程序设计语言的选择：
- 项目的应用领域
(1)科学工程计算。需要大量的标准库函数，以便处理复杂的数值计算，可供选用的语言有FORTRAN语言、C语言等。
(2)数据处理与数据库应用。SQL为IBM公司开发的数据库查询语言，4GL称为第4代语言。
(3)实时处理。实时处理软件一般对性能的要求很高，可选用的语言有汇编语言、Ada语言等。
(4)系统软件。如果编写操作系统、编译系统等系统软件时，可选用汇编语言、C语言、Pascal语言和Ada语言。
(5)人工智能。如果要完成知识库系统、专家系统、决策支持系统、推理工程、语言识别、模式识别等人工智能领域内的系统，应选择Prolog、Lisp语言。 - 软件开发的方法
有时编程语言的选择依赖于开发的方法，如果要用快速原型模型来开发，要求能快速实现原型，因此宜采用4GL。如果是面向对象方法，宜采用面向对象的语言编程。 - 软件执行的环境
良好的编程环境不但能有效提高软件生产率，同时能减少错误，有效提高软件质量。 - 算法和数据结构的复杂性
科学计算、实时处理和人工智能领域中的问题算法较复杂，而数据处理、数据库应用、系统软件领域的问题，数据结构．比较复杂，因此选择语言时可考虑是否有完成复杂算法的能力，或者有构造复杂数据结构的能力。 - 软件开发人员的知识
编写语言的选择与软件开发人员的知识水平及心理因素有关，开发人员应仔细地分析软件项目的类型，敢于学习新知识，掌握新技术。
Choice of programming language:
- Application areas of the project
(1) Scientific engineering calculations. A large number of standard library functions are needed to handle complex numerical calculations. Languages available for selection include FORTRAN language, C language, etc.
(2) Data processing and database application. SQL is a database query language developed by IBM, and 4GL is called the 4th generation language.
(3) Real-time processing. Real-time processing software generally has high performance requirements, and the available languages include assembly language and Ada language.
(4) System software. When writing system software such as operating system and compilation system, you can choose assembly language, C language, Pascal language and Ada language.
(5) Artificial intelligence. If you want to complete systems in the field of artificial intelligence such as knowledge base systems, expert systems, decision support systems, reasoning engineering, language recognition, and pattern recognition, you should choose Prolog and Lisp languages. - Methods of software development
Sometimes the choice of programming language depends on the method of development. If you want to use a rapid prototyping model to develop, you need to be able to quickly implement the prototype, so 4GL should be used. If it is an object-oriented method, an object-oriented language programming should be used. - Software execution environment
A good programming environment can not only effectively improve software productivity, but also reduce errors and effectively improve software quality. - The complexity of algorithms and data structures
The problem algorithms in the fields of scientific computing, real-time processing, and artificial intelligence are more complex, while problems in the fields of data processing, database applications, and system software are data structures. It is more complicated, so you can consider whether you have the ability to complete complex algorithms or the ability to construct complex data structures when choosing a language. - Knowledge of software developers
The choice of writing language is related to the knowledge level and psychological factors of software developers. Developers should carefully analyze the types of software projects and dare to learn new knowledge and master new technologies.
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