What Naur got wrong from The concept of mind

5 hours ago

The author argues that Peter Naur misinterprets Gilbert Ryle's concept of theory, conflating intelligence with intellect.
Naur's reference to Popper's World 3 objects is deemed odd because Ryle rejects the separation of mind and matter.
Ryle distinguishes intelligence (applying criteria critically) from intellect (theorizing), but Naur incorrectly attributes Ryle's points about intelligence to theory.
Despite confusions, the author agrees that programming is theory building, as Ryle's analogy of a thinker smoothing a path applies to programmers modifying code.
Naur's claim that theory revival from documentation is 'strictly impossible' is overblown; code and documentation can convey theory, though it may be difficult.
The author criticizes Naur for focusing only on program modifications, ignoring well-understood systems like compilers that require no new theory.

The article argues that in large software systems, having only a partial understanding of the codebase is acceptable and often necessary.
It critiques Peter Naur's 'Programming as Theory Building' by stating that rebuilding large systems from scratch is impractical due to complexity and that abandoned systems can be revived through gradual learning.
The author suggests that engineers in large teams must work with imperfect mental models, making educated guesses and dealing with consequences.

Software engineers have differing views on codebase understanding: small, low-turnover teams advocate complete understanding, while large, high-turnover teams accept partial understanding.
Peter Naur's 'Programming as Theory Building' argues that code is a by-product of a programmer's 'theory of the program,' but his conclusion that code should be discarded when theory is lost is impractical for large systems.
Large software systems cannot be rebuilt from scratch due to countless quirks; rewrites must occur incrementally by carving out small chunks.

The author critiques the presentation and perceived manipulative nature of 'Uncle Bob' (Robert C. Martin)'s works like Clean Code and SOLID principles.
He finds the content filled with unnecessary filler, akin to academic padding, and questions the subjective naming like 'Clean' or 'Simple' for code.
The author argues that software engineering culture is dogmatic and overly reliant on acronyms (e.g., SOLID, DRY) that can lead to complexity rather than clarity.

Psychological phenomena like power posing, ego depletion, and growth mindset persist in research despite being debunked, often rebranded under new names.
The replication crisis has not settled disputes; theories continue to be studied because they are difficult to definitively falsify, leading to endless debates.
The author proposes a 'Halo theory' of science: scientific theories never truly die, they only become embarrassing, and instead of trying to kill them, we should recognize when they are no longer worth pursuing.

The search for truth involves building and refining falsifiable theories, which can always be improved but never proven absolutely true.
Magical theories are unfalsifiable and cannot be improved, often causing pain and leading to abusive attachments like the Spanish Prisoner con.
Emotions provide valid data for detecting friction in theories, but should be regulated to avoid clouding judgment.

The article argues that in large software systems, having only a partial understanding of the codebase is acceptable and often necessary.
It critiques Peter Naur's 'Programming as Theory Building' by stating that rebuilding large systems from scratch is impractical due to complexity and that abandoned systems can be revived through gradual learning.
The author suggests that engineers in large teams must work with imperfect mental models, making educated guesses and dealing with consequences.

Software engineers have differing views on codebase understanding: small, low-turnover teams advocate complete understanding, while large, high-turnover teams accept partial understanding.
Peter Naur's 'Programming as Theory Building' argues that code is a by-product of a programmer's 'theory of the program,' but his conclusion that code should be discarded when theory is lost is impractical for large systems.
Large software systems cannot be rebuilt from scratch due to countless quirks; rewrites must occur incrementally by carving out small chunks.

The author critiques the presentation and perceived manipulative nature of 'Uncle Bob' (Robert C. Martin)'s works like Clean Code and SOLID principles.
He finds the content filled with unnecessary filler, akin to academic padding, and questions the subjective naming like 'Clean' or 'Simple' for code.
The author argues that software engineering culture is dogmatic and overly reliant on acronyms (e.g., SOLID, DRY) that can lead to complexity rather than clarity.

Psychological phenomena like power posing, ego depletion, and growth mindset persist in research despite being debunked, often rebranded under new names.
The replication crisis has not settled disputes; theories continue to be studied because they are difficult to definitively falsify, leading to endless debates.
The author proposes a 'Halo theory' of science: scientific theories never truly die, they only become embarrassing, and instead of trying to kill them, we should recognize when they are no longer worth pursuing.

The search for truth involves building and refining falsifiable theories, which can always be improved but never proven absolutely true.
Magical theories are unfalsifiable and cannot be improved, often causing pain and leading to abusive attachments like the Spanish Prisoner con.
Emotions provide valid data for detecting friction in theories, but should be regulated to avoid clouding judgment.

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