Under Permanent Construction

• DOGgy Style Programming
• Wax On -- Wax Off
• Half-Truth Tables and Abnormal Forms: The Hitchhiker's Guide To Logic

• Software

  • Netflix More More Info, SIMKL TV SIMKL MOV - More Info button for titles on Netflix More Info pages.
  • Kallithea Repositories
  • Python Snippets
  • Emacs development
  • Emacs vc Ignore Feature

• Documentation

  • Documentation Standard
  • Kallithea Deployment

• Applicants

  • Work Package for Applicants
  • Applicant 1: repository documentation application
  • Applicant 2: repository documentation application
  • Applicant 3: repository documentation application
  • Applicant 4: repository documentation application
  • Applicant 5: repository documentation application
  • Applicant 6: repository documentation application
  • Applicant 7: repository documentation application
  • Applicant 8: repository documentation application
  • Applicant 9: repository documentation application
  • Applicant 10: repository documentation application
  • Applicant 11: repository documentation application

• Sudoku

  • The World's Hardest Sudoku describes an IDDFS algorithm for solving sudokus.
    It is suitable for humans with paper, pencil and a copy machine or a computer program.
    The depth does not exceed 3 hypotheses for any given sudoku.
  • Automated Sudoku Documentations
    The hardest sudokus are in level very deep.
  • HDP Sudoku - Hypothesis/Disproof/Proof helper for Sudokus.
    • Linux (pyinstaller archive)
      Try HDPSudoku --help for batch options.
      Optional OS packages: sudo apt-get install graphviz
      
    • Windows (pyinstaller archive)
      Try HDPSudoku.exe --help for batch options.
      Optional OS packages: GraphViz
    • Python (AdHoc'ed archive)
      Use python HDPSudoku.py --help to see batch options.
      

      Needs OS packages:	sudo apt-get install python-qt4 python-docutils python-pymongo python-sqlalchemy
      Needs python packages:	pip install ws_docutils
      Optional OS packages:	sudo apt-get install graphviz

      Use python HDPSudoku.py --explode to view/modify source code.
      

Satoku Material

• Satoku Matrix

  • Oreganography (PDF)
  • Structural Single State Mutinex Logic (PDF) -- Satoku Matrix in a nut-shell. Describes an inverted adjacency matrix as a formalized state relation matrix.
  • Satoku Matrix Principle -- what Structural Logic aims at, and where it will arrive one day
  • Generalization of CNF and Consequences for DNF of Implicants under Distributive Expansion (PDF) -- Precursor to the Satoku Matrix
  • CDCL and Direct Encoding -- SAT solver experiments
  • Rationale for the Satoku Matrix -- Abstract Drafts and Notes
  • Satoku package (Emacs Lisp, Python, examples) (18Mb)
    • satoku.el documentation
    • Satoku Python Module (documentation)

• Other Satoku Matrix Material

  • Partial Distributive Expansion of CNF Problems - The Foundation of the Satoku Matrix
  • 2-SAT Algorithm For Complete Set of Solutions (PDF, almost finished)
  • Satoku Matrix: Mapping a Logical Problem
  • Satoku Matrix: 2-SAT Solutions
  • Satoku Matrix: Row Updates
  • Satoku Matrix: Variables, Truth Table, Resolution and Expansion
  • Satoku Matrix: Indirect Conflicts
  • Satoku Matrix: Problem Encoding
  • Satoku Matrix: XOR - Gauss-Jordan Elimination
  • Satoku (general, in permanent flux)

  • Examples (included in package)

    • XOR Analysis
    • 5-Variable XOR (3-SAT)

  • Examples (not included in package)

    • Pick-A-Puck -- the difference between setting propositional variables to true or false and making a selection from a clause

  • Experimental (links may or may not work, so don't bookmark)

    • Prime Implicants And Reliable Assignments
    • 2-SAT Solutions
    • Distributed Conjunctive Single-Selection (3-SAT)
    • Distributed Conjunctive Single-Selection (4-SAT)
    • 6-Variable Contradiction (3-SAT)
    • 6-Variable XOR
    • Various Resolution Algorithms
• Rants

FUQ-T-FAQ: Frequently Unanswered Questions To Frequently Answered Questions

• The "deprecated" warning dilemma

  "This POS is deprecated. Do not use in new code."

  What if I am writing new code to be run both on an old system and a new system?
  Now, do I have to write it twice, if I do not appreciate the stupid warnings?

  Of course not, just define the new stuff in terms of the old stuff:
  (unless (fboundp 'new-stuff) (defun new-stuff() (in terms of old-stuff)))

  This would also be the Python from __future__ import new-stuff principle, if only import from __future__ did work all the way back to version 0.0.

• The "cut-and-paste" conundrum (also: the library misconception)

  "`Cut-and-paste' is the Devil's highway to hell."

  Oh! But it feels so good!?

  Well -- as with other things -- if you are doing it for procreation, you are doing Yggod's work.

  The rules for code procreation by `cut-and-paste' are simple:

  • If the copy is given up for adoption (i.e., nobody cares what becomes of it):
    • Copy as much as possible, since everything copied contains no additional typos.
    • Modify the copy to your heart's content.
  • If the clones may have to be refurbished at a later time:
    • Keep the original for reference and modification.
    • Prominently mark the beginning of the copied section and never ever modify it after pasting (anchor for diff(1)).
    • Generally avoid modification after pasting. Instead, modify the original and regenerate the clone(s) at your earliest convenience. Or when hell freezes over. Whichever comes first.

  This results in the concept of a single-step library.
  A Library of text snippets, which is used with diff(1) to update copies manually, semi-automatically or fully automatically.