A Taxonomy of Errors for Information Systems

We provide a full characterization of computational error states for information systems. The class of errors considered is general enough to include human rational processes, logical reasoning, scientific progress and data processing in some functional programming languages. The aim is to reach a full taxonomy of error states by analysing the recovery and processing of data. We conclude by presenting machine-readable checking and resolve algorithms.

[1]  D. Mayo ONE Learning from Error , Severe Testing , and the Growth of Theoretical Knowledge , 2011 .

[2]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[3]  J. Shaoul Human Error , 1973, Nature.

[4]  Giuseppe Primiero,et al.  An epistemic logic for becoming informed , 2009, Synthese.

[5]  Giovanni Sommaruga Formal Theories of Information: From Shannon to Semantic Information Theory and General Concepts of Information [Muenchenwiler Seminar (Switzerland), May 2009] , 2009, Formal Theories of Information.

[6]  Luciano Floridi,et al.  Philosophical Conceptions of Information , 2009, Formal Theories of Information.

[7]  Denis Bonnay,et al.  Knowing One’s Limits: An Analysis in Centered Dynamic Epistemic Logic , 2011 .

[8]  Keith DeRose Knowledge and its Limits , 2002 .

[9]  Bjørn Jespersen,et al.  Two Conceptions of Technical Malfunction , 2011 .

[10]  B. B. Agarwal,et al.  Software Engineering and Testing: An Introduction , 2009 .

[11]  D. Mayo Error and Inference: Learning from Error, Severe Testing, and the Growth of Theoretical Knowledge , 2009 .

[12]  Steven A. Moore,et al.  Philosophy and design: From engineering to architecture , 2008 .

[13]  William A. Howard,et al.  The formulae-as-types notion of construction , 1969 .

[14]  M. Sørensen,et al.  Lectures on the Curry-Howard Isomorphism, Volume 149 (Studies in Logic and the Foundations of Mathematics) , 2006 .

[15]  Giuseppe Primiero,et al.  Offline and online data: on upgrading functional information to knowledge , 2012, Philosophical Studies.

[16]  Greg J. Michaelson,et al.  An introduction to functional programming through lambda calculus , 2011, International computer science series.

[17]  Charles S. Peirce,et al.  Illustrations of the Logic of Science , 2014 .

[18]  H. B. Curry,et al.  Combinatory Logic, Volume I. , 1961 .

[19]  Diego Calvanese,et al.  The Description Logic Handbook , 2007 .

[20]  Douglas Allchin,et al.  Error Types , 2001, Perspectives on Science.

[21]  John E. Woods The Death of Argument , 2004 .

[22]  H B Curry,et al.  Functionality in Combinatory Logic. , 1934, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Edwin D. Mares,et al.  Informational Semantics as a Third Alternative? , 2012 .

[24]  M. Sørensen,et al.  Lectures on the Curry-Howard Isomorphism , 2013 .

[25]  Maarten Franssen Design, Use, and the Physical and Intentional Aspects of Technical Artifacts , 2008 .

[26]  John E. Woods,et al.  The death of argument - fallacies in agent based reasoning , 2004, Applied logic series.

[27]  David I. Beaver Presupposition and Assertion in Dynamic Semantics , 2001 .

[28]  J. Roger Hindley,et al.  To H.B. Curry: Essays on Combinatory Logic, Lambda Calculus, and Formalism , 1980 .

[29]  Raymond Turner,et al.  Specification , 2011, Minds and Machines.

[30]  Massimiliano Carrara,et al.  A New Logic of Technical Malfunction , 2013, Stud Logica.

[31]  S. D’Alfonso,et al.  The Logic Of Being Informed , 2010 .

[32]  J. Farris CONJECTURES AND REFUTATIONS , 1995, Cladistics : the international journal of the Willi Hennig Society.