Software is a ubiquitous artifact, yet not much has been done to understand its ontological nature. There are a few accounts offered so far about the nature of software. I argue that none of those accounts give a plausible picture of the nature of software. I draw attention to the striking similarities between software and musical works. These similarities motivate to look more closely on the discussions regarding the nature of the musical works. With the lessons drawn from the ontology (...) of musical works I offer a novel account of the nature of software. In this account, software is an abstract artifact. I elaborate the conditions under which software comes into existence; how it persists; how and on which entities its existence depends. (shrink)

I defend the historical definition of "function" originally given in my Language, Thought and Other Biological Categories (1984a). The definition was not offered in the spirit of conceptual analysis but is more akin to a theoretical definition of "function". A major theme is that nonhistorical analyses of "function" fail to deal adequately with items that are not capable of performing their functions.

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

The specification and implementation of computational artefacts occurs throughout the discipline of computer science. Consequently, unpacking its nature should constitute one of the core areas of the philosophy of computer science. This paper presents a conceptual analysis of the central role of specification in the discipline.

In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical states have a (...) unique history, representations of those states in a computational model will usually be compatible with more than one possible history in the model. We describe some of the challenges involved in prediction and retrodiction in computational models while arguing that prediction is an essential feature of non-arbitrary decision making. Furthermore, we contend that the non-predictive virtues of computational models are dependent to a significant degree on the predictive success of the models in question. (shrink)

Computational modeling plays an increasingly important explanatory role in cases where we investigate systems or problems that exceed our native epistemic capacities. One clear case where technological enhancement is indispensable involves the study of complex systems.1 However, even in contexts where the number of parameters and interactions that define a problem is small, simple systems sometimes exhibit non-linear features which computational models can illustrate and track. In recent decades, computational models have been proposed as a way to assist us in (...) understanding emergent phenomena. (shrink)

The question about the scientific nature of computing has been widely debated with no universal consensus reached about its disciplinary status. Positions vary from acknowledging computing as the science of computers to defining it as a synthetic engineering discipline. In this paper, we aim at discussing the nature of computing from a methodological perspective. We consider, in particular, the nature and role of experiments in this field, whether they can be considered close to the traditional experimental scientific method or, instead, (...) they possess peculiar and unique features. We argue that this experimental perspective should be taken into account when discussing the status of computing. We critically survey how the experimental method has been conceived and applied in computing, and some open issues that could be tackled with the aid of the history of science, the philosophy of science, and the philosophy of technology. (shrink)

Over the past four decades, software engineering has emerged as a discipline in its own right, though it has roots both in computer science and in classical engineering. Its philosophical foundations and premises are not yet well understood. In recent times, members of the software engineering community have started to search for such foundations. In particular, the philosophies of Kuhn and Popper have been used by philosophically-minded software engineers in search of a deeper understanding of their discipline. It seems, however, (...) that professional philosophers of science are not yet aware of this new discourse within the field of software engineering. Therefore, this article aims to reflect critically upon recent software engineers’ attempts towards a philosophy of software engineering and to introduce our own philosophical thoughts in this context. Finally, we invite the professional philosophers of science to participate in this interesting new discourse. (shrink)

The topic of this paper is the notion of technical (as opposed to biological) malfunction. It is shown how to form the property being a malfunctioning F from the property F and the property modifier malfunctioning (a mapping taking a property to a property). We present two interpretations of malfunctioning. Both interpretations agree that a malfunctioning F lacks the dispositional property of functioning as an F. However, its subsective interpretation entails that malfunctioning Fs are Fs, whereas its privative interpretation entails (...) that malfunctioning Fs are not Fs. We chart various of their respective logical consequences and discuss some of the philosophical implications of both interpretations. (shrink)

Because much of the recent philosophical interest in functions has been motivated by their application in biology and other sciences, most of the ensuing discussions have focused on functional explanations to the neglect of the practical role of functional knowledge. This practical role is essential for understanding how users form plans involving artifacts. We introduce the concept of instrumental function which is intended to capture the features of functional claims that are relevant to practical—in particular, instrumental—reasoning. We discuss the four (...) primary features of an instrumental function ascription, the teleological component of such ascriptions and give a clear definition of malfunction in terms of incapability to perform as well as “normal” tokens of the same type. (shrink)

On the basis of an earlier contribution to the philosophy of computer science by Amnon Eden, this essay discusses to what extent Eden’s ‘paradigms’ of computer science can be transferred or applied to software engineering. This discussion implies an analysis of how software engineering and computer science are related to each other. The essay concludes that software engineering can neither be fully subsumed by computer science, nor vice versa. Consequently, also the philosophies of computer science and software engineering—though related to (...) each other—are not identical branches of a general philosophy of science. This also implies that not all of Eden’s earlier arguments can be directly mapped from the domain of computer science into the domain of software science. After the discussion of this main topic, the essay also points to some further problems and open issues for future studies in the philosophy of software science and engineering. (shrink)

The types of errors that emerge in the development and maintenance of software are essentially different from the types of errors that emerge in the development and maintenance of engineered hardware products. There is a set of standard responses to actual and potential hardware errors, including: engineering ethics codes, engineering practices, corporate policies and laws. The essential characteristics of software errors require new ethical, policy, and legal approaches to the development of software in the global arena.

The phenomenon of digital computation is explained (often differently) in computer science, computer engineering and more broadly in cognitive science. Although the semantics and implications of malfunctions have received attention in the philosophy of biology and philosophy of technology, errors in computational systems remain of interest only to computer science. Miscomputation has not gotten the philosophical attention it deserves. Our paper fills this gap by offering a taxonomy of miscomputations. This taxonomy is underpinned by a conceptual analysis of the design (...) and implementation of conventional computational systems at various levels of abstraction. It shows that ‘malfunction’ as it is typically used in the philosophy of artefacts only represents one type of miscomputation. (shrink)

Part of the distinction between artefacts, objects made by humans for particular purposes, and natural objects is that artefacts are subject to normative judgements. A drill, say, can be a good drill or a poor drill, it can function well or correctly or it can malfunction. In this paper I investigate how such judgements fit into the domain of the normative in general and what the grounds for their normativity are. Taking as a starting point a general characterization of normativity (...) proposed by Dancy, I argue how statements such as ‘this is a good drill’ or ‘this drill is malfunctioning’ can be seen to express normative facts, or the content of normative statements. What they say is that a user who has a desire to achieve a particular relevant outcome has a reason to use, or not to use, the artefact in question. Next this analysis is extended to show that not just statements that say that an artefact performs its function well or poorly, but all statements that ascribe a function to an artefact can be seen as expressing a normative fact. On this approach the normativity of artefacts is analyzed in terms of reasons on grounds of practical, and to a lesser extent theoretical, rationality. I close by investigating briefly to what extent reasons on moral grounds are, in the analysis adopted here, involved in the normativity of artefacts.Keywords: Artefact; Normativity; Instrumental reason; Practical rationality; Function; Use. (shrink)

The use of “levels of abstraction” in philosophical analysis (levelism) has recently come under attack. In this paper, I argue that a refined version of epistemological levelism should be retained as a fundamental method, called the method of levels of abstraction. After a brief introduction, in section “Some Definitions and Preliminary Examples” the nature and applicability of the epistemological method of levels of abstraction is clarified. In section “A Classic Application of the Method ofion”, the philosophical fruitfulness of the new (...) method is shown by using Kant’s classic discussion of the “antinomies of pure reason” as an example. In section “The Philosophy of the Method of Abstraction”, the method is further specified and supported by distinguishing it from three other forms of “levelism”: (i) levels of organisation; (ii) levels of explanation and (iii) conceptual schemes. In that context, the problems of relativism and antirealism are also briefly addressed. The conclusion discusses some of the work that lies ahead, two potential limitations of the method and some results that have already been obtained by applying the method to some long-standing philosophical problems. (shrink)

Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming (...) languages function as models of causal (or physical) machines. The resulting account suggests that sets of models embedded within models are indispensable for computer programming. (shrink)

A persistent boast of the historical approach to functions is that functional properties are normative. The claim is that a token trait retains its functional status even when it is defective, diseased, or damaged and consequently unable to perform the relevant task. This is because historical functional categories are defined in terms of some sort of historical success -- success in natural selection, typically -- which imposes a norm upon the performance of descendent tokens. Descendents thus are supposed to perform (...) the associated task even when they cannot. The conceit, then, is that malfunctions are explicable in terms of historical success. The aim of this paper is to challenge this conceit. My thesis is that the historical approach to functions lacks the resources with which to account for the possibility of malfunctions. If functional types are defined in terms of historical success, then tokens that lack the defining property due to defect, and tokens that have lost the defining property due to disease or damage, are excluded from the functional category. Historically based malfunctions, in consequence, are impossible. The historical approach is no better than its non-historical competitors in accounting for the presumed normativity of functional properties. (shrink)

This paper analyzes both philosophical and practical assumptions underlying claims for the dual nature of software, including software as a machine made of text, and software as a concrete abstraction. A related view of computer science as a branch of pure mathematics is analyzed through a comparative examination of the nature of abstraction in mathematics and computer science. The relationship between the concrete and the abstract in computer programs is then described by exploring a taxonomy of approaches borrowed from philosophy (...) of mind. (shrink)

The distinction between the modeling of information and the modeling of data in the creation of automated systems has historically been important because the development tools available to programmers have been wedded to machine oriented data types and processes. However, advances in software engineering, particularly the move toward data abstraction in software design, allow activities reasonably described as information modeling to be performed in the software creation process. An examination of the evolution of programming languages and development of general programming (...) paradigms, including object-oriented design and implementation, suggests that while data modeling will necessarily continue to be a programmer's concern, more and more of the programming process itself is coming to be characterized by information modeling activities. (shrink)

We characterize abstraction in computer science by first comparing the fundamental nature of computer science with that of its cousin mathematics. We consider their primary products, use of formalism, and abstraction objectives, and find that the two disciplines are sharply distinguished. Mathematics, being primarily concerned with developing inference structures, has information neglect as its abstraction objective. Computer science, being primarily concerned with developing interaction patterns, has information hiding as its abstraction objective. We show that abstraction through information hiding is a (...) primary factor in computer science progress and success through an examination of the ubiquitous role of information hiding in programming languages, operating systems, network architecture, and design patterns. (shrink)

This paper takes part in the methodological debate concerning the nature and the justification of hypotheses about computational systems in software engineering by providing an epistemological analysis of Software Testing, the practice of observing the programs’ executions to examine whether they fulfil software requirements. Property specifications articulating such requirements are shown to involve falsifiable hypotheses about software systems that are evaluated by means of tests which are likely to falsify those hypotheses. Software Reliability metrics, used to measure the growth of (...) probability that given failures will occur at specified times as new executions are observed, is shown to involve a Bayesian confirmation of falsifiable hypotheses on programs. Coverage criteria, used to select those input values with which the system under test is to be launched, are understood as theory-laden principles guiding software tests, here compared to scientific experiments. Redundant computations, fault seeding models and formal methods used in software engineering to evaluate test results are taken to be instantiations of some epistemological strategies used in scientific experiments to distinguish between valid and non-valid experimental outcomes. The final part of the paper explores the problem, advanced in the context of the philosophy of technology, of defining the epistemological status of software engineering by conceiving it as a scientifically attested technology. (shrink)

Questions concerning the epistemological status of computer science are, in this paper, answered from the point of view of the formal verification framework. State space reduction techniques adopted to simplify computational models in model checking are analysed in terms of Aristotelian abstractions and Galilean idealizations characterizing the inquiry of empirical systems. Methodological considerations drawn here are employed to argue in favour of the scientific understanding of computer science as a discipline. Specifically, reduced models gained by Dataion are acknowledged as Aristotelian (...) abstractions that include only data which are sufficient to examine the interested executions. The present study highlights how the need to maximize incompatible properties is at the basis of both Abstraction Refinement, the process of generating a cascade of computational models to achieve a balance between simplicity and informativeness, and the Multiple Model Idealization approach in biology. Finally, fairness constraints, imposed to computational models to allow fair behaviours only, are defined as ceteris paribus conditions under which temporal formulas, formalizing software requirements, acquire the status of law-like statements about the software systems executions. (shrink)

"The biggest contribution of Vincenti's splendidly crafted book may well be that it offers us a believably human image of the engineer."--Technology Review. Johns Hopkins Studies in the History of Technology. Merritt Roe Smith, Series Editor.

In defining the concept of software, I try at first to distinguish software from data, noise, and abstract patterns of information with no material embodiment. But serious objections prevent any of these distinctions from remaining stable. The strong thesis that software is pattern per se, or syntactical form, is initially refined to overcome obvious difficulties; but further arguments show that the refinements are trivial and that the strong thesis is defensible.