Esling (1991), created a series of task-based CALL activities to promote productive email exchanges between ESL students at two Canadian universities. In these activities, for example, students were directed to describe photographs, give directions, or express an opinion. The role of computer software was to help deliver visual materials for description, process word documents, or provide interactive simulations. In another project, Abraham and Liou (1991) studied the spoken language of learners at workstations to compare the talk elicited by different types of computer applications and to see if the talk was more useful and pro-ductive than would otherwise be the case in non-computer situations. In their conclusion, they report that the talk elicited by the different programs did not vary widely, nor was it significantly different than in non-computer situations.Integrative CALL seeks to make full use of networked computers as a means to engage learners in meaningful, large-scale collaborative activities (Debski, 2000; Warschauer & Kern, 2000). Instructors promote close ties between learning processes, objectives, and a student ownership of the out-comes. As with mainstream computer-supported collaborative learning (e.g., Bonk & King, 1998; Koschmann, 1996; Land & Hannafin, 2000), meaningful interaction and authentic project work are highlighted. Authentic discourse provides the basis for learning material. Students are taught techniques inonline publishing, and are urged to produce their own texts. Fostering learner agency, or “the satisfying power to take meaningful action and see the results of our own decisions and choices” (Murray, 1997, p. 126 cited in Warschauer, 2000b, p. 524), is a primary goal of integrative CALL. The key distinction between communicative CALL and integrative CALL is that, in the former, learner choice and self-management of activity are driven by task-based approaches to syllabus design. At its most liberal interpretation, a syllabus in integrative CALL simply represents a “dynamic blueprint” where learning occurs through “accidents” generated by projects (Barson, 1999). In contrast, a syllabus in communicative CALL is likely to be discrete and related to a set of curricular guidelines that have been defined in advance of learner needs (Corbel, 1999).In practice, however, the realization of integrative CALL may lie beyond the realm of language learning institutions constrained by a lack of resources, embedded teaching practices, and large class sizes. Such is the case in adult migrant education centers in Australia, for example (Taylor & Corbel, 1998) or in educational centers in South Africa (Oberprieler, 1999). At such sites, students are generally directed to access online materials alone, teachers are not free to alter a syllabus based on established curriculum guidelines. Students may not have the means to make use of the Internet outside limited class times.630Paul Gruba25.3Key Areas: The Roles of Computers,Students, Teachers, and ResearchersBroadly speaking, CALL is made possible through an interdependent relation-ship among computers, students, and instructors. The use of computers, for example, influences the nature of student activities which in turn affects how teacher may set goals and construct the learning environment. The aim of this section is to provide a detailed examination of the roles computers, learners, and teachers play in CALL settings.25.3.1Roles of the computersIn the structural stage of CALL, educators characterized the computer as a “tutor” who patiently delivered repetitive drills. In this way the computer could engage the independent student in individualized, self-paced instruc-tion through efficient materials delivery. Later, in communicative CALL, the computer was seen as a “pupil” that was trained to navigate through “microworlds” (Papert, 1980). Communicative CALL practitioners also used the computer to stimulate conversations amongst small groups of students who sat in front of it. In recent integrative CALL approaches, the computer acts like a “unified information manager” (Ullmer, 1994), that comes equipped with a host of applications, or a “toolbox,” that stand ready to be used in theconstruction of projects. More and more, a computer environment can create a “social space” in which to conduct purposeful interactions through virtual reality (Toyoda & Harrison, 2002).With the widespread use of computers in the 1980s, concern grew about their effectiveness (Kulik, Kulik, & Schwalb, 1986). Significantly, critics sought justification of claims that computers help to raise test scores and speed language acquisition (Dunkel, 1991) or otherwise promote cognitive aug-mentation through carefully designed materials (Clark & Sugrue, 1991). Such concerns were raised against a background of comparison studies which pitted computer-assisted instruction against other modes of learning and often concluded there was “no significant difference” between the types of presenta-tions (Russell, 1999).Although claims are still made that computers in education are “oversold and underused” (Cuban, 2001), many educators now see their use as an expected and necessary part of learning (Debski & Gruba, 1999; Pennington, 1999a). These days, the computer is likely to be seen in the “subservient role of tool in the service of the larger goals and contexts of instructional communities”(Meskill, 1999, p. 141). That is, most educators now downplay the centrality of computers and simply acknowledge their integrated use in classroom management, materials presentation, and learner interactions.In light of studies which view motivation as a key factor in language learn-ing success (for an extensive review, see Dörnyei, 2001), CALL practitionersComputer Assisted Language Learning (CALL)631 have been keen to point out that computer environments themselves can motivate many student (Soo, 1999). According to Pennington (1996), learners gain motivation through computer use because they are less threatened and thus take more risks and are more spontaneous. With reference to computer-based writing, Pennington (1999a, p. 289) credits positive attitudes toward computing as a key factor in student motivation to produce high quality materials. Increased access to authentic materials, email usage, and collaborat-ive activities have also been seen to spur student motivation to learn language (e.g., Biesenbach-Lucas & Weasenforth, 2001; Warschauer, 1995).Despite a general enthusiasm for computers, student resistance to their use can potentially reduce motivation through activities which promote isolation, dull creativity, and otherwise contribute to learner frustrations (Lewis & Atzert, 2000).One key role of computers is to deliver materials. Indeed, in structural CALL, efficient materials delivery was a prime focus of the technology. Sophisticated applications have been designed to adapt and fit individual learner needs. Materials in communicative CALL served as prompts for both discussion and practice. Increasingly, Internet access to foreign newspapers, specialized websites, and other forms of media has shifted a view of materials as authentic discourse. Specifically because they help make available such a wide range of authentic materials, Kramsch and Anderson (1999, p. 31) write that“computers seem to realize the dream of every language teacher – to bring the language and culture as close and as authentically as possible to students in the class-room.” However, they remind us, even though digitized materials give the appearance of authenticity, such media reshape the context of language use. That is, it is important for the consumers of multimedia to remember that such materials create their own unique symbol system through the juxtaposition, selection, and filtering of complex aural and visual elements (Potter, 2001; Salomon, 1979).Computers also permit the creation of electronic materials. Davies (1998) provides a succinct four-part overview of multimedia authoring packages for language teachers. In the first of his categories, he cites products which align with the “Keep it Simple and Stupid” school of design. The popularity of this approach rests with its relative ease of use. Secondly, an integrated approach using a full authoring suite can be utilized for materials production. A third approach is to use a multipurpose application and then later move and adapt materials into related computer environments. In his fourth “Generic CALL”category, Davies writes about the formation of a European Community project, known as MALTED (Multimedia Authoring for Language Tutors and Educa-tional Development), that aims to create an authoring environment which specifically meets the requirements of language teachers. Participating project members are set to develop the means of authoring multimedia courseware that can be shared and revised according to the requirements of local contexts. By using an open framework, the project hopes to encourage contributions based on a range of instructional design approaches. Similar work is underway632Paul Grubain the Information and Communications Technology for Language Teachers (ICT4LT) community.Levy (1999a) pulls together theory, research, and evaluation throughout the process of CALL materials design. He singles out audience awareness, unbridled creativity, and a clear understanding of development tools as the most fundamental characteristics of good designers. From there, designers need to determine the focal use of an element and ground its intended use in either holistic or discrete language learning activities. At the same time, they must determine where their materials will sit along the computer as a tutor or as a unified information system continuum.With reference to the broader CASLA agenda, Chapelle (2001) urges the production of software tools that are designed specifically for language acquisition use and research. Of course, such tools could also be productively applied to language teaching situations in order to provide an authentic educational experience to research participants. At present, Chapelle observes, there is no single tool that can perform functions such as task difficulty estimates and yet support a structure for learner models. Table 25.2 provides Chapelle’s list of desired functions and their purposes.As shown by its frequent mention in Table 25.2, the nature of technology-mediated tasks for language acquisition and assessment is a particular point of interest for CALL (Chapelle, 2001; Hoven, 1999a). The basic definition of pedagogical tasks is “a focused, well-defined activity, relatable to pedagogic decision making, which requires learners to use language, with an emphasison meaning, to attain an objective, and which elicits data which may be the basis for research” (Bygate, Skehan, & Swain, 2001, p. 12).Such a definition of tasks in computer environments, particularly in regard to integrative CALL, may well change. For example, as Driscoll (2000) points out, social constructivist approaches to instruction prefer that tasks not be “well-defined” so that learners themselves can work out how to meet the challenges of a particular “problem space.” In Debski (2000), for example, it is argued that collaborative learners themselves need to negotiate what to do and how to complete activities. That is, task definition in and of itself is an opportunity for learning in an ill-defined domain. The optimal role of “objectives,” too, may require consideration because they may change within the context of a group project. Authenticity must be re-examined as lines blur between the class-room and the world beyond (Chapelle, 1999). Further, future definition of technologically-mediated tasks may well need an explicit view of mode of presentation as a way to acknowledge the effects of medium on comprehension. Significantly for CALL educators, computers have the potential to help students with special needs, for example, in their use of screen readers, Braille devices, or other assistive technologies. The goal of “web access initiative”projects is to make all objects available in “gracefully depreciating” forms so that however they are to be used, they are still accessible (LeLoup & Ponterio, 1997). Awareness about the provision and design of accessible materials, however, is very low amongst CALL practitioners. Discussions focused on。
计算机专业名词英语Computer Science Terminology in EnglishComputers have become an integral part of our daily lives, revolutionizing the way we work, communicate, and access information. As the field of computer science continues to evolve, a vast array of specialized terminology has emerged to describe the various components, processes, and concepts that make up this dynamic industry. Understanding these technical terms is crucial for anyone aspiring to work in the computer science field or effectively communicate with professionals in the industry.One of the most fundamental terms in computer science is the "computer." A computer is an electronic device that can perform a wide range of tasks, from simple calculations to complex data processing and analysis. At the heart of a computer lies the central processing unit (CPU), which is responsible for executing instructions and coordinating the various components of the system.Another essential component of a computer is the memory, which can be divided into two main types: RAM (Random Access Memory) and ROM (Read-Only Memory). RAM is the primary memory used bythe computer to store and access data and instructions during operation, while ROM is used to store the basic instructions and firmware necessary for the computer to boot up and function.The term "operating system" refers to the software that manages the hardware resources of a computer and provides a user interface for interacting with the system. Some of the most widely used operating systems include Windows, macOS, and Linux, each with its own unique features and capabilities.In the world of computer programming, the term "code" is used to describe the set of instructions written in a programming language, such as Python, Java, or C++, that tell the computer what tasks to perform. Programmers use various software development tools, including integrated development environments (IDEs) and code editors, to write, test, and debug their code.Another important concept in computer science is "data structures," which are ways of organizing and storing data in a computer's memory. Common data structures include arrays, linked lists, stacks, queues, and trees, each with its own strengths and weaknesses depending on the specific requirements of the application.The term "algorithm" refers to a step-by-step procedure or set of rules that a computer can follow to solve a problem or perform aspecific task. Algorithms are the foundation of many computer programs and are essential for tasks such as sorting, searching, and optimization.In the realm of computer networks, the term "protocol" is used to describe the set of rules and standards that govern the communication between different devices on a network. Examples of common network protocols include TCP/IP (Transmission Control Protocol/Internet Protocol), which is the foundation of the internet, and HTTP (Hypertext Transfer Protocol), which is used for web-based communication.The term "database" refers to a structured collection of data that is organized and stored in a way that allows for efficient retrieval, manipulation, and management of information. Databases are widely used in a variety of applications, from e-commerce websites to enterprise resource planning (ERP) systems.In the field of artificial intelligence (AI), the term "machine learning" refers to the ability of a computer system to learn and improve from experience without being explicitly programmed. Machine learning algorithms are used in a wide range of applications, from image recognition to natural language processing.Another important concept in computer science is "cybersecurity,"which refers to the practice of protecting computer systems, networks, and data from unauthorized access, misuse, or disruption. Cybersecurity professionals use a variety of tools and techniques, such as firewalls, encryption, and intrusion detection systems, to safeguard digital assets.Finally, the term "cloud computing" refers to the delivery of computing services, including storage, processing power, and software, over the internet. Cloud computing has revolutionized the way businesses and individuals access and use technology, allowing for increased flexibility, scalability, and cost-effectiveness.These are just a few examples of the many specialized terms that are commonly used in the field of computer science. As the technology landscape continues to evolve, the language used to describe it will also continue to expand and evolve, making it essential for anyone interested in this dynamic field to stay up-to-date with the latest terminology and concepts.。
谈谈计算机专业英语作文标题，Computer Science English Composition。
With the rapid development of technology, computer science has become an increasingly important field of study. As a result, proficiency in computer science English is crucial for students in this discipline. In this essay, we will explore the significance of computer science English and provide insights into its key aspects.First and foremost, computer science English plays avital role in facilitating communication within the global tech community. As English is widely regarded as the lingua franca of the computing world, professionals andresearchers from diverse linguistic backgrounds rely on itto exchange ideas, collaborate on projects, and disseminate knowledge. Therefore, mastering computer science English enables students to actively participate in thisinternational discourse, broaden their professional networks, and stay abreast of the latest developments intheir field.Moreover, proficiency in computer science English enhances students' access to a wealth of resources and information. The majority of academic journals, conference proceedings, and technical documentation in the field are published in English. Consequently, students who are proficient in computer science English can effectively navigate these resources, conduct comprehensive literature reviews, and leverage existing research to inform their own work. Furthermore, they can engage with online communities, participate in forums, and access tutorials and documentation for various programming languages andsoftware tools, thereby enriching their learning experience and honing their skills.In addition to its practical benefits, computer science English also fosters cognitive development and critical thinking skills. Learning technical concepts and expressing them in English requires students to engage in analytical thinking, problem-solving, and abstract reasoning. Moreover, communicating with peers and instructors in Englishcultivates effective communication skills, including clarity, coherence, and conciseness. These cognitive and linguistic skills are not only invaluable in academic and professional settings but also transferable to other domains of life.Furthermore, proficiency in computer science English enhances students' career prospects in the global job market. In an increasingly interconnected world, employers value candidates who possess both technical expertise and strong communication skills. By demonstrating proficiency in computer science English, students can differentiate themselves from their peers and position themselves as competitive candidates for job opportunities, internships, and research positions at leading companies andinstitutions worldwide. Moreover, they can pursue international collaborations, work on multinational projects, and explore job opportunities abroad, thereby broadening their horizons and advancing their careers.To cultivate proficiency in computer science English, students should actively engage in language learningactivities both inside and outside the classroom. In addition to attending lectures and participating in discussions, they can supplement their learning by reading academic papers, watching tutorials, listening to podcasts, and practicing writing and speaking tasks. Moreover, they can seek feedback from instructors, peers, and language experts to identify areas for improvement and refine their language skills. By adopting a proactive and systematic approach to language learning, students can enhance their proficiency in computer science English and unlock new opportunities for academic and professional growth.In conclusion, computer science English is an essential skill for students in the field of computer science. It enables them to communicate effectively, access resources, develop cognitive skills, and enhance their career prospects. By investing time and effort in language learning, students can position themselves for success in the global tech community and make valuable contributions to the advancement of their field.。
谈谈计算机专业英语作文English:Studying computer science involves learning about algorithms, data structures, programming languages, software engineering, and the theoretical foundations of computing. It also involves understanding hardware systems, computer architecture, and the practical applications of computer technology. In addition, computer science professionals need to have strong problem-solving skills, analytical thinking, and the ability to work with abstract concepts. They also need to stay updated with the latest developments in the field, as technology is constantly evolving. Communication skills are also important, as computer science professionals often work in teams and need to be able to effectively communicate their ideas and collaborate with others. Overall, computer science is a dynamic and continuously evolving field that offers a wide range of career opportunities.中文翻译：学习计算机科学涉及学习算法、数据结构、编程语言、软件工程以及计算的理论基础。
