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Research methods in computer science

机译:计算机科学中的研究方法

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摘要

Computer Science as a research discipline has always struggled with its identity. On the one hand, it is a field deeply rooted in mathematics which resulted in strong theories.1 For example, there is computational complexity theory (turing machines, the halting problem), database theory (the relational model, expresive power of query languages), formal language theory (the chomsky hierarchy, well-formedness, formal semantics). On the other hand, it is a field deeply rooted in engineering which resulted in machines that have completely warped our society: the von Neumann architecture (the basis for digital computers), parallel processors (the new generation of multi-core machines), distributed computers (a prerequisite for the success of the internet and recent phenomena like grid computing). Consequently, computer science has inherited its research methods from the same disciplines: on the one hand, the mathematical approach with axioms, postulates and proofs; on the other hand the engineering approach with quantification, measurements and comparison.
机译:作为研究学科的计算机科学一直都在为其身份而苦苦挣扎。一方面,它是一个扎根于数学的领域,产生了深厚的理论。 1 例如,存在计算复杂性理论(图灵机,暂停问题),数据库理论(关系模型) ,查询语言的强大功能),形式语言理论(乔姆斯基层次结构,格式正确,形式语义)。另一方面,这是一个深深扎根于工程学的领域,导致机器彻底扭曲了我们的社会:冯·诺依曼架构(数字计算机的基础),并行处理器(新一代多核机器),分布式计算机(互联网成功的先决条件以及诸如网格计算等最新现象的先决条件)。因此,计算机科学已从同一学科继承了其研究方法:一方面,采用公理,假设和证明的数学方法;另一方面,采用公理,假设和证明的数学方法。另一方面,采用量化,测量和比较的工程方法。

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