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  1. Classes of Recursively Enumerable Sets and Their Decision Problems.H. G. Rice - 1954 - Journal of Symbolic Logic 19 (2):121-122.
  • The Ontology of Cyberspace: Philosophy, Law, and the Future of Intellectual Property.David Richard Koepsell - 2000 - Open Court Publishing Company.
  • The Second Treatise of Government. Über Die Regierung: Englisch/Deutsch.John Locke - 1966 - [New York]Barnes & Noble.
  • Computational Artifacts: Towards a Philosophy of Computer Science.Raymond Turner - 2018 - Springer Berlin Heidelberg.
    The philosophy of computer science is concerned with issues that arise from reflection upon the nature and practice of the discipline of computer science. This book presents an approach to the subject that is centered upon the notion of computational artefact. It provides an analysis of the things of computer science as technical artefacts. Seeing them in this way enables the application of the analytical tools and concepts from the philosophy of technology to the technical artefacts of computer science. With (...)
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  • What an Algorithm Is.Robin K. Hill - 2016 - Philosophy and Technology 29 (1):35-59.
    The algorithm, a building block of computer science, is defined from an intuitive and pragmatic point of view, through a methodological lens of philosophy rather than that of formal computation. The treatment extracts properties of abstraction, control, structure, finiteness, effective mechanism, and imperativity, and intentional aspects of goal and preconditions. The focus on the algorithm as a robust conceptual object obviates issues of correctness and minimality. Neither the articulation of an algorithm nor the dynamic process constitute the algorithm itself. Analysis (...)
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  • Software Intensive Science.John Symons & Jack Horner - 2014 - Philosophy and Technology 27 (3):461-477.
    This paper argues that the difference between contemporary software intensive scientific practice and more traditional non-software intensive varieties results from the characteristically high conditionality of software. We explain why the path complexity of programs with high conditionality imposes limits on standard error correction techniques and why this matters. While it is possible, in general, to characterize the error distribution in inquiry that does not involve high conditionality, we cannot characterize the error distribution in inquiry that depends on software. Software intensive (...)
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  • The Problem of Justification of Empirical Hypotheses in Software Testing.Nicola Angius - 2014 - Philosophy and Technology 27 (3):423-439.
    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 (...)
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  • The Method of Levels of Abstraction.Luciano Floridi - 2008 - Minds and Machines 18 (3):303–329.
    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 (...)
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  • Philosophy of Computer Science: An Introductory Course.William J. Rapaport - 2005 - Teaching Philosophy 28 (4):319-341.
    There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments.
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  • Copies, Replicas, and Counterfeits of Artworks and Artefacts.Marzia Soavi & Massimiliano Carrara - 2010 - The Monist 93 (3):414-432.
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  • On Malfunctioning Software.Giuseppe Primiero, Nir Fresco & Luciano Floridi - 2015 - Synthese 192 (4):1199-1220.
    Artefacts do not always do what they are supposed to, due to a variety of reasons, including manufacturing problems, poor maintenance, and normal wear-and-tear. Since software is an artefact, it should be subject to malfunctioning in the same sense in which other artefacts can malfunction. Yet, whether software is on a par with other artefacts when it comes to malfunctioning crucially depends on the abstraction used in the analysis. We distinguish between “negative” and “positive” notions of malfunction. A negative malfunction, (...)
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  • Second Treatise on Government.John Locke - 1690/1980 - In Elizabeth Schmidt Radcliffe, Richard McCarty, Fritz Allhoff & Anand Vaidya (eds.), Late Modern Philosophy: Essential Readings with Commentary. Blackwell.
  • Model-Based Abductive Reasoning in Automated Software Testing.N. Angius - 2013 - Logic Journal of the IGPL 21 (6):931-942.
    Automated Software Testing (AST) using Model Checking is in this article epistemologically analysed in order to argue in favour of a model-based reasoning paradigm in computer science. Preliminarily, it is shown how both deductive and inductive reasoning are insufficient to determine whether a given piece of software is correct with respect to specified behavioural properties. Models algorithmically checked in Model Checking to select executions to be observed in Software Testing are acknowledged as analogical models which establish isomorphic relations with the (...)
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  • What is an Algorithm?Yiannis Moschovakis - 2001 - In Mathematics Unlimited --- 2001 and beyond.
     
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  • Natural Intellectual Property Rights and the Public Domain.Hugh Breakey - 2010 - Modern Law Review 73 (2):208-239.
    No natural rights theory justifies strong intellectual property rights. More specifically, no theory within the entire domain of natural rights thinking – encompassing classical liberalism, libertarianism and left-libertarianism, in all their innumerable variants – coherently supports strengthening current intellectual property rights. Despite their many important differences, all these natural rights theories endorse some set of members of a common family of basic ethical precepts. These commitments include non-interference, fairness, non-worsening, consistency, universalisability, prior consent, self-ownership, self-governance, and the establishment of zones (...)
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  • What is an Algorithm.Yuri Gurevich - 2012 - Lecture Notes in Computer Science.
  • Intellectual Property.Adam Moore - forthcoming - Stanford Encyclopedia of Philosophy.
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