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More of my philosophy about: Is software engineers really engineers?
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Amine Moulay Ramdane
Jan 19, 2021, 4:41:41 PM1/19/21
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Hello...
More of my philosophy about: Is software engineers really engineers?
I am a white arab and i think i am smart since i have also invented many
scalable algorithms and algorithms..
I have just read the following article about: Is software engineers really engineers ?, i invite you to read it:
Are we really engineers ?
https://www.hillelwayne.com/post/crossover-project/are-we-really-engineers/
I think the above article is lacking, because i think that what makes
the difference between software engineering and other engineering disciplines is not only that software engineering uses discrete
math, but it uses Logic(Formal Logic and such) that has been called "the calculus of computer science". The argument is that logic plays a fundamental role in computer science, similar to that played by calculus in the physical sciences and traditional engineering disciplines. Indeed, logic plays an important role in areas of Computer Science as disparate as artificial intelligence (automated reasoning), architecture (logic gates), software engineering (specification and verification), programming languages (semantics, logic programming), databases (relational algebra and SQL), algorithms (complexity and expressiveness), and theory of computation (general notions of computability).
This is why you are seeing me using my smartness of my fluid intelligence using a sophisticated Logic to find patterns and also proving, and here is some of my thoughts and notice how i am finding patterns and proving with my fluid intelligence:
More precision about capitalism and about National Vanguard..
I will be more rigorous, so read again:
I have just read the following article from a white supremacist website called National Vanguard:
Why Capitalism Fails
https://nationalvanguard.org/2015/07/why-capitalism-fails/
And it is saying the following about why capitalism fails:
"Capitalism permits inheritance, the command transfer of private property to a esignated new owner upon the death of the previous owner. And therein is the flaw: inherited wealth isn’t earned by its owner, yet it leads to a class segregation of men that has nothing to do with how much wealth they have earned; i.e., nothing to do with how much or how well or how significantly they have worked."
I am a white arab and i think i am smart since i have invented many scalable algorithms, and i will answer with my fluid intelligence: I think the above article is not taking into account the risk factor and and the smartness factor, so there have to be mechanisms, that are like engines, that "encourage" to or/and "make" a part of the people work by taking risks or great risks and by doing there best (so that to become rich) or/and that "encourage" to or/and "make" the smartest to give there best with there smartness (so that to become rich), so i think capitalism has those mechanisms in form of rewards by allowing to become "rich" and in form of rewards by allowing inheritance, the command transfer of private property to a designated new owner upon the death of the previous owner: Since it "encourages" to or/and "makes" a part of the people work by taking risks and by doing there best (so that to become rich) or/and it encourages to or/and makes the smartest give there best with there smartness (so that to become rich).
And notice that i am also defining taking a "risk" as working "hard".
And the above article is saying the following:
"Capitalism constantly looks for ways to reduce labor costs. Automation made human labor less necessary than it had been when capitalism first appeared. When automation did appear, people who had the talent, the skills, and the motivation to make contributions began to find no jobs, or to become uncompetitive with mass-production if they tried to employ themselves."
I think it is not true, because read the following:
https://singularityhub.com/2019/01/01/ai-will-create-millions-more-jobs-than-it-will-destroy-heres-how/
And read the following:
Here is the advantages and disadvantages of automation:
Following are some of the advantages of automation:
1. Automation is the key to the shorter workweek. Automation will allow
the average number of working hours per week to continue to decline,
thereby allowing greater leisure hours and a higher quality life.
2. Automation brings safer working conditions for the worker. Since
there is less direct physical participation by the worker in the
production process, there is less chance of personal injury to the worker.
3. Automated production results in lower prices and better products. It
has been estimated that the cost to machine one unit of product by
conventional general-purpose machine tools requiring human operators may
be 100 times the cost of manufacturing the same unit using automated
mass-production techniques. The electronics industry offers many
examples of improvements in manufacturing technology that have
significantly reduced costs while increasing product value (e.g., colour
TV sets, stereo equipment, calculators, and computers).
4. The growth of the automation industry will itself provide employment
opportunities. This has been especially true in the computer industry,
as the companies in this industry have grown (IBM, Digital Equipment
Corp., Honeywell, etc.), new jobs have been created.
These new jobs include not only workers directly employed by these
companies, but also computer programmers, systems engineers, and other
needed to use and operate the computers.
5. Automation is the only means of increasing standard of living. Only
through productivity increases brought about by new automated methods of
production, it is possible to advance standard of living. Granting wage
increases without a commensurate increase in productivity
will results in inflation. To afford a better society, it is a must to
increase productivity.
Following are some of the disadvantages of automation:
1. Automation will result in the subjugation of the human being by a
machine. Automation tends to transfer the skill required to perform work
from human operators to machines. In so doing, it reduces the need for
skilled labour. The manual work left by automation requires lower skill
levels and tends to involve rather menial tasks (e.g., loading and
unloading workpart, changing tools, removing chips, etc.). In this
sense, automation tends to downgrade factory work.
2. There will be a reduction in the labour force, with resulting
unemployment. It is logical to argue that the immediate effect of
automation will be to reduce the need for human labour, thus displacing
workers.
3. Automation will reduce purchasing power. As machines replace workers
and these workers join the unemployment ranks, they will not receive the
wages necessary to buy the products brought by automation. Markets will
become saturated with products that people cannot afford to purchase.
Inventories will grow. Production will stop. Unemployment will reach
epidemic proportions and the result will be a massive economic depression.
And to know more about economy and capitalism, please read my following thoughts:
https://groups.google.com/forum/#!topic/alt.culture.morocco/wlJu5j1xhPk
And more political philosophy about the good taste..
So let us look in the dictionary at what is the taste, it says the following:
"The taste is the sense by which the qualities and flavour of a substance are distinguished by the taste buds."
Read here in the dictionary to notice it:
https://www.collinsdictionary.com/dictionary/english/taste
But when you are smart you will also notice that there is also the intellectual taste from culture or genetics, i mean that when you are genetically more rational and more smart you will notice that this more rational and more smart is also intellectual taste since with it you are able to be more efficiently selective of your knowledge, so it permits you to enhance quality, and this is also the same for culture, i mean when you enhance more your culture it enhances your intellectual taste and it permits you to be more efficiently selective of your knowledge, so it permits you to enhance quality.
So as you are noticing that the intellectual taste is so important..
And you have to also know that i am also doing political philosophy by efficiently finding the patterns with my smartness, i give you an example, look at the following pattern that i am finding with my smartness:
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More explanation about the rule of "work smart and not hard"..
I will be more logically rigorous and explain more, so read my logical proof:
I have just looked at the following video, i invite you to look at it:
People who say "work smart not hard" pretty much always fail | James Gosling and Lex Fridman
https://www.youtube.com/watch?v=Jaho2mbaVGM&t=99s
Here is James Gosling:
https://en.wikipedia.org/wiki/James_Gosling
And here is Lex Fridman:
https://lexfridman.com/#:~:text=Lex%20Fridman%3A%20I'm%20an,Teaching%3A%20deeplearning.mit.edu
I think i am a white arab that is smart since i have invented many scalable algorithms and i say that Lex Fridman and James Gosling in the above video are not smart by saying that "work smart and not hard" pretty much always fail, and notice that Lex Fridman says that
the "not hard" in the rule means lazy, but this is not logically correct, since if the statistical distribution of the strenght and force of the work is normal in the real world , so i have to discern with my fluid intelligence that it is a system that means "work smart and not hard" and it can mean: "work smart and using an average force or strenght", so then it means that this system or rule doesn't pretty much always fail, also we can generalize and say: since the truth of "work smart and not hard pretty much always fail" depends on the statistical distribution(of the strenght and force of the work) in the real world, so we can not generalize and say that the rule of "work smart and not hard" pretty much always fail.
--
I give you another example, look at the following patterns that i am finding with my smartness:
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What is it to be smart ?
Read my following thoughts:
I am a white arab, and i think i am smart since i have invented many scalable algorithms and there implementations, and today i will speak about what is it to be "smart"..
So i will start it by inviting you to read carefully the following webpage from a Senior Consultant (and former Editor-in-Chief and Publishing Director) of New Scientist and Author of After the Ice:
Why are humans smarter than other animals?
https://www.edge.org/response-detail/12021
So as you are noticing he is saying the following:
--
"The idea of human superiority should have died when Darwin came on the scene.
Unfortunately, the full implications of what he said have been difficult to take in: there is no Great Chain of Being, no higher and no lower. All creatures have adapted effectively to their own environments in their own way. Human "smartness" is just a particular survival strategy among many others, not the top of a long ladder. It took a surprisingly long time for scientists to grasp this. For decades, comparative psychologists tried to work out the learning abilities of different species so that they could be arranged on a single scale. Animal equivalents of intelligence tests were used and people seriously asked whether fish were smarter than birds. It took the new science of ethology, created by Nobel-prize winners Konrad Lorenz, Niko Tinbergen and Karl von Frisch, to show that each species had the abilities it needed for its own lifestyle and they could not be not arranged on a universal scale. Human smartness is no smarter than anyone else's smartness. The question should have died for good."
--
So i think i am smart and say that the above webpage is not so smart, because the logical reasoning defect is that he is first saying the following:
"Human "smartness" is just a particular survival strategy"
This is the first logical defect, since he is like using boolean logic by saying that human smartness is only a particular survival strategy, and this is not correct logical reasoning, because we have like to be fuzzy logic and say that not all humans are using smartness for only survival, since we are not like animals, since we have not to think it only societally, but we can also say there is a great proportion of humans that have transcended there "survival" condition with there smartness to be a much better human condition than only survival. So now we can say with human smartness (and measure it with human smartness) that the humans that have transcended there "survival" condition with there smartness to be a much better human condition have a much superior smartness than animals, since we can measure it with human smartness, and here is the definition of surviving in the dictionary:
https://www.dictionary.com/browse/survive
So as you are noticing that survival is only to remain alive, so i am logical in my thoughts above.
The second logical defect of the above webpage is the following:
Notice that the above webpage that he is saying the following:
"Strangley enough, even evolutionary biologists still get caught up with the notion that humans stand at the apex of existence. There are endless books from evolutionary biologists speculating on the reasons why humans evolved such wonderful big brains, but a complete absence of those which ask if a big brains is a really useful organ to have. The evidence is far from persuasive. If you look at a wide range of organisms, those with bigger brains are generally no more successful than those with smaller brains — hey go extinct just as fast."
So i think that the above webpage is not right.
So notice again that he is saying that the brain must be successful in survival, and this is not correct reasoning, since as i said above smartness is not only about survival, since we have to measure it with our smartness and notice that from also my above thoughts that we can be humans that are much more smart than animals even if we go extinct.
So the important thing to notice in my above logical reasoning , is that you have to measure smartness with smartness, it is the same as my following logical proof about: Is beauty universal ? , here it is , read it carefully:
I will make you understand with smartness what about the following webpage:
Look at the following webpage from BBC:
The myth of universal beauty
https://www.bbc.com/future/article/20150622-the-myth-of-universal-beauty
So notice in the above webpage that it is saying the following about beauty:
"Where starvation is a risk, heavier weight is more attractive"
So you have to understand that the above webpage from BBC is not smart, i will make you understand with smartness that beauty is universal, so if we take the following sentence of the above webpage:
"Where starvation is a risk, heavier weight is more attractive"
So you have to put it in the context of the above webpage, and understand that the way of thinking of the webpage from BBC is not smart, because it is saying that since in the above sentence starvation is a risk , so heavier weight can be more attractive, but this can be heavier weight that is not beautiful for the eyes, so it makes a conclusion that universal beauty is not universal, but this is not smart because we have not to measure beautifulness with only our eyes and say that heavier weight that is not beautiful for the eyes is not beautiful, because we have to measure it with smartness and say that smartness says that in the above sentence that heavier weight that is not beautiful for the eyes is beautiful for smartness because starvation is a risk, so then with smartness we can say that beauty is universal. So we have to know that that the system of reference of measure is very important, by logical analogy we can say that measuring beautifulness with the eyes is like measuring individual smartness with only genetics, but measuring beautifulness with both the eyes and smartness is like measuring individual smartness with both the genetical and the cultural.
About more philosophy about smartness..
You will think that smartness is much more genetical, but this is a big mistake, since i think i am smart and i will explain:
If you want to climb a big mountain, there is two ways:
You can climb the big mountain or you can make the big mountain small in height so that to climb it, so when you are smart you will take a look at the constraints that make smartness much less expressive, and those constraints that make smartness much less expressive is like making the mountain small in height so that to climb it. Read more my following thoughts to understand:
More philosophy about smartness and abstraction and complexity..
So i will start by asking a question:
Is the way of learning by abstraction an efficient way ?
So when you are smart you will quickly notice that we have to take into account the "context" of the way of learning by abstraction, and when you are smart you will notice that the way of learning by abstraction is also to reduce complexity, but when you take into account the context you will notice that learning by abstraction is a also a "specialization" and it is also an efficient way of learning when we measure it inside the "context" of abstraction that is the reality, so then we have not to be pessimistic about learning by the efficient way of abstraction since, first, it reduces the complexity and, second, even if we are not understanding the complexity behind the abstraction, learning by abstraction is also an efficient specialization that is efficient for adaptability, so we have to know how to balance between those that are required to understand the complexity behind the abstraction and those that are required to learn by the way of abstraction that is a specialization.
More philosophy about the way of learning by abstraction..
I will give you an example so that you understand, so if you ask what is the way of learning by abstraction, look at my following tutorial where i am presenting my methodology that, first, permits to model the synchronization primitives of parallel programs with logic primitives with If-then-OR-AND so that to make it easy to translate to petri nets so that to detect deadlocks in parallel programs, please take a look at it because this tutorial of mine is the way of learning by abstraction:
How to analyse parallel applications with Petri Nets
https://sites.google.com/site/scalable68/how-to-analyse-parallel-applications-with-petri-nets
I think i am smart and i will explain more what is smartness..
So that you understand me more, let us say that you are measuring a human IQ, so if it is high human IQ , this value is a measure that is relative to the other human IQs, so you will say that this high IQ is much better at adaptability than the other humans, but it is not correct measure, because even science and technology have constraints that constrain(or limit greatly) the expressiveness of human IQs, so then we can not say that a high human IQ is better at adaptability than the other humans..
More philosophy about how to measure human IQ or human smartness..
I think i am smart, and i will talk about how to measure human IQs or human smartness, first you have to know that you can measure relatively or absolutely, so if you measure the IQ of a human, you will give a value of IQ that is "relative" to the distribution of IQs of humans, so can we ask if it is the right way to measure human IQs? i think it is not, because there is a "very" important thing that is missing, and it is that you have to also measure IQ or smartness relatively to the "constraints" in our reality that constrain(or limit) human IQ or human smartness, and i think this will give a much more realistic measure of human IQs or human smartness, so if you are really smart you will start by searching what are those constraints in the reality that constrain human IQs or human smartness, because this way you will become really smart.
Let me give an example about how to measure IQs or smartness..
So if you are really smart you will give a smart example so that people can understand, so here it is:
If i say: 2 + 2 = 4
So you will notice that this equality is also constrained by constraints of reality, since for example you are noticing that it is not so mathematically expressive, so this not mathematically expressive is also constraining human IQ or human smartness, since if you understand and learn this mathematical equality, another person will quickly do the same, so the other person will adapt quickly to this level of smartness, so now you are noticing the smart idea, it is that even science and technology are constrained the same way, and this constraints on science and technology constrain or limit the expressiveness of high human IQs or high level of smartness so that other lower level human IQs or smartness can attain the level of adaptability of high human IQs, this is what is happening in our today world, and if you are smart you will notice that there is something else that is happening and it is that abstraction of complexity that reduce the complexity is making others not understanding the complexity behind the abstraction and this is not so efficient.
Here is more about the constraints on science and technology:
Is Science Going To End?
Read more here:
https://philosophynow.org/issues/68/Is_Science_Going_To_End
And read also the following
The Industrial Era Ended, and So Will the Digital Era
Read more here:
https://hbr.org/2018/07/the-industrial-era-ended-and-so-will-the-digital-era
More political philosophy about what is smartness..
I give you an example so that you understand:
If i give the following three words:
I, love, you.
It is not the same as if i give the following five words:
I, love, you, very, much
So you are noticing that the five words permit a more sophisticated expressiveness, and notice that i am saying more sophisticated, since the five words bring more efficiency, and this bringing more efficiency is also what we call smartness, but notice that this smartness is brought by using the "tool" that is composed of the five words, so the tool that is our english language brings smartness, so then we have to be convinced by the fact that the tool like internet brings a much more efficiency and this much more efficiency brings much more smartness, so now you are noticing that smartness is not only genetical or cultural, but it is also the smartness of using the tool, and this is a very important thing, since the tool can be powerful and it can advance very much a human and can make a human really smart. So you have to understand that we are also in an Era of powerful tools such as internet that can advance very much a human and that can make a human really smart.
And now i will ask a philosophical question:
How to manage efficiently complexity ?
I think you can manage complexity by the “divide and rule” approach
to management, which also leads to hierarchical division of large organisations, or wich also leads to the Division of "labour", you can read more about the Division of labour here:
https://en.wikipedia.org/wiki/Division_of_labour
Also you can manage complexity by using constraints, such as laws, road rules and commercial standards, all of which limit the potential for harmful interactions to occur, also you can manage complexity by using higher layers of abstraction such as in computer programming, and we can also follow the efficient rule of: "Do less and do it better" that can also use higher level layers of abstraction to enhance productivity and quality, this rule is good for productivity and quality, and about productivity: I have also just posted about the following thoughts from the following PhD computer scientist:
https://lemire.me/blog/about-me/
Read more here his thoughts about productivity:
https://lemire.me/blog/2012/10/15/you-cannot-scale-creativity/
And i think he is making a mistake:
Since we have that Productivity = Output/Input
But better human training and/or better tools and/or better human smartness and/or better human capacity can make the Parallel productivity part much bigger that the Serial productivity part, so it can scale much more (it is like Gustafson's Law).
And it looks like the following:
About parallelism and about Gustafson’s Law..
Gustafson’s Law:
• If you increase the amount of work done by each parallel
task then the serial component will not dominate
• Increase the problem size to maintain scaling
• Can do this by adding extra complexity or increasing the overall
problem size
Scaling is important, as the more a code scales the larger a machine it
can take advantage of:
• can consider weak and strong scaling
• in practice, overheads limit the scalability of real parallel programs
• Amdahl’s law models these in terms of serial and parallel fractions
• larger problems generally scale better: Gustafson’s law
Load balance is also a crucial factor.
So read my following thoughts about the Threadpool to notice that my Threadpool that scales very well does Load balance well:
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About the Threadpool..
I have just read the following:
Concurrency - Throttling Concurrency in the CLR 4.0 ThreadPool
https://docs.microsoft.com/en-us/archive/msdn-magazine/2010/september/concurrency-throttling-concurrency-in-the-clr-4-0-threadpool
But i think that both the methodologies from Microsoft of the Hill Climbing and of the Control Theory using band pass filter or match filter and discrete Fourier transform have a weakness, there weakness is that they are "localized" optimization that maximize the throughput , so they are not fair, so i don't think i will implement them, so then you can use my following invention of an efficient Threadpool engine with priorities that scales very well (and you can use a second Threadpool for IO etc.):
https://sites.google.com/site/scalable68/an-efficient-threadpool-engine-with-priorities-that-scales-very-well
And here is my other Threadpool engine with priorities:
https://sites.google.com/site/scalable68/threadpool-engine-with-priorities
And read my following previous thoughts to understand more:
About the strategy of "work depth-first; steal breadth-first"..
I have just read the following webpage:
Why Too Many Threads Hurts Performance, and What to do About It
https://www.codeguru.com/cpp/sample_chapter/article.php/c13533/Why-Too-Many-Threads-Hurts-Performance-and-What-to-do-About-It.htm
Also I have just looked at the following interesting video about Go scheduler and Go concurrency:
Dmitry Vyukov — Go scheduler: Implementing language with lightweight concurrency
https://www.youtube.com/watch?v=-K11rY57K7k
And i have just read the following webpage about the Threadpool of microsoft .NET 4.0:
https://blogs.msdn.microsoft.com/jennifer/2009/06/26/work-stealing-in-net-4-0/
And as you are noticing the first web link above is speaking about the strategy of "work depth-first; steal breadth-first" , but we have to be more smart because i think that this strategy, that is advantageous for cache locality, works best for recursive algorithms, because a thread is taking the first task and after that the algorithm is recursive, so it will put the childs tasks inside the local work-stealing queue, and the other threads will start to take from the work-stealing queue, so the work will be distributed correctly, but as you will notice that this strategy works best for recursive algorithms, but when you you iteratively start many tasks, i think we will have much more contention on the work-stealing queue and this is a weakness of this strategy, other than that when it is not a recursive algorithm and the threads are receiving from the global queue so there will be high contention on the global queue and this is not good. MIT's Cilk and Go scheduler and the Threadpool of Microsoft and Intel® C++ TBB are using this strategy of "work depth-first; steal breadth-first". And as you are noticing that they are giving more preference to cache locality than scalability.
But in my following invention of a Threadpool that scales very well i am
giving more preference to scalability than to cache locality:
https://sites.google.com/site/scalable68/an-efficient-threadpool-engine-with-priorities-that-scales-very-well
Other than that when you are doing IO with my Threadpool, you can use asychronous IO by starting a dedicated thread to IO to be more efficient, or you can start another of my Threadpool and use it for tasks that uses IO, you can use the same method when threads of the my Threadpool are waiting or sleeping..
Other than that for recursion and the stack overflow problem you can convert your function from a recursive to iterative to solve the problem of stack overflow.
Other than that to be able to serve a great number of internet connections or TCP/IP socket connections you can use my Threadpool with my powerful Object oriented Stackful coroutines library for Delphi and FreePascal here:
https://sites.google.com/site/scalable68/object-oriented-stackful-coroutines-library-for-delphi-and-freepascal
---
And enhancing productivity is also related to my following powerful product that i have designed and implemented(that can also be applied to organizations):
https://sites.google.com/site/scalable68/universal-scalability-law-for-delphi-and-freepascal
Please read the following about Applying the Universal Scalability Law to organisations:
https://blog.acolyer.org/2015/04/29/applying-the-universal-scalability-law-to-organisations/
Yet more philosophy about quality control and quality..
So first you have to define quality(read below about it) and second you have to construct quality and third you have to control quality.
So, I have just read the following about the Central Limit Theorem (I understood it), i invite you to read it carefully:
https://www.probabilitycourse.com/chapter7/7_1_2_central_limit_theorem.php
So as you are noticing this Central Limit Theorem is so important for quality control, read the following to notice it(I also understood Statistical Process Control (SPC)):
An Introduction to Statistical Process Control (SPC)
https://www.engineering.com/AdvancedManufacturing/ArticleID/19494/An-Introduction-to-Statistical-Process-Control-SPC.aspx
Also PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs are independent random variables with known probability distribution functions, and have finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration.
So, i have designed and implemented my PERT++ that that is important for quality, please read about it and download it from my website here:
https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal
---
So I have provided you in my PERT++ with the following functions:
function NormalDistA (const Mean, StdDev, AVal, BVal: Extended): Single;
function NormalDistP (const Mean, StdDev, AVal: Extended): Single;
function InvNormalDist(const Mean, StdDev, PVal: Extended; const Less: Boolean): Extended;
For NormalDistA() or NormalDistP(), you pass the best estimate of completion time to Mean, and you pass the critical path standard deviation to StdDev, and you will get the probability of the value Aval or the probability between the values of Aval and Bval.
For InvNormalDist(), you pass the best estimate of completion time to Mean, and you pass the critical path standard deviation to StdDev, and you will get the length of the critical path of the probability PVal, and when Less is TRUE, you will obtain a cumulative distribution.
So as you are noticing from my above thoughts that since PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs are independent random variables with known probability distribution functions, and have finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration. So then you have to use my above functions
that are Normal distribution and inverse normal distribution functions, please look at my demo inside my zip file to understand better how i am doing it:
You can download and read about my PERT++ from my website here:
https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal
More of my philosophy about Niklaus Wirth and about the good taste..
Having good taste involves knowing what is truly excellent or of genuine value.
Read here to notice it:
What Is Good Taste?
https://www.3quarksdaily.com/3quarksdaily/2014/03/what-is-good-taste.html
And as you have just noticed i have just posted the following thoughts of Niklaus Wirth (https://en.wikipedia.org/wiki/Niklaus_Wirth):
https://groups.google.com/g/alt.culture.morocco/c/h_xKwu2gM44
And i think that Niklaus Wirth is too pessimistic on the above thoughts Since you have to know that an efficient education can permit to give you a good taste so that to be able to be efficiently selective, and this is valid for both the consumers and the producers of products or services.
And more of my philosophy about the good taste..
So let us look in the dictionary at what is the taste, it says the following:
"The taste is the sense by which the qualities and flavour of a substance are distinguished by the taste buds."
Read here in the dictionary to notice it:
https://www.collinsdictionary.com/dictionary/english/taste
But when you are smart you will also notice that there is also the intellectual taste from culture or genetics, i mean that when you are genetically more rational and more smart you will notice that this more rational and more smart is also intellectual taste since with it you are able to be more efficiently selective of your knowledge, so it permits you to enhance quality, and this is also the same for culture, i mean when you enhance more your culture it enhances your intellectual taste and it permits you to be more efficiently selective of your knowledge, so it permits you to enhance quality.
So as you are noticing that the intellectual taste is so important..
Thank you,
Amine Moulay Ramdane.
More of my philosophy about: Is software engineers really engineers?
I am a white arab and i think i am smart since i have also invented many
scalable algorithms and algorithms..
I have just read the following article about: Is software engineers really engineers ?, i invite you to read it:
Are we really engineers ?
https://www.hillelwayne.com/post/crossover-project/are-we-really-engineers/
I think the above article is lacking, because i think that what makes
the difference between software engineering and other engineering disciplines is not only that software engineering uses discrete
math, but it uses Logic(Formal Logic and such) that has been called "the calculus of computer science". The argument is that logic plays a fundamental role in computer science, similar to that played by calculus in the physical sciences and traditional engineering disciplines. Indeed, logic plays an important role in areas of Computer Science as disparate as artificial intelligence (automated reasoning), architecture (logic gates), software engineering (specification and verification), programming languages (semantics, logic programming), databases (relational algebra and SQL), algorithms (complexity and expressiveness), and theory of computation (general notions of computability).
This is why you are seeing me using my smartness of my fluid intelligence using a sophisticated Logic to find patterns and also proving, and here is some of my thoughts and notice how i am finding patterns and proving with my fluid intelligence:
More precision about capitalism and about National Vanguard..
I will be more rigorous, so read again:
I have just read the following article from a white supremacist website called National Vanguard:
Why Capitalism Fails
https://nationalvanguard.org/2015/07/why-capitalism-fails/
And it is saying the following about why capitalism fails:
"Capitalism permits inheritance, the command transfer of private property to a esignated new owner upon the death of the previous owner. And therein is the flaw: inherited wealth isn’t earned by its owner, yet it leads to a class segregation of men that has nothing to do with how much wealth they have earned; i.e., nothing to do with how much or how well or how significantly they have worked."
I am a white arab and i think i am smart since i have invented many scalable algorithms, and i will answer with my fluid intelligence: I think the above article is not taking into account the risk factor and and the smartness factor, so there have to be mechanisms, that are like engines, that "encourage" to or/and "make" a part of the people work by taking risks or great risks and by doing there best (so that to become rich) or/and that "encourage" to or/and "make" the smartest to give there best with there smartness (so that to become rich), so i think capitalism has those mechanisms in form of rewards by allowing to become "rich" and in form of rewards by allowing inheritance, the command transfer of private property to a designated new owner upon the death of the previous owner: Since it "encourages" to or/and "makes" a part of the people work by taking risks and by doing there best (so that to become rich) or/and it encourages to or/and makes the smartest give there best with there smartness (so that to become rich).
And notice that i am also defining taking a "risk" as working "hard".
And the above article is saying the following:
"Capitalism constantly looks for ways to reduce labor costs. Automation made human labor less necessary than it had been when capitalism first appeared. When automation did appear, people who had the talent, the skills, and the motivation to make contributions began to find no jobs, or to become uncompetitive with mass-production if they tried to employ themselves."
I think it is not true, because read the following:
https://singularityhub.com/2019/01/01/ai-will-create-millions-more-jobs-than-it-will-destroy-heres-how/
And read the following:
Here is the advantages and disadvantages of automation:
Following are some of the advantages of automation:
1. Automation is the key to the shorter workweek. Automation will allow
the average number of working hours per week to continue to decline,
thereby allowing greater leisure hours and a higher quality life.
2. Automation brings safer working conditions for the worker. Since
there is less direct physical participation by the worker in the
production process, there is less chance of personal injury to the worker.
3. Automated production results in lower prices and better products. It
has been estimated that the cost to machine one unit of product by
conventional general-purpose machine tools requiring human operators may
be 100 times the cost of manufacturing the same unit using automated
mass-production techniques. The electronics industry offers many
examples of improvements in manufacturing technology that have
significantly reduced costs while increasing product value (e.g., colour
TV sets, stereo equipment, calculators, and computers).
4. The growth of the automation industry will itself provide employment
opportunities. This has been especially true in the computer industry,
as the companies in this industry have grown (IBM, Digital Equipment
Corp., Honeywell, etc.), new jobs have been created.
These new jobs include not only workers directly employed by these
companies, but also computer programmers, systems engineers, and other
needed to use and operate the computers.
5. Automation is the only means of increasing standard of living. Only
through productivity increases brought about by new automated methods of
production, it is possible to advance standard of living. Granting wage
increases without a commensurate increase in productivity
will results in inflation. To afford a better society, it is a must to
increase productivity.
Following are some of the disadvantages of automation:
1. Automation will result in the subjugation of the human being by a
machine. Automation tends to transfer the skill required to perform work
from human operators to machines. In so doing, it reduces the need for
skilled labour. The manual work left by automation requires lower skill
levels and tends to involve rather menial tasks (e.g., loading and
unloading workpart, changing tools, removing chips, etc.). In this
sense, automation tends to downgrade factory work.
2. There will be a reduction in the labour force, with resulting
unemployment. It is logical to argue that the immediate effect of
automation will be to reduce the need for human labour, thus displacing
workers.
3. Automation will reduce purchasing power. As machines replace workers
and these workers join the unemployment ranks, they will not receive the
wages necessary to buy the products brought by automation. Markets will
become saturated with products that people cannot afford to purchase.
Inventories will grow. Production will stop. Unemployment will reach
epidemic proportions and the result will be a massive economic depression.
And to know more about economy and capitalism, please read my following thoughts:
https://groups.google.com/forum/#!topic/alt.culture.morocco/wlJu5j1xhPk
And more political philosophy about the good taste..
So let us look in the dictionary at what is the taste, it says the following:
"The taste is the sense by which the qualities and flavour of a substance are distinguished by the taste buds."
Read here in the dictionary to notice it:
https://www.collinsdictionary.com/dictionary/english/taste
But when you are smart you will also notice that there is also the intellectual taste from culture or genetics, i mean that when you are genetically more rational and more smart you will notice that this more rational and more smart is also intellectual taste since with it you are able to be more efficiently selective of your knowledge, so it permits you to enhance quality, and this is also the same for culture, i mean when you enhance more your culture it enhances your intellectual taste and it permits you to be more efficiently selective of your knowledge, so it permits you to enhance quality.
So as you are noticing that the intellectual taste is so important..
And you have to also know that i am also doing political philosophy by efficiently finding the patterns with my smartness, i give you an example, look at the following pattern that i am finding with my smartness:
--
More explanation about the rule of "work smart and not hard"..
I will be more logically rigorous and explain more, so read my logical proof:
I have just looked at the following video, i invite you to look at it:
People who say "work smart not hard" pretty much always fail | James Gosling and Lex Fridman
https://www.youtube.com/watch?v=Jaho2mbaVGM&t=99s
Here is James Gosling:
https://en.wikipedia.org/wiki/James_Gosling
And here is Lex Fridman:
https://lexfridman.com/#:~:text=Lex%20Fridman%3A%20I'm%20an,Teaching%3A%20deeplearning.mit.edu
I think i am a white arab that is smart since i have invented many scalable algorithms and i say that Lex Fridman and James Gosling in the above video are not smart by saying that "work smart and not hard" pretty much always fail, and notice that Lex Fridman says that
the "not hard" in the rule means lazy, but this is not logically correct, since if the statistical distribution of the strenght and force of the work is normal in the real world , so i have to discern with my fluid intelligence that it is a system that means "work smart and not hard" and it can mean: "work smart and using an average force or strenght", so then it means that this system or rule doesn't pretty much always fail, also we can generalize and say: since the truth of "work smart and not hard pretty much always fail" depends on the statistical distribution(of the strenght and force of the work) in the real world, so we can not generalize and say that the rule of "work smart and not hard" pretty much always fail.
--
I give you another example, look at the following patterns that i am finding with my smartness:
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What is it to be smart ?
Read my following thoughts:
I am a white arab, and i think i am smart since i have invented many scalable algorithms and there implementations, and today i will speak about what is it to be "smart"..
So i will start it by inviting you to read carefully the following webpage from a Senior Consultant (and former Editor-in-Chief and Publishing Director) of New Scientist and Author of After the Ice:
Why are humans smarter than other animals?
https://www.edge.org/response-detail/12021
So as you are noticing he is saying the following:
--
"The idea of human superiority should have died when Darwin came on the scene.
Unfortunately, the full implications of what he said have been difficult to take in: there is no Great Chain of Being, no higher and no lower. All creatures have adapted effectively to their own environments in their own way. Human "smartness" is just a particular survival strategy among many others, not the top of a long ladder. It took a surprisingly long time for scientists to grasp this. For decades, comparative psychologists tried to work out the learning abilities of different species so that they could be arranged on a single scale. Animal equivalents of intelligence tests were used and people seriously asked whether fish were smarter than birds. It took the new science of ethology, created by Nobel-prize winners Konrad Lorenz, Niko Tinbergen and Karl von Frisch, to show that each species had the abilities it needed for its own lifestyle and they could not be not arranged on a universal scale. Human smartness is no smarter than anyone else's smartness. The question should have died for good."
--
So i think i am smart and say that the above webpage is not so smart, because the logical reasoning defect is that he is first saying the following:
"Human "smartness" is just a particular survival strategy"
This is the first logical defect, since he is like using boolean logic by saying that human smartness is only a particular survival strategy, and this is not correct logical reasoning, because we have like to be fuzzy logic and say that not all humans are using smartness for only survival, since we are not like animals, since we have not to think it only societally, but we can also say there is a great proportion of humans that have transcended there "survival" condition with there smartness to be a much better human condition than only survival. So now we can say with human smartness (and measure it with human smartness) that the humans that have transcended there "survival" condition with there smartness to be a much better human condition have a much superior smartness than animals, since we can measure it with human smartness, and here is the definition of surviving in the dictionary:
https://www.dictionary.com/browse/survive
So as you are noticing that survival is only to remain alive, so i am logical in my thoughts above.
The second logical defect of the above webpage is the following:
Notice that the above webpage that he is saying the following:
"Strangley enough, even evolutionary biologists still get caught up with the notion that humans stand at the apex of existence. There are endless books from evolutionary biologists speculating on the reasons why humans evolved such wonderful big brains, but a complete absence of those which ask if a big brains is a really useful organ to have. The evidence is far from persuasive. If you look at a wide range of organisms, those with bigger brains are generally no more successful than those with smaller brains — hey go extinct just as fast."
So i think that the above webpage is not right.
So notice again that he is saying that the brain must be successful in survival, and this is not correct reasoning, since as i said above smartness is not only about survival, since we have to measure it with our smartness and notice that from also my above thoughts that we can be humans that are much more smart than animals even if we go extinct.
So the important thing to notice in my above logical reasoning , is that you have to measure smartness with smartness, it is the same as my following logical proof about: Is beauty universal ? , here it is , read it carefully:
I will make you understand with smartness what about the following webpage:
Look at the following webpage from BBC:
The myth of universal beauty
https://www.bbc.com/future/article/20150622-the-myth-of-universal-beauty
So notice in the above webpage that it is saying the following about beauty:
"Where starvation is a risk, heavier weight is more attractive"
So you have to understand that the above webpage from BBC is not smart, i will make you understand with smartness that beauty is universal, so if we take the following sentence of the above webpage:
"Where starvation is a risk, heavier weight is more attractive"
So you have to put it in the context of the above webpage, and understand that the way of thinking of the webpage from BBC is not smart, because it is saying that since in the above sentence starvation is a risk , so heavier weight can be more attractive, but this can be heavier weight that is not beautiful for the eyes, so it makes a conclusion that universal beauty is not universal, but this is not smart because we have not to measure beautifulness with only our eyes and say that heavier weight that is not beautiful for the eyes is not beautiful, because we have to measure it with smartness and say that smartness says that in the above sentence that heavier weight that is not beautiful for the eyes is beautiful for smartness because starvation is a risk, so then with smartness we can say that beauty is universal. So we have to know that that the system of reference of measure is very important, by logical analogy we can say that measuring beautifulness with the eyes is like measuring individual smartness with only genetics, but measuring beautifulness with both the eyes and smartness is like measuring individual smartness with both the genetical and the cultural.
About more philosophy about smartness..
You will think that smartness is much more genetical, but this is a big mistake, since i think i am smart and i will explain:
If you want to climb a big mountain, there is two ways:
You can climb the big mountain or you can make the big mountain small in height so that to climb it, so when you are smart you will take a look at the constraints that make smartness much less expressive, and those constraints that make smartness much less expressive is like making the mountain small in height so that to climb it. Read more my following thoughts to understand:
More philosophy about smartness and abstraction and complexity..
So i will start by asking a question:
Is the way of learning by abstraction an efficient way ?
So when you are smart you will quickly notice that we have to take into account the "context" of the way of learning by abstraction, and when you are smart you will notice that the way of learning by abstraction is also to reduce complexity, but when you take into account the context you will notice that learning by abstraction is a also a "specialization" and it is also an efficient way of learning when we measure it inside the "context" of abstraction that is the reality, so then we have not to be pessimistic about learning by the efficient way of abstraction since, first, it reduces the complexity and, second, even if we are not understanding the complexity behind the abstraction, learning by abstraction is also an efficient specialization that is efficient for adaptability, so we have to know how to balance between those that are required to understand the complexity behind the abstraction and those that are required to learn by the way of abstraction that is a specialization.
More philosophy about the way of learning by abstraction..
I will give you an example so that you understand, so if you ask what is the way of learning by abstraction, look at my following tutorial where i am presenting my methodology that, first, permits to model the synchronization primitives of parallel programs with logic primitives with If-then-OR-AND so that to make it easy to translate to petri nets so that to detect deadlocks in parallel programs, please take a look at it because this tutorial of mine is the way of learning by abstraction:
How to analyse parallel applications with Petri Nets
https://sites.google.com/site/scalable68/how-to-analyse-parallel-applications-with-petri-nets
I think i am smart and i will explain more what is smartness..
So that you understand me more, let us say that you are measuring a human IQ, so if it is high human IQ , this value is a measure that is relative to the other human IQs, so you will say that this high IQ is much better at adaptability than the other humans, but it is not correct measure, because even science and technology have constraints that constrain(or limit greatly) the expressiveness of human IQs, so then we can not say that a high human IQ is better at adaptability than the other humans..
More philosophy about how to measure human IQ or human smartness..
I think i am smart, and i will talk about how to measure human IQs or human smartness, first you have to know that you can measure relatively or absolutely, so if you measure the IQ of a human, you will give a value of IQ that is "relative" to the distribution of IQs of humans, so can we ask if it is the right way to measure human IQs? i think it is not, because there is a "very" important thing that is missing, and it is that you have to also measure IQ or smartness relatively to the "constraints" in our reality that constrain(or limit) human IQ or human smartness, and i think this will give a much more realistic measure of human IQs or human smartness, so if you are really smart you will start by searching what are those constraints in the reality that constrain human IQs or human smartness, because this way you will become really smart.
Let me give an example about how to measure IQs or smartness..
So if you are really smart you will give a smart example so that people can understand, so here it is:
If i say: 2 + 2 = 4
So you will notice that this equality is also constrained by constraints of reality, since for example you are noticing that it is not so mathematically expressive, so this not mathematically expressive is also constraining human IQ or human smartness, since if you understand and learn this mathematical equality, another person will quickly do the same, so the other person will adapt quickly to this level of smartness, so now you are noticing the smart idea, it is that even science and technology are constrained the same way, and this constraints on science and technology constrain or limit the expressiveness of high human IQs or high level of smartness so that other lower level human IQs or smartness can attain the level of adaptability of high human IQs, this is what is happening in our today world, and if you are smart you will notice that there is something else that is happening and it is that abstraction of complexity that reduce the complexity is making others not understanding the complexity behind the abstraction and this is not so efficient.
Here is more about the constraints on science and technology:
Is Science Going To End?
Read more here:
https://philosophynow.org/issues/68/Is_Science_Going_To_End
And read also the following
The Industrial Era Ended, and So Will the Digital Era
Read more here:
https://hbr.org/2018/07/the-industrial-era-ended-and-so-will-the-digital-era
More political philosophy about what is smartness..
I give you an example so that you understand:
If i give the following three words:
I, love, you.
It is not the same as if i give the following five words:
I, love, you, very, much
So you are noticing that the five words permit a more sophisticated expressiveness, and notice that i am saying more sophisticated, since the five words bring more efficiency, and this bringing more efficiency is also what we call smartness, but notice that this smartness is brought by using the "tool" that is composed of the five words, so the tool that is our english language brings smartness, so then we have to be convinced by the fact that the tool like internet brings a much more efficiency and this much more efficiency brings much more smartness, so now you are noticing that smartness is not only genetical or cultural, but it is also the smartness of using the tool, and this is a very important thing, since the tool can be powerful and it can advance very much a human and can make a human really smart. So you have to understand that we are also in an Era of powerful tools such as internet that can advance very much a human and that can make a human really smart.
And now i will ask a philosophical question:
How to manage efficiently complexity ?
I think you can manage complexity by the “divide and rule” approach
to management, which also leads to hierarchical division of large organisations, or wich also leads to the Division of "labour", you can read more about the Division of labour here:
https://en.wikipedia.org/wiki/Division_of_labour
Also you can manage complexity by using constraints, such as laws, road rules and commercial standards, all of which limit the potential for harmful interactions to occur, also you can manage complexity by using higher layers of abstraction such as in computer programming, and we can also follow the efficient rule of: "Do less and do it better" that can also use higher level layers of abstraction to enhance productivity and quality, this rule is good for productivity and quality, and about productivity: I have also just posted about the following thoughts from the following PhD computer scientist:
https://lemire.me/blog/about-me/
Read more here his thoughts about productivity:
https://lemire.me/blog/2012/10/15/you-cannot-scale-creativity/
And i think he is making a mistake:
Since we have that Productivity = Output/Input
But better human training and/or better tools and/or better human smartness and/or better human capacity can make the Parallel productivity part much bigger that the Serial productivity part, so it can scale much more (it is like Gustafson's Law).
And it looks like the following:
About parallelism and about Gustafson’s Law..
Gustafson’s Law:
• If you increase the amount of work done by each parallel
task then the serial component will not dominate
• Increase the problem size to maintain scaling
• Can do this by adding extra complexity or increasing the overall
problem size
Scaling is important, as the more a code scales the larger a machine it
can take advantage of:
• can consider weak and strong scaling
• in practice, overheads limit the scalability of real parallel programs
• Amdahl’s law models these in terms of serial and parallel fractions
• larger problems generally scale better: Gustafson’s law
Load balance is also a crucial factor.
So read my following thoughts about the Threadpool to notice that my Threadpool that scales very well does Load balance well:
---
About the Threadpool..
I have just read the following:
Concurrency - Throttling Concurrency in the CLR 4.0 ThreadPool
https://docs.microsoft.com/en-us/archive/msdn-magazine/2010/september/concurrency-throttling-concurrency-in-the-clr-4-0-threadpool
But i think that both the methodologies from Microsoft of the Hill Climbing and of the Control Theory using band pass filter or match filter and discrete Fourier transform have a weakness, there weakness is that they are "localized" optimization that maximize the throughput , so they are not fair, so i don't think i will implement them, so then you can use my following invention of an efficient Threadpool engine with priorities that scales very well (and you can use a second Threadpool for IO etc.):
https://sites.google.com/site/scalable68/an-efficient-threadpool-engine-with-priorities-that-scales-very-well
And here is my other Threadpool engine with priorities:
https://sites.google.com/site/scalable68/threadpool-engine-with-priorities
And read my following previous thoughts to understand more:
About the strategy of "work depth-first; steal breadth-first"..
I have just read the following webpage:
Why Too Many Threads Hurts Performance, and What to do About It
https://www.codeguru.com/cpp/sample_chapter/article.php/c13533/Why-Too-Many-Threads-Hurts-Performance-and-What-to-do-About-It.htm
Also I have just looked at the following interesting video about Go scheduler and Go concurrency:
Dmitry Vyukov — Go scheduler: Implementing language with lightweight concurrency
https://www.youtube.com/watch?v=-K11rY57K7k
And i have just read the following webpage about the Threadpool of microsoft .NET 4.0:
https://blogs.msdn.microsoft.com/jennifer/2009/06/26/work-stealing-in-net-4-0/
And as you are noticing the first web link above is speaking about the strategy of "work depth-first; steal breadth-first" , but we have to be more smart because i think that this strategy, that is advantageous for cache locality, works best for recursive algorithms, because a thread is taking the first task and after that the algorithm is recursive, so it will put the childs tasks inside the local work-stealing queue, and the other threads will start to take from the work-stealing queue, so the work will be distributed correctly, but as you will notice that this strategy works best for recursive algorithms, but when you you iteratively start many tasks, i think we will have much more contention on the work-stealing queue and this is a weakness of this strategy, other than that when it is not a recursive algorithm and the threads are receiving from the global queue so there will be high contention on the global queue and this is not good. MIT's Cilk and Go scheduler and the Threadpool of Microsoft and Intel® C++ TBB are using this strategy of "work depth-first; steal breadth-first". And as you are noticing that they are giving more preference to cache locality than scalability.
But in my following invention of a Threadpool that scales very well i am
giving more preference to scalability than to cache locality:
https://sites.google.com/site/scalable68/an-efficient-threadpool-engine-with-priorities-that-scales-very-well
Other than that when you are doing IO with my Threadpool, you can use asychronous IO by starting a dedicated thread to IO to be more efficient, or you can start another of my Threadpool and use it for tasks that uses IO, you can use the same method when threads of the my Threadpool are waiting or sleeping..
Other than that for recursion and the stack overflow problem you can convert your function from a recursive to iterative to solve the problem of stack overflow.
Other than that to be able to serve a great number of internet connections or TCP/IP socket connections you can use my Threadpool with my powerful Object oriented Stackful coroutines library for Delphi and FreePascal here:
https://sites.google.com/site/scalable68/object-oriented-stackful-coroutines-library-for-delphi-and-freepascal
---
And enhancing productivity is also related to my following powerful product that i have designed and implemented(that can also be applied to organizations):
https://sites.google.com/site/scalable68/universal-scalability-law-for-delphi-and-freepascal
Please read the following about Applying the Universal Scalability Law to organisations:
https://blog.acolyer.org/2015/04/29/applying-the-universal-scalability-law-to-organisations/
Yet more philosophy about quality control and quality..
So first you have to define quality(read below about it) and second you have to construct quality and third you have to control quality.
So, I have just read the following about the Central Limit Theorem (I understood it), i invite you to read it carefully:
https://www.probabilitycourse.com/chapter7/7_1_2_central_limit_theorem.php
So as you are noticing this Central Limit Theorem is so important for quality control, read the following to notice it(I also understood Statistical Process Control (SPC)):
An Introduction to Statistical Process Control (SPC)
https://www.engineering.com/AdvancedManufacturing/ArticleID/19494/An-Introduction-to-Statistical-Process-Control-SPC.aspx
Also PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs are independent random variables with known probability distribution functions, and have finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration.
So, i have designed and implemented my PERT++ that that is important for quality, please read about it and download it from my website here:
https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal
---
So I have provided you in my PERT++ with the following functions:
function NormalDistA (const Mean, StdDev, AVal, BVal: Extended): Single;
function NormalDistP (const Mean, StdDev, AVal: Extended): Single;
function InvNormalDist(const Mean, StdDev, PVal: Extended; const Less: Boolean): Extended;
For NormalDistA() or NormalDistP(), you pass the best estimate of completion time to Mean, and you pass the critical path standard deviation to StdDev, and you will get the probability of the value Aval or the probability between the values of Aval and Bval.
For InvNormalDist(), you pass the best estimate of completion time to Mean, and you pass the critical path standard deviation to StdDev, and you will get the length of the critical path of the probability PVal, and when Less is TRUE, you will obtain a cumulative distribution.
So as you are noticing from my above thoughts that since PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs are independent random variables with known probability distribution functions, and have finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration. So then you have to use my above functions
that are Normal distribution and inverse normal distribution functions, please look at my demo inside my zip file to understand better how i am doing it:
You can download and read about my PERT++ from my website here:
https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal
More of my philosophy about Niklaus Wirth and about the good taste..
Having good taste involves knowing what is truly excellent or of genuine value.
Read here to notice it:
What Is Good Taste?
https://www.3quarksdaily.com/3quarksdaily/2014/03/what-is-good-taste.html
And as you have just noticed i have just posted the following thoughts of Niklaus Wirth (https://en.wikipedia.org/wiki/Niklaus_Wirth):
https://groups.google.com/g/alt.culture.morocco/c/h_xKwu2gM44
And i think that Niklaus Wirth is too pessimistic on the above thoughts Since you have to know that an efficient education can permit to give you a good taste so that to be able to be efficiently selective, and this is valid for both the consumers and the producers of products or services.
And more of my philosophy about the good taste..
So let us look in the dictionary at what is the taste, it says the following:
"The taste is the sense by which the qualities and flavour of a substance are distinguished by the taste buds."
Read here in the dictionary to notice it:
https://www.collinsdictionary.com/dictionary/english/taste
But when you are smart you will also notice that there is also the intellectual taste from culture or genetics, i mean that when you are genetically more rational and more smart you will notice that this more rational and more smart is also intellectual taste since with it you are able to be more efficiently selective of your knowledge, so it permits you to enhance quality, and this is also the same for culture, i mean when you enhance more your culture it enhances your intellectual taste and it permits you to be more efficiently selective of your knowledge, so it permits you to enhance quality.
So as you are noticing that the intellectual taste is so important..
Thank you,
Amine Moulay Ramdane.
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