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The Science of Computing: Shaping a Discipline
The identity of computing has been fiercely debated throughout its short history. Why is it still so hard to define computing as an academic discipline? Is computing a scientific, mathematical, or engineering discipline? By describing the mathematical, engineering, and scientific traditions of computing, The Science of Shaping a Discipline presents a rich picture of computing from the viewpoints of the field’s champions. The book helps readers understand the debates about computing as a discipline. It explains the context of computing’s central debates and portrays a broad perspective of the discipline.The book first looks at computing as a formal, theoretical discipline that is in many ways similar to mathematics, yet different in crucial ways. It traces a number of discussions about the theoretical nature of computing from the field’s intellectual origins in mathematical logic to modern views of the role of theory in computing.The book then explores the debates about computing as an engineering discipline, from the central technical innovations to the birth of the modern technical paradigm of computing to computing’s arrival as a new technical profession to software engineering gradually becoming an academic discipline. It presents arguments for and against the view of computing as engineering within the context of software production and analyzes the clash between the theoretical and practical mindsets.The book concludes with the view of computing as a science in its own right—not just as a tool for other sciences. It covers the early identity debates of computing, various views of computing as a science, and some famous characterizations of the discipline. It also addresses the experimental computer science debate, the view of computing as a natural science, and the algorithmization of sciences.
292 pages, Kindle Edition
First published August 15, 2014
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About the author
Matti Tedre
2 books1 followerMatti Tedre is a Professor in the School of Computing at the University of Eastern Finland, Associate Professor in the Department of Computer and Systems Science at Stockholm University, and the author of The Science of Computing: Shaping a Discipline.
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Displaying 1 - 2 of 2 reviews
June 14, 2020
TODO review sketch:
+++ If you have time to read only one book to understand what computer science is about, read Matti Tedre's The Science of Computing: Shaping a Discipline. I've been learning about and working in this field for over 25 years, and still learned much from this book. Loved it.
i I took nearly 400 notes and made nearly 700 highlights. This is the most I've done in any book, regardless of its length. This matches the approach taken by the author: read everything, report on everything, let the reader do the filtering. Works for me.
+++ One very important observation: that the debate about the science in computer science seems petty, when compared with the changes brought by computing (and computational methods)
to other sciences and the impact this had on the society.
+++/-- An amazing wealth of references, all analyzed. The format of the digital book makes it extremely difficult to follow the analysis, because it is placed at the end, and navigation in the Kindle reader is very poor. The author should consider using footnotes, to give the reader a fighting chance.
+++ Understand key concepts in computer science, starting with computer science (and the family of related theory, practice, and science fields, such as information technology and systems, scientific computing, e-Science, computing science, etc.)
++ Very good analysis of important terminology in computing, including the notion of "experiment" as used across computing and other sciences.
+++/-- Focus on important and field-shaping debates: about the nature of computing as a discipline, about the role of mathematics in computer science, about the roles of theory and practice in computing, about the theoretical/engineering/scientific traditions in computing (but where is the design tradition, as exemplified by Frederick P. Brooks, Jr. and his work on IBM/360?), about the need to try in practice and test, about the methodology to study and evolve computer science, etc. But the selection of topics comes with drawbacks: where are the debates about ethics?
+ Identifying and explaining the role of well-crafted, powerful rhetoric in shaping computing. Foremost example: the often vitriolic attacks of the academia-centered community working on strong formal verification on anything they saw as "mere engineering" (e.g., software engineering) has led to two decades of witch-hunting on the corridors of many universities, and the development and prominence of technical universities. Who knew Dijkstra was so scary?! Who knew Hoare was so wrong in understanding the difference between computing as abstraction and computing as physical, interactive process? Who knew so many computer scientists have tried to compare their work with the Greeks' on axiomatic geometry, Netwon's on the laws of motion, and Leibniz's on calculus?
+++ Identifying and explaining why computer science is value-laden, as opposed to the value-free (pure) mathematics, and why it matters.
+++ Understand the history of the core elements of computer science. The waves of intellectual pursuit, from the early onset of making things work (1940s), to separating from mathematics (1950s), to making a discipline out of practice (1950s), to defining a curriculum (stabilized around the 1960s, albeit, with expansions since), to the emergence of many domains beyond numerical computation through expansion toward many (all?) scientific disciplines and domains of application (1970s), to the "software crisis" and the clash between the advocates of the strong formal verification and practice (from the emergence of "software engineering" in 1968, and until the 1980s and their refutation of the claims of strong formal verification), to the move for "experimental computer science" (emerging in 1980s, 1990s methodological wars, and re-emerging of the idea in the 2000s with large-scale computing), to the emergence of computing in all scientific and technical domains in "the age of simulation" (2000s), to the legitimacy gained by the (previously seen as practical) software engineering and information systems in all curricula (2000s and 2010s).
++ Some nice observations: Vannevar Bush, of the As We May Think, Science: The Endless Frontier, and other influential policy-documents renown, almost caused the rejection of the ENIAC proposal for funding, because he thought the use of electronics would be inefficient; 60 years later, turns out we are still using electronics. Let's say John von Neumann did not give credit initially, and never worked again with the engineers of the first stored-program computer, Eckert and Mauchly. Turing's ideas seem to have had little impact on the development of the first computers. Grace Hopper developed the first automatic compiler, but performance reasons delayed the adoption of this technology; this retained the jobs of many coders, which at the time were primarily women. Wirth's "Law": the computer you want will always cost $5,000; it still does work. Etc.
+++/- An excellent analysis of the evolution of computer science/computing curricula by ACM. Would have been interesting to see an analysis of the joint ACM/IEEE curriculum (finalized in 2013 for Computer Science).
+++ Understand the main figures of the computer science debates and evolution, from the unsuspecting Jacquard and Pascal, to the combative Dijkstra and Hoare, to the philosophical Simon and Valiant.
- Does not cover the new age: the Internet, the WWW, grid and cloud computing, peer-to-peer and edge-centric computing, etc. This is somewhat ok: a book has to stop somewhere, and the author mentions the first two items in the list. Implicitly, the book does not cover any computing idea after 2014, when it was first published.
--- Does not cover design in a modern sense, or even much at all.
- Some typos: "body [of] knowledge" (Location: 63,790); "similar[ly]," (Location: 96,557).
+++ If you have time to read only one book to understand what computer science is about, read Matti Tedre's The Science of Computing: Shaping a Discipline. I've been learning about and working in this field for over 25 years, and still learned much from this book. Loved it.
i I took nearly 400 notes and made nearly 700 highlights. This is the most I've done in any book, regardless of its length. This matches the approach taken by the author: read everything, report on everything, let the reader do the filtering. Works for me.
+++ One very important observation: that the debate about the science in computer science seems petty, when compared with the changes brought by computing (and computational methods)
to other sciences and the impact this had on the society.
+++/-- An amazing wealth of references, all analyzed. The format of the digital book makes it extremely difficult to follow the analysis, because it is placed at the end, and navigation in the Kindle reader is very poor. The author should consider using footnotes, to give the reader a fighting chance.
+++ Understand key concepts in computer science, starting with computer science (and the family of related theory, practice, and science fields, such as information technology and systems, scientific computing, e-Science, computing science, etc.)
++ Very good analysis of important terminology in computing, including the notion of "experiment" as used across computing and other sciences.
+++/-- Focus on important and field-shaping debates: about the nature of computing as a discipline, about the role of mathematics in computer science, about the roles of theory and practice in computing, about the theoretical/engineering/scientific traditions in computing (but where is the design tradition, as exemplified by Frederick P. Brooks, Jr. and his work on IBM/360?), about the need to try in practice and test, about the methodology to study and evolve computer science, etc. But the selection of topics comes with drawbacks: where are the debates about ethics?
+ Identifying and explaining the role of well-crafted, powerful rhetoric in shaping computing. Foremost example: the often vitriolic attacks of the academia-centered community working on strong formal verification on anything they saw as "mere engineering" (e.g., software engineering) has led to two decades of witch-hunting on the corridors of many universities, and the development and prominence of technical universities. Who knew Dijkstra was so scary?! Who knew Hoare was so wrong in understanding the difference between computing as abstraction and computing as physical, interactive process? Who knew so many computer scientists have tried to compare their work with the Greeks' on axiomatic geometry, Netwon's on the laws of motion, and Leibniz's on calculus?
+++ Identifying and explaining why computer science is value-laden, as opposed to the value-free (pure) mathematics, and why it matters.
+++ Understand the history of the core elements of computer science. The waves of intellectual pursuit, from the early onset of making things work (1940s), to separating from mathematics (1950s), to making a discipline out of practice (1950s), to defining a curriculum (stabilized around the 1960s, albeit, with expansions since), to the emergence of many domains beyond numerical computation through expansion toward many (all?) scientific disciplines and domains of application (1970s), to the "software crisis" and the clash between the advocates of the strong formal verification and practice (from the emergence of "software engineering" in 1968, and until the 1980s and their refutation of the claims of strong formal verification), to the move for "experimental computer science" (emerging in 1980s, 1990s methodological wars, and re-emerging of the idea in the 2000s with large-scale computing), to the emergence of computing in all scientific and technical domains in "the age of simulation" (2000s), to the legitimacy gained by the (previously seen as practical) software engineering and information systems in all curricula (2000s and 2010s).
++ Some nice observations: Vannevar Bush, of the As We May Think, Science: The Endless Frontier, and other influential policy-documents renown, almost caused the rejection of the ENIAC proposal for funding, because he thought the use of electronics would be inefficient; 60 years later, turns out we are still using electronics. Let's say John von Neumann did not give credit initially, and never worked again with the engineers of the first stored-program computer, Eckert and Mauchly. Turing's ideas seem to have had little impact on the development of the first computers. Grace Hopper developed the first automatic compiler, but performance reasons delayed the adoption of this technology; this retained the jobs of many coders, which at the time were primarily women. Wirth's "Law": the computer you want will always cost $5,000; it still does work. Etc.
+++/- An excellent analysis of the evolution of computer science/computing curricula by ACM. Would have been interesting to see an analysis of the joint ACM/IEEE curriculum (finalized in 2013 for Computer Science).
+++ Understand the main figures of the computer science debates and evolution, from the unsuspecting Jacquard and Pascal, to the combative Dijkstra and Hoare, to the philosophical Simon and Valiant.
- Does not cover the new age: the Internet, the WWW, grid and cloud computing, peer-to-peer and edge-centric computing, etc. This is somewhat ok: a book has to stop somewhere, and the author mentions the first two items in the list. Implicitly, the book does not cover any computing idea after 2014, when it was first published.
--- Does not cover design in a modern sense, or even much at all.
- Some typos: "body [of] knowledge" (Location: 63,790); "similar[ly]," (Location: 96,557).
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April 23, 2021The Review by Mr Scott is FANTASTIC
Displaying 1 - 2 of 2 reviews