This page is under development. Comments are welcome, but please load any comments in the comments section at the bottom of the page. Please include your wiki MONIKER and date in your comment with the same courtesy that I will give you. Aside from your courtesy, your wiki MONIKER and date as a signature and minimal good faith of any internet post are the rules of this TCL-WIKI. Its very hard to reply reasonably without some background of the correspondent on his WIKI bio page. Thanks, gold 20Aug2020
gold Update 3/7/2024. Pseudocode serves as a bridge between human thinking and computer programming, allowing developers to plan solutions before writing actual code. This article explores effective pseudocode practices specifically designed for Tool Command Language (TCL) programming. Understanding these rules helps programmers create clearer logic flows and reduces errors when transitioning from planning to implementation.
Here are some calculations with Pseudocode outline in reference to TCL Procedures. Console program outputs data as table in TCL table format and comma delimited spreadsheet. These auxiliary decks are used to proof features or subroutines of the prospective gui program. The Monopoly page from GWM seems closest in theme to what I was trying to learn. Using dice and running with random throws along a track or path like Snakes and Ladders.
gold Update 3/7/2024. The author is retired engineer on Windows 10 and no longer has proofing access to Unix machines. Unix is respected after use of so many decades in engineering, but my wings are lost. I did find a useful online IDE, jdoodle. I can paste from a text file, edit, and run an output using this online IDE.
This page on developing pseudocode examples and one line procedures is not a replacement for the current Tcl core and Tcllib, which is much improved since Tcl version 4, and other <faster> language constructs. math ops, Tcllib routines, and other compiled routines can reduce the cost of big-data tasks by about 1/3. The time savings of the core are not always obvious on small quantities of data, like 4 or 5 numbers. Performance of one-line programs may suffer degradation due to lengthy recursion calls, and may be limited by constraints on recursion. Dependence on math operator notation, helper procedures, math check examples, degradation due to lengthy recursion calls, and special library functions should be noted in the comment lines.
1. Convert the tasks lists into a formal design that can be used as the basis for coding. Break each task into smaller subtasks or sub-subtasks, and then convert each of these detailed elements into lines of pseudocode. Each pseudocode line will represent one "action."
Pseudocode Example:
START
GET user input
IF user input is valid
CALL process user input
DISPLAY processed user input
ELSE
DISPLAY invalid input message
END IF
END2. Capitalize initial keywords: The keywords in the pseudocode should be written in all capital letters, as they begin the statement and give special meaning to the operation. READ, WRITE, IF, WHILE, and UNTIL are examples of keywords that should be written in all capital letters.
START
GET user input
IF user input is valid
CALL process user input
DISPLAY processed user input
ELSE
DISPLAY invalid input message
END IF
END3. Use indentation to show hierarchy: Indentation helps indicate the "boundaries" of the structure within the pseudocode. Sequence structures do not require indentation, but loop or selection structures must indicate which statements are executed within the structure.
START
GET user input
IF user input is valid
CALL process user input
DISPLAY processed user input
ELSE
DISPLAY invalid input message
END IF
END4. End multiline structures: Structures, such as loops or selections, should be ended to provide clarity. Indentation helps indicate the beginning and end of these structures.
START
GET user input
IF user input is valid
CALL process user input
DISPLAY processed user input
ELSE
DISPLAY invalid input message
END IF
END5. Keep statements language-independent: This rule does not mean that pseudocode should be written in a specific language; it means that the pseudocode should be designed in a way that is free of special requirements or capabilities unique to specific programming languages. This ensures that the pseudocode can be translated into any programming language.
gold Update 2/29/2024. Note. The term "language independent statements" has caused debate in either a positive or negative light. There has been some heartburn over the meaning of the phrase " language independent statements". Notice the hyphen is zapped here. The term "language independent" as defined here refers to statements in "natural language" that has no known dependencies on the classic computer programming compilers and interpreters. I say classic programming languages, because there were experimental "natural language programs" used in the 1960's. Some well meaning students are taking "language independent statements" to mean not using a human language at all. Well, getting down into the weeds, that is possible in the math and graphic methods and solutions. There are a number of trials that show crows, squirrels, frogs, and rats solving problems with no involvement of human languages. And subject to interpretation, some of the language independent statements and algorithms were chipped on stone and clay tablets in Sumer Ur III, current Iraq.
Pseudocode is a method of describing the steps in an algorithm or other computed process written in plain "natural" language. Pseudocode does not rely on any particular implementation of a computer programming language In other words, the ugly math is off the table and kept out of sight. There are examples of pseudocode solutions for translating into the TCL script, but use includes possible exercises for translating into other computer languages such as Python or C++.
gold Update 1/19/2026.This article outlines the use of pseudocode as a design tool for procedures in Tool Command Language (Tcl), a scripting language for rapid prototyping and automation. Pseudocode allows developers to describe algorithms in natural language before implementing code in Tcl. The purpose involves exploring key principles to enhance clarity in procedural logic. Pseudocode serves as a language-independent method to break down tasks. Developers start by listing subtasks in simple steps. Keywords appear in all capital letters for emphasis. For example, START marks the beginning. Indentation shows structure in conditionals and loops. Multiline blocks end with explicit closures like END IF. This approach keeps designs clear. A basic example follows: START. GET user input. IF user input is valid. CALL process input. DISPLAY result. ELSE. DISPLAY error message. END IF. END. This structure translates easily to Tcl scripts.
The Lehmer random number generator illustrates pseudocode in Tcl contexts. Tcl includes a built-in rand function for random floats between zero and one. Pseudocode captures the algorithm first. Constants define a as 16807 and m as 2147483647. A function computes temp as a times seed. Seed updates to temp minus m times the integer part of temp over m. The return value divides seed by m. In Tcl, a procedure named randomx implements this. For instance, set a to 16807.0 and m to 2147483647.0. Proc randomx takes seed. It computes temp. It updates seed. It returns the fraction. A seed of 12345 yields approximately 0.0966. This example shows pseudocode guiding efficient implementations.
Common pitfalls arise in pseudocode for Tcl. Recursion risks depth limits in lengthy calls. Dependencies on external libraries require documentation. Pseudocode avoids replacing Tcl core commands. For instance, math operations in Tcllib enhance performance. Overuse of one-line procedures adds overhead.
A new idea involves integrating pseudocode with version control. Developers draft pseudocode in comments. Teams review designs early. This prevents errors in complex simulations like dice games.In conclusion, developers apply pseudocode by breaking tasks into steps and using clear keywords. Implementation follows in Tcl with attention to performance. Regular practice refines algorithmic thinking for better procedures.
A simple idea for human readable code and pseudocode. Programming should be readable not only by computers but by humans. Readability is not achieved by piling on comments, because comments drift out of sync with the code. The goal is instead to make the code itself readable.
This matters because software engineers and domain experts rarely share the same knowledge. The expert knows the business requirements. The programmer knows how to encode logic. A shared representation would let both sides look at the same artifact with a unified viewpoint.
Traditionally, requirements are written in a document, handed to a programmer, interpreted, implemented, and only validated when the system runs. By the time someone notices a mismatch, “months have elapsed.” The proposed alternative is to write human readable code in a form that both parties can read and validate together.
Domain‑specific languages are powerful, but expensive to build. So the experiment is to take mainstream languages and push it toward human readable expression. The example domain is a deck of cards. The goal is to write code that looks almost like English.
Writing the code in psuedocode or *as if* such a language already existed. But the idea is to shape the code around the desired human readable form first. Then build the supporting structures underneath. This reverses the usual order of programming. Instead of asking “what functions do I have,” the programmer asks “what should this read like.”
How to invent interfaces such as *choice*, *action*, and *selection*. These names come from the shared vocabulary negotiated between programmer and domain expert. The method names—*that_Are*, *then_Is*—are chosen to preserve the sentence‑like flow. The underlying implementation is “plumbing,” invisible to the non‑programmer, but essential for execution.
Running the unfinished code produces some errors, which is expected. Once the first example works, new scenarios can be added without rewriting the underlying machinery. Over time, this becomes a set of command or small custom language tailored to the domain. The shared vocabulary allows meaningful conversation at the right level of abstraction.
But for domains with many evolving features, the investment pays off. The biggest payoff appears in testing. If tests are written in this human readable style, the domain expert can validate them directly. A test that is both correct and comprehensible gives strong confidence that the system behaves as intended.
This approach is portable in philosophy, though not in literal code. The same ideas can be applied in Python, JavaScript, C, or any language with different techniques. The guiding principle remains. Start from the human description of the problem and shape the code to match it. Rather than forcing the human description to fit the programming language.
#pseudocode can be developed from rules of thumb.
#pseudocode: some problems can be solved by proportions (rule of three), to some order of magnitude
#pseudocode: enter quantity1, quantity2, quantity3 and expected output (quantity4) for testcases.
#pseudocode: enter time in years, number of remaining items
#pseudocode: output fraction of (remaining items) over (items at time zero)
#pseudocode: ouput remaining items as fraction or percent
#pseudocode: output fraction of (quantity4 ) over ( quantity1 at time zero)
#pseudocode: output fraction of (quantity2) * (quantity3 ) over (quantity1 at time zero)
#pseudocode: outputs should be in compatible units.
#pseudocode: rules of thumb can be 3 to 15 percent off, partly since g..in g..out.
#pseudocode: need test cases > small,medium, giant
#pseudocode: need testcases within range of expected operation.
#pseudocode: are there any cases too small or large to be solved?
#
# F(N+1) == F(N) + F(N-1)
# F(1) == 1
# F(2) == 1
set Grade_School 6
set Middle_School 2
set High_School 4
set College 4
set Graduate_School 2
set values [list 6 8 12 16 18]
set fractals [list 9.7 12.94 19.4 25.888 29.14]
partials, f(1)= .5
f(2) = (1/4) * .5
f(3) = (1/6) * .5
+----------------------------------------------------------------------------------+ | 1) PSEUDOCODE AS A DESIGN BRIDGE | | From human thinking to working TCL program | | | | Human Problem | | Statement | | | | | v | | +--------------------+ | | | Pseudocode | <-- plain natural language, no compiler needed | | | (language- | ugly math kept off the table | | | independent) | no special syntax required | | +--------------------+ | | | | | | | v v v | | TCL Script Python Script C++ Program | | (proc, expr, (def, if, for) (function, | | set, puts) cout) | | | | Key point: same pseudocode translates into ANY target language | +----------------------------------------------------------------------------------+
+----------------------------------------------------------------------------------+
| 2) FIVE RULES OF GOOD PSEUDOCODE |
| |
| Rule 1: BREAK TASKS INTO SUBTASKS |
| Each pseudocode line = one action |
| Large task --> smaller subtasks --> sub-subtasks --> code lines |
| |
| Rule 2: CAPITALIZE KEYWORDS |
| START END GET READ WRITE CALL DISPLAY |
| IF ELSE END IF WHILE UNTIL FOR RETURN |
| |
| Rule 3: USE INDENTATION TO SHOW HIERARCHY |
| Sequence: no indent needed |
| Selection (IF/ELSE): indent body one level |
| Loop (WHILE/FOR): indent body one level |
| |
| Rule 4: END MULTILINE STRUCTURES EXPLICITLY |
| END IF, END WHILE, END FOR --> clarity of block boundaries |
| |
| Rule 5: KEEP STATEMENTS LANGUAGE-INDEPENDENT |
| No TCL-specific syntax in pseudocode |
| Use natural language, not set x [expr { $a + $b }] |
+----------------------------------------------------------------------------------++----------------------------------------------------------------------------------+
| 3) STANDARD PSEUDOCODE STRUCTURE TEMPLATE |
| |
| START |
| GET user input |
| IF user input is valid |
| CALL process user input |
| DISPLAY processed user input |
| ELSE |
| DISPLAY invalid input message |
| END IF |
| END |
| |
| Mapping to TCL: |
| +--------------------+----------------------------------+ |
| | Pseudocode keyword | TCL equivalent | |
| +--------------------+----------------------------------+ |
| | GET | set varname [gets stdin] | |
| | IF ... ELSE END IF | if { cond } { } else { } | |
| | CALL proc | proc_name args | |
| | DISPLAY result | puts $result | |
| | WHILE ... END WHILE| while { cond } { body } | |
| | FOR i = 1 TO N | for {set i 1} {$i<=$N} {incr i} | |
| | RETURN value | return $value | |
| +--------------------+----------------------------------+ |
+----------------------------------------------------------------------------------++----------------------------------------------------------------------------------+ | 4) LEHMER ALGORITHM IN PSEUDOCODE | | Pseudo-random number generator using Mersenne prime modulus | | | | Constants: | | a = 16807 (= 7^5, multiplier, Lewis-Goodman-Miller 1969) | | m = 2147483647 (= 2^31 - 1, Mersenne prime modulus) | | | | FUNCTION Random (seed): | | | | | v | | temp = a * seed <-- scale seed by multiplier | | | | | v | | seed = temp - m * TRUNCATE(temp / m) <-- modular reduction | | | (equivalent to temp MOD m) | | v | | RETURN seed / m <-- normalize to float in (0.0, 1.0) | | | | Example: seed=12345 --> random output ~= 0.09661652850760917 | | Note: unlike TCL rand(), this proc requires a seed on every call | +----------------------------------------------------------------------------------+
+----------------------------------------------------------------------------------+
| 5) PSEUDOCODE --> TCL TRANSLATION (randomx proc) |
| |
| Pseudocode TCL code |
| +--------------------------+ +------------------------------------------+ |
| | const a = 16807.0 | | set a 16807.0 | |
| | const m = 2147483647.0 | | set m 2147483647.0 | |
| +--------------------------+ +------------------------------------------+ |
| | FUNCTION Random(seed) | | proc randomx {seed} { | |
| | temp = a * seed | | set temp [expr {$a * $seed}] | |
| | seed = temp - | | set seed [expr {$temp - | |
| | m * TRUNCATE(t/m) | | $m * int($temp / $m)}] | |
| | RETURN seed / m | | return [expr {$seed / $m}] | |
| | END FUNCTION | | } | |
| +--------------------------+ +------------------------------------------+ |
| |
| Important notes: |
| TCL expr uses double precision fp internally |
| Use real constants (16807.0 not 16807) to avoid integer arithmetic |
| TCL int() truncates toward zero ~= pseudocode TRUNCATE() |
+----------------------------------------------------------------------------------++----------------------------------------------------------------------------------+
| 6) PSEUDOCODE CHECKLIST FOR WIKI PAGE DEVELOPMENT |
| |
| Before coding: |
| [ ] define inputs: quantity1, quantity2, quantity3 |
| [ ] define expected output: quantity4 |
| [ ] state units: are outputs in compatible units? |
| [ ] apply rule of proportions where applicable (rule of three) |
| |
| Testcase planning: |
| [ ] testcase SMALL (near-zero or minimum inputs) |
| [ ] testcase MEDIUM (typical working range) |
| [ ] testcase GIANT (large or boundary inputs) |
| [ ] are there inputs too small or too large to solve? |
| |
| After coding: |
| [ ] check_answer: does (a + b) + c = a + (b + c)? (yes/no) |
| [ ] cross-check algorithm result vs expr { direct calculation } |
| [ ] note dependencies: Tcllib, recursion limits, external libraries |
| [ ] add comment lines for math operator notation used |
+----------------------------------------------------------------------------------++----------------------------------------------------------------------------------+ | 7) COMMON PITFALLS IN TCL PSEUDOCODE IMPLEMENTATION | | | | Pitfall 1: RECURSION DEPTH LIMITS | | One-line procedures with lengthy recursion --> degraded performance | | Pseudocode should note: "recursion depth may be limited" | | | | Pitfall 2: INTEGER vs FLOAT ARITHMETIC | | TCL math operators can switch modes unexpectedly | | Pseudocode note: "use real constants (16807.0 not 16807)" | | | | Pitfall 3: LIBRARY DEPENDENCIES | | Tcllib math::numtheory, simulation::random etc. reduce big-data cost ~1/3 | | Pseudocode should document: "requires package X" | | | | Pitfall 4: LANGUAGE-INDEPENDENT CONFUSION | | "Language-independent" = natural language, no compiler dependencies | | Does NOT mean: avoid human language entirely | | Clay tablet algorithms from Sumer Ur III qualify as language-independent | | | | Performance tip: | | math ops (::tcl::mathop) and Tcllib compiled routines | | outperform interpreted one-liners on big-data tasks | +----------------------------------------------------------------------------------+
+----------------------------------------------------------------------------------+ | 8) TCL WIKI PAGE DEVELOPMENT WORKFLOW (suggested method) | | | | Problem statement (natural language) | | | | | v | | Pseudocode outline | | (rules 1-5, language-independent) | | | | | v | | +------------------------------------+ | | | Auxiliary console deck | <-- proof features and subroutines | | | (no GUI, console show, puts) | before building GUI calculator | | +------------------+-----------------+ | | | | | +------------+-------------+ | | | | | | v v | | Testcases eTCL GUI calculator | | (small, medium, giant) (.frame entries, | | cross-check vs expr .buttons, reportx proc) | | | | | | v v | | TCL wiki format table console report | | (copy-paste ready) (copy-paste to wiki) | +----------------------------------------------------------------------------------+
David T. Ashley From wiki page on rand, D.A. recommends the recurrence. Reference the C. code definition for rand in TCL.
Draft. From this C. code snippet, the variable x is set to an initial seed value (e.g., 12345). The random number is generated by multiplying the seed value by 16807, taking the modulus division by 2147483647, and storing the result in the variable randx. This approach uses modulus division to ensure that the generated random number falls within a specific range. The modulus operator % in TCL returns the remainder of the division operation, which will be an integer value. """ Lehmer suggested that the (Mersenne) prime m = (2**31) - 1 might be an appropriate choice for the modulus. a = 7**5 = 16807 was first suggested by Lewis, Goodman and Miller in 1969 , based largely on the fact that j(z) = 168072 mod 2147483645 """" >>> ? But I am seeing a fraction from expr {rand} in TCL? <<<< In TCL, it's important to note that the rand function in TCL generates a random floating-point number between 0 and 1. If one needs an integer random number, one can multiply the result of rand by a suitable range and then convert it to an integer using the int function. This can help in generating integer random numbers within a desired range.
# ~~~~ C. code definition for rand
x = (16807 * x) MOD 2147483647
# C. code pronounced as “x mod y”. For example, 10 % 2 will be pronounced as ” Ten mod Two”.
# not sure C. code mod is exactly as TCL % or fmod?
# set a 2.9999383
# expr {fmod($a,1)} result 0.9999383000000002puts " Mersenne prime m = (2**31) - 1 [ expr { (2**31) - 1 } ]"
# 2147483647
puts " seven**5 = [ expr { 7**5 } ]"
# seven**5 = 16807# Pseudocode
# this is the "Lehmer" algorithm in Pseudocode
#
const a = 16807.0
const m = 2147483647.0
function Random(seed):
temp = a * seed
seed = temp - m * Truncate (temp / m)
return seed / m# tcl
# this is the "Lehmer" algorithm translated in TCL
#
# constants field
# real constants, not integer arithmetic?
# a = 7**5 = 16807
# Lehmer suggested that the
# Mersenne prime m = (2**31) - 1
set a 16807.0
set m 2147483647.0
# proc to generate random number
proc randomx {seed} {
set a 16807.0
set m 2147483647.0
set temp [expr {$a * $seed}]
set seed [expr {$temp - $m * int($temp / $m)}]
return [expr {$seed / $m}]
}
# Usage example
set seed 12345
set random_num [randomx $seed]
puts "Random number generated: $random_num"
# Random number generated: 0.09661652850760917
# Unlike rand in Tcl, this randomx procedure expects a seed value
# every time invoked. Proc is not defaulted to blank entry, though a default
# & entry error could be loaded up. Please include your wiki MONIKER and date in your comment with the same courtesy that I will give you. Thanks, gold 12Aug2020
test edit
Coding the Lehmer Pseudorandom Number Generator W. H. PAYNE, J. 1~. RABUNG, AND T. P. BOGYO Washington State University, Pullman, Washington An algorithm and coding technique is presented for quick evaluation of the Lehmer pseudo-random number generator modulo 2 ** 31 -- 1, a prime Mersenne number which produces 2 ** 31 -- 2 numbers, on a p-bit (greater than 31) computer. The computation method is extendible to limited problems in modular arithmetic. Prime factorization for 2 ** 61 -- 2 and a primitive root for 2 ** 61 -- 1, the next largest prime Mersenne number, are given for possible construction of a pseudo-random number generator of increased cycle length. KEY WORDS AND PHRASES: pseudo-random number, random number, modular arithmetic,
# pseudocode
function randomxxx():
m = 13
x = array of size m
a = 7
i = 0
c = 0
p = 1
temp = 0
x[1] = 1
for i = 1 to m-1:
x[i+1] = (a^i * x[1]) mod m
print x
p = 1
temp = a
while temp != 1:
p = p + 1
temp = (a * temp) mod m| Category Numerical Analysis | Category Toys | Category Calculator | Category Mathematics | Category Example | Toys and Games | Category Games | Category Application | Category GUI |