Word wrap: Difference between revisions

Line 151:

| has seen so much, was astonished whenever

| it shone in her face.

</pre>

=={{header|REXX}}==

The input for this program is in a file (named LAWS.TXT).

<br>The default width of the output is ½ of the current terminal width, or

<br>if the terminal width is indeterminable, then 40 is used.

<br>If the specified width is negative, then the output is shown justified (with the absolute value of width).

/*REXX pgm reads a file and displays it (with word wrap to the screen). */

parse arg width fileID .; if fileID='' then fileID='LAWS.TXT'

if width=='' then width=linesize()%2; if width==0 then width=40

if \datatype(width,'W') then call err "WIDTH (1st arg) isn't an integer."

txt=; $=; justify=width<0; width=abs(width)

do j=0 while lines(fileID)\==0 /*read from until until E-O-F. */

txt=txt linein(fileID)

end

txt=space(txt)

if j==0 then call err 'file' fileID "not found."

if txt=='' then call err 'file' fileID "is empty."

do k=1 for words(txt)

x=word(txt,k)

_=$ x

if length(_)>width then call tell

$=_

end

if $\=='' then call tell /*handle any residual words. */

exit

tell: if justify then say justify($,width)

else say strip($)

_=x

return

err: say; say '***error!***'; say; say arg(1); say; say arg(1);say;exit 13

</lang>

The input file:

────────── Computer programming laws ──────────

The Primal Scenario -or- Basic Datum of Experience:

∙ Systems in general work poorly or not at all.

∙ Nothing complicated works.

∙ Complicated systems seldom exceed 5% efficiency.

∙ There is always a fly in the ointment.

The Fundamental Theorem:

∙ New systems generate new problems.

Occam's Razor:

∙ Systems should not be unnecessarily multiplied.

The Law of Conservation of Energy:

∙ The total amount of energy in the universe is constant.

∙ Systems operate by redistributing energy into different forms and into accumulations of different sizes.

Laws of Growth:

∙ Systems tend to grow, and as they grow, they encroach.

The Big-Bang Theorem of Systems-Cosmology:

∙ Systems tend to expand to fill the known universe.

Parkinson's Extended Law:

∙ The system itself tends to expand at 5-6% per annum.

The Generalized Uncertainty Principle:

∙ Systems display antics.

∙ Complicated systems produce unexpected outcomes.

∙ The total behavior of large systems cannot be predicted.

The Non-Addivity Theorem of Systems-Behavior -or- Climax Design Theorem:

∙ A large system, produced by expanding the dimensions of a smaller system, does not behave like the smaller system.

LeChateliers's Principle:

∙ Complex systems tend to oppose their own proper function.

∙ Systems get in the way.

∙ The system always kicks back.

∙ Positive feedback is dangerous.

Functionary's Falsity:

∙ People in systems do not do what the system says they are doing.

∙ The function performed by a system is not operationally identical to the function of the same name performed by a man.

∙ A function performed by a larger system is not operationally identical to the function of the same name performed by a smaller system.

The Fundamental Law of Administrative Workings:

∙ Things are what they are reported to be.

∙ The real world is whatever is reported to the system.

∙ If it isn't official; it didn't happen.

∙ If it's made in Detriot, it must be an automobile.

∙ A system is no better than its sensory organs.

∙ To those within a system, the outside reality tends to pale and disappear.

∙ Systems attract systems-people.

∙ For every human system, there is a type of person adapted to thrive on it or in it.

∙ The bigger the system, the narrower and more specialized the interface with individuals.

Administrator's Anxiety:

∙ Pushing on the systems doesn't help. It just makes things worse.

∙ A complex system cannot be "made" to work. It either works or it doesn't.

∙ A simple system, designed from scratch, sometimes works.

∙ A simple system may or may not work.

∙ Some complex systems actually work.

∙ If a system is working, leave it alone.

∙ A complex system that works is invariably found to have evolved from a simple system that works.

∙ A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working simple system.

∙ Programs never run the first time.

∙ Complex programs never run.

∙ Anything worth doing once will probably have to be done twice.

The Functional indeterminancy Theorem:

∙ In complex systems, malfunction and even total nonfunction may not be detectable for long periods, if ever.

The Kantian Hypothesis -or- Know-Nothing Theorem:

∙ Large complex systems are beyond human capacity to evaluate.

The Newtonian Lay of Systems-Inertia:

∙ A system that performs a certain way will continue to operate in that way regardless of the need of of changed conditions.

∙ A system continues to do its thing, regardless of need.

∙ Systems develop goals of their own the instant they come into being.

∙ Intrasystem goals come first.

Failure-Mode Theorems:

∙ Complex systems usually operate in failure mode.

∙ A complex system can fail in a infinite number of ways.

∙ If anything can go wrong, it will.

∙ The mode of failure of a complex system cannot ordinarily be predicted from its structure.

∙ The crucial variables are discovered by accident.

∙ The larger the system, the greater the probability of unexpected failure.

∙ "Success" or "function" in any system may be failure in the larger or smaller systems to which the system is connected.

∙ In setting up a new system, tread softly. You may be disturbing another system that is actually working.

The Fail-Safe Theorem:

∙ When a fail-safe system fails, it fails by failing to fail safe.

∙ Complex systems tend to produce complex responses (not solutions) to problems.

∙ Great advances are not produced by systems designed to produce great advances.

∙ Loose systems last longer and work better.

∙ Efficient systems are dangerous to themselves and to others.

The Vector Theory of Systems:

∙ Systems run better when designed to run downhill.

∙ Systems aligned with human motivational vectors will sometimes work. Systems opposing such vectors work poorly or not at all.

Advanced Systems Theories:

∙ Everything is a system.

∙ Everything is a part of a larger system.

∙ The universe is infinitely systematized, both upward [larger systems] and downward [smaller systems].

∙ All systems are infinitely complex. (The illusion of simplicity comes from focusing attention on one or a few variables.)

∙ Parameters are variables travelling under an assumed name.

</pre>

Output when specifying: <tt> 155 </tt>

────────── Computer programming laws ────────── The Primal Scenario -or- Basic Datum of Experience: ∙ Systems in general work poorly or not at all. ∙

Nothing complicated works. ∙ Complicated systems seldom exceed 5% efficiency. ∙ There is always a fly in the ointment. The Fundamental Theorem: ∙ New

systems generate new problems. Occam's Razor: ∙ Systems should not be unnecessarily multiplied. The Law of Conservation of Energy: ∙ The total amount of

energy in the universe is constant. ∙ Systems operate by redistributing energy into different forms and into accumulations of different sizes. Laws of

Growth: ∙ Systems tend to grow, and as they grow, they encroach. The Big-Bang Theorem of Systems-Cosmology: ∙ Systems tend to expand to fill the known

universe. Parkinson's Extended Law: ∙ The system itself tends to expand at 5-6% per annum. The Generalized Uncertainty Principle: ∙ Systems display antics.

∙ Complicated systems produce unexpected outcomes. ∙ The total behavior of large systems cannot be predicted. The Non-Addivity Theorem of Systems-Behavior

-or- Climax Design Theorem: ∙ A large system, produced by expanding the dimensions of a smaller system, does not behave like the smaller system.

LeChateliers's Principle: ∙ Complex systems tend to oppose their own proper function. ∙ Systems get in the way. ∙ The system always kicks back. ∙ Positive

feedback is dangerous. Functionary's Falsity: ∙ People in systems do not do what the system says they are doing. ∙ The function performed by a system is

not operationally identical to the function of the same name performed by a man. ∙ A function performed by a larger system is not operationally identical

to the function of the same name performed by a smaller system. The Fundamental Law of Administrative Workings: ∙ Things are what they are reported to be.

∙ The real world is whatever is reported to the system. ∙ If it isn't official; it didn't happen. ∙ If it's made in Detriot, it must be an automobile. ∙ A

system is no better than its sensory organs. ∙ To those within a system, the outside reality tends to pale and disappear. ∙ Systems attract systems-people.

∙ For every human system, there is a type of person adapted to thrive on it or in it. ∙ The bigger the system, the narrower and more specialized the

interface with individuals. Administrator's Anxiety: ∙ Pushing on the systems doesn't help. It just makes things worse. ∙ A complex system cannot be "made"

to work. It either works or it doesn't. ∙ A simple system, designed from scratch, sometimes works. ∙ A simple system may or may not work. ∙ Some complex

systems actually work. ∙ If a system is working, leave it alone. ∙ A complex system that works is invariably found to have evolved from a simple system

that works. ∙ A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working

simple system. ∙ Programs never run the first time. ∙ Complex programs never run. ∙ Anything worth doing once will probably have to be done twice. The

Functional indeterminancy Theorem: ∙ In complex systems, malfunction and even total nonfunction may not be detectable for long periods, if ever. The

Kantian Hypothesis -or- Know-Nothing Theorem: ∙ Large complex systems are beyond human capacity to evaluate. The Newtonian Lay of Systems-Inertia: ∙ A

system that performs a certain way will continue to operate in that way regardless of the need of of changed conditions. ∙ A system continues to do its

thing, regardless of need. ∙ Systems develop goals of their own the instant they come into being. ∙ Intrasystem goals come first. Failure-Mode Theorems: ∙

Complex systems usually operate in failure mode. ∙ A complex system can fail in a infinite number of ways. ∙ If anything can go wrong, it will. ∙ The mode

of failure of a complex system cannot ordinarily be predicted from its structure. ∙ The crucial variables are discovered by accident. ∙ The larger the

system, the greater the probability of unexpected failure. ∙ "Success" or "function" in any system may be failure in the larger or smaller systems to which

the system is connected. ∙ In setting up a new system, tread softly. You may be disturbing another system that is actually working. The Fail-Safe Theorem:

∙ When a fail-safe system fails, it fails by failing to fail safe. ∙ Complex systems tend to produce complex responses (not solutions) to problems. ∙ Great

advances are not produced by systems designed to produce great advances. ∙ Loose systems last longer and work better. ∙ Efficient systems are dangerous to

themselves and to others. The Vector Theory of Systems: ∙ Systems run better when designed to run downhill. ∙ Systems aligned with human motivational

vectors will sometimes work. Systems opposing such vectors work poorly or not at all. Advanced Systems Theories: ∙ Everything is a system. ∙ Everything is

a part of a larger system. ∙ The universe is infinitely systematized, both upward [larger systems] and downward [smaller systems]. ∙ All systems are

infinitely complex. (The illusion of simplicity comes from focusing attention on one or a few variables.) ∙ Parameters are variables travelling under an

assumed name.

</pre>

Output when specifying: <tt> 76 </tt>

────────── Computer programming laws ────────── The Primal Scenario -or-

Basic Datum of Experience: ∙ Systems in general work poorly or not at all.

∙ Nothing complicated works. ∙ Complicated systems seldom exceed 5%

efficiency. ∙ There is always a fly in the ointment. The Fundamental

Theorem: ∙ New systems generate new problems. Occam's Razor: ∙ Systems

should not be unnecessarily multiplied. The Law of Conservation of Energy:

∙ The total amount of energy in the universe is constant. ∙ Systems operate

by redistributing energy into different forms and into accumulations of

different sizes. Laws of Growth: ∙ Systems tend to grow, and as they grow,

they encroach. The Big-Bang Theorem of Systems-Cosmology: ∙ Systems tend to

expand to fill the known universe. Parkinson's Extended Law: ∙ The system

itself tends to expand at 5-6% per annum. The Generalized Uncertainty

Principle: ∙ Systems display antics. ∙ Complicated systems produce

unexpected outcomes. ∙ The total behavior of large systems cannot be

predicted. The Non-Addivity Theorem of Systems-Behavior -or- Climax Design

Theorem: ∙ A large system, produced by expanding the dimensions of a

smaller system, does not behave like the smaller system. LeChateliers's

Principle: ∙ Complex systems tend to oppose their own proper function. ∙

Systems get in the way. ∙ The system always kicks back. ∙ Positive feedback

is dangerous. Functionary's Falsity: ∙ People in systems do not do what the

system says they are doing. ∙ The function performed by a system is not

operationally identical to the function of the same name performed by a

man. ∙ A function performed by a larger system is not operationally

identical to the function of the same name performed by a smaller system.

The Fundamental Law of Administrative Workings: ∙ Things are what they are

reported to be. ∙ The real world is whatever is reported to the system. ∙

If it isn't official; it didn't happen. ∙ If it's made in Detriot, it must

be an automobile. ∙ A system is no better than its sensory organs. ∙ To

those within a system, the outside reality tends to pale and disappear. ∙

Systems attract systems-people. ∙ For every human system, there is a type

of person adapted to thrive on it or in it. ∙ The bigger the system, the

narrower and more specialized the interface with individuals.

Administrator's Anxiety: ∙ Pushing on the systems doesn't help. It just

makes things worse. ∙ A complex system cannot be "made" to work. It either

works or it doesn't. ∙ A simple system, designed from scratch, sometimes

works. ∙ A simple system may or may not work. ∙ Some complex systems

actually work. ∙ If a system is working, leave it alone. ∙ A complex system

that works is invariably found to have evolved from a simple system that

works. ∙ A complex system designed from scratch never works and cannot be

patched up to make it work. You have to start over, beginning with a

working simple system. ∙ Programs never run the first time. ∙ Complex

programs never run. ∙ Anything worth doing once will probably have to be

done twice. The Functional indeterminancy Theorem: ∙ In complex systems,

malfunction and even total nonfunction may not be detectable for long

periods, if ever. The Kantian Hypothesis -or- Know-Nothing Theorem: ∙ Large

complex systems are beyond human capacity to evaluate. The Newtonian Lay of

Systems-Inertia: ∙ A system that performs a certain way will continue to

operate in that way regardless of the need of of changed conditions. ∙ A

system continues to do its thing, regardless of need. ∙ Systems develop

goals of their own the instant they come into being. ∙ Intrasystem goals

come first. Failure-Mode Theorems: ∙ Complex systems usually operate in

failure mode. ∙ A complex system can fail in a infinite number of ways. ∙

If anything can go wrong, it will. ∙ The mode of failure of a complex

system cannot ordinarily be predicted from its structure. ∙ The crucial

variables are discovered by accident. ∙ The larger the system, the greater

the probability of unexpected failure. ∙ "Success" or "function" in any

system may be failure in the larger or smaller systems to which the system

is connected. ∙ In setting up a new system, tread softly. You may be

disturbing another system that is actually working. The Fail-Safe Theorem:

∙ When a fail-safe system fails, it fails by failing to fail safe. ∙

Complex systems tend to produce complex responses (not solutions) to

problems. ∙ Great advances are not produced by systems designed to produce

great advances. ∙ Loose systems last longer and work better. ∙ Efficient

systems are dangerous to themselves and to others. The Vector Theory of

Systems: ∙ Systems run better when designed to run downhill. ∙ Systems

aligned with human motivational vectors will sometimes work. Systems

opposing such vectors work poorly or not at all. Advanced Systems Theories:

∙ Everything is a system. ∙ Everything is a part of a larger system. ∙ The

universe is infinitely systematized, both upward [larger systems] and

downward [smaller systems]. ∙ All systems are infinitely complex. (The

illusion of simplicity comes from focusing attention on one or a few

variables.) ∙ Parameters are variables travelling under an assumed name.

</pre>

Output [justified] when specifying: <tt> -70 </tt>

────────── Computer programming laws ────────── The Primal Scenario

-or- Basic Datum of Experience: ∙ Systems in general work poorly or

not at all. ∙ Nothing complicated works. ∙ Complicated systems seldom

exceed 5% efficiency. ∙ There is always a fly in the ointment. The

Fundamental Theorem: ∙ New systems generate new problems. Occam's

Razor: ∙ Systems should not be unnecessarily multiplied. The Law of

Conservation of Energy: ∙ The total amount of energy in the universe

is constant. ∙ Systems operate by redistributing energy into different

forms and into accumulations of different sizes. Laws of Growth: ∙

Systems tend to grow, and as they grow, they encroach. The Big-Bang

Theorem of Systems-Cosmology: ∙ Systems tend to expand to fill the

known universe. Parkinson's Extended Law: ∙ The system itself tends to

expand at 5-6% per annum. The Generalized Uncertainty Principle: ∙

Systems display antics. ∙ Complicated systems produce unexpected

outcomes. ∙ The total behavior of large systems cannot be predicted.

The Non-Addivity Theorem of Systems-Behavior -or- Climax Design

Theorem: ∙ A large system, produced by expanding the dimensions of a

smaller system, does not behave like the smaller system.

LeChateliers's Principle: ∙ Complex systems tend to oppose their own

proper function. ∙ Systems get in the way. ∙ The system always kicks

back. ∙ Positive feedback is dangerous. Functionary's Falsity: ∙

People in systems do not do what the system says they are doing. ∙ The

function performed by a system is not operationally identical to the

function of the same name performed by a man. ∙ A function performed

by a larger system is not operationally identical to the function of

the same name performed by a smaller system. The Fundamental Law of

Administrative Workings: ∙ Things are what they are reported to be. ∙

The real world is whatever is reported to the system. ∙ If it isn't

official; it didn't happen. ∙ If it's made in Detriot, it must be an

automobile. ∙ A system is no better than its sensory organs. ∙ To

those within a system, the outside reality tends to pale and

disappear. ∙ Systems attract systems-people. ∙ For every human system,

there is a type of person adapted to thrive on it or in it. ∙ The

bigger the system, the narrower and more specialized the interface

with individuals. Administrator's Anxiety: ∙ Pushing on the systems

doesn't help. It just makes things worse. ∙ A complex system cannot be

"made" to work. It either works or it doesn't. ∙ A simple system,

designed from scratch, sometimes works. ∙ A simple system may or may

not work. ∙ Some complex systems actually work. ∙ If a system is

working, leave it alone. ∙ A complex system that works is invariably

found to have evolved from a simple system that works. ∙ A complex

system designed from scratch never works and cannot be patched up to

make it work. You have to start over, beginning with a working simple

system. ∙ Programs never run the first time. ∙ Complex programs never

run. ∙ Anything worth doing once will probably have to be done twice.

The Functional indeterminancy Theorem: ∙ In complex systems,

malfunction and even total nonfunction may not be detectable for long

periods, if ever. The Kantian Hypothesis -or- Know-Nothing Theorem: ∙

Large complex systems are beyond human capacity to evaluate. The

Newtonian Lay of Systems-Inertia: ∙ A system that performs a certain

way will continue to operate in that way regardless of the need of of

changed conditions. ∙ A system continues to do its thing, regardless

of need. ∙ Systems develop goals of their own the instant they come

into being. ∙ Intrasystem goals come first. Failure-Mode Theorems: ∙

Complex systems usually operate in failure mode. ∙ A complex system

can fail in a infinite number of ways. ∙ If anything can go wrong, it

will. ∙ The mode of failure of a complex system cannot ordinarily be

predicted from its structure. ∙ The crucial variables are discovered

by accident. ∙ The larger the system, the greater the probability of

unexpected failure. ∙ "Success" or "function" in any system may be

failure in the larger or smaller systems to which the system is

connected. ∙ In setting up a new system, tread softly. You may be

disturbing another system that is actually working. The Fail-Safe

Theorem: ∙ When a fail-safe system fails, it fails by failing to fail

safe. ∙ Complex systems tend to produce complex responses (not

solutions) to problems. ∙ Great advances are not produced by systems

designed to produce great advances. ∙ Loose systems last longer and

work better. ∙ Efficient systems are dangerous to themselves and to

others. The Vector Theory of Systems: ∙ Systems run better when

designed to run downhill. ∙ Systems aligned with human motivational

vectors will sometimes work. Systems opposing such vectors work poorly

or not at all. Advanced Systems Theories: ∙ Everything is a system. ∙

Everything is a part of a larger system. ∙ The universe is infinitely

systematized, both upward [larger systems] and downward [smaller

systems]. ∙ All systems are infinitely complex. (The illusion of

simplicity comes from focusing attention on one or a few variables.) ∙

Parameters are variables travelling under an assumed name.

</pre>