1. Computational ArtifactsComputer

1. Computational Artifacts
Computer science underpins our Facebook pages, controls air traffic around the world, and ensures that we will not be too surprised when it snows. It has been applied in algebra, car manufacturing, laser surgery, banking, gastronomy, astronomy and astrology. Indeed, it is hard to find an area of life that has not been fundamentally changed and enhanced by its application. But what is it that is applied? What are the things that give substance to such applications? The trite answer is the entities that computer scientists construct, the artifacts of computer science, computational artifacts, if you will. Much of the philosophy of the subject is concerned with their nature, specification, design and construction.

1.1 Duality
Folklore has it that computational artifacts fall into two camps: hardware and software. Presumably, software includes compilers and natural language understanding systems whereas laptops and tablets are hardware. But how is this distinction drawn: how do we delineate what we take to be software and what we take to be hardware?

A standard way identifies the distinction with the abstract/physical one (see the entry on abstract objects) where hardware is taken to be physical and software to be abstract. Unfortunately, this does not seem quite right. As Moor (1978) points out, programs, which are normally seen as software, and therefore under this characterization abstract, may also be physical devices. In particular, programs were once identified with sequences of physical lever pulls and pushes. There are different reactions to this observation. Some have suggested there is no distinction. In particular, Suber (1988) argues that hardware is a special case of software, and Moor (1978) that the distinction is ontologically insignificant. On the other hand, Duncan (2009—see Other Internet Resources) insists that there is an important difference but it is one that can only be made within an ontological framework that supports finer distinctions than the simple abstract/physical one (e.g., B. Smith 2012). Irmak (2012) also thinks that software and hardware are different: software is an abstract artifact, but apparently not a standard one since it has temporal properties.

Whether or not the software/hardware distinction can be made substantial, most writers agree that, while a program can be taken as an abstract thing, it may also be cashed out as a sequence of physical operations. Consequently, they (e.g., Colburn 2000; Moor 1978) insist that programs have a dual nature: they have both an abstract guise and a physical one. Indeed, once this is conceded, it would seem to apply to the majority of computational artifacts. On the one hand they seem to have an abstract guise which enables us to reflect and reason about them independently of any physical manifestation. This certainly applies to abstract data types (Cardelli and Wegner 1985). For example, the list abstract data type consists of the carrier type together with operations that support the formation and manipulation of lists. Even if not made explicit, these are determined by several axioms that fix their properties e.g., if one adds an element to the head of a list to form a new list, and then removes the head, the old list is returned. Similarly, an abstract stack is determined by axioms that govern push and pop operations. Using such properties one may reason about lists and stacks in a mathematical way, independently of any concrete implementation. And one needs to. One cannot design nor program without such reasoning; one cannot construct correct programs without reasoning about what the programs are intended to do. If this is right, computational artifacts have an abstract guise that is separable from their physical realization or implementation. Indeed, this requirement to entertain abstract devices to support reasoning about physical ones is not unique to computer science. The necessity to abstract is clearly made by the physicist Duhem.

When a physicist does an experiment, two very distinct representations of the instrument on which he is working fill his mind: one is the image of the concrete instrument that he manipulates in reality; the other is a schematic model of the same instrument, constructed with the aid of symbols supplied by theories; and it is on this ideal and symbolic instrument that he does his reasoning, and it is to it that he applies the laws and formulas of physics. A manometer, for example, is on the one hand, a series of glass tubes, solidly connected to one another filled with a very heavy metallic liquid called mercury and on the other by the perfect fluid in mechanics, and having at each point a certain density and temperature defined by a certain equation of compressibility and expansion. (Duhem 1954: 155–156)

Wittgenstein talks about a similar notion of abstraction when he argues that in kinematics one abstracts away from actual physical properties.

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