• About Java and Delphi and Freepascal.. (1/2)

    From Wisdom90@21:1/5 to Bonita Montero on comp.programming. on Mon Jan 27 12:19:48 2020
    Hello..


    About Java and Delphi and Freepascal..

    I have just read the following webpage:

    Java is not a safe language

    https://lemire.me/blog/2019/03/28/java-is-not-a-safe-language/


    But as you have noticed the webpage says:

    - Java does not trap overflows

    But Delphi and Freepascal do trap overflows.

    And the webpage says:

    - Java lacks null safety

    But Delphi has null safety since i have just posted about it by saying
    the following:

    Here is MyNullable library for Delphi and FreePascal that brings null
    safety..

    Java lacks null safety. When a function receives an object, this object
    might be null. That is, if you see ‘String s’ in your code, you often
    have no way of knowing whether ‘s’ contains an actually String unless
    you check at runtime. Can you guess whether programmers always check?
    They do not, of course, In practice, mission-critical software does
    crash without warning due to null values. We have two decades of
    examples. In Swift or Kotlin, you have safe calls or optionals as part
    of the language.

    Here is MyNullable library for Delphi and FreePascal that brings null
    safety, you can read the html file inside the zip to know how it works,
    and you can download it from my website here:

    https://sites.google.com/site/scalable68/null-safety-library-for-delphi-and-freepascal


    And the webpage says:

    - Java allows data races

    But for Delphi and Freepascal i have just written about how to prevent
    data races by saying the following:

    Yet more precision about the invariants of a system..

    I was just thinking about Petri nets , and i have studied more
    Petri nets, they are useful for parallel programming, and
    what i have noticed by studying them, is that there is two methods
    to prove that there is no deadlock in the system, there is the
    structural analysis with place invariants that you have to
    mathematically find, or you can use the reachability tree, but we have
    to notice that the structural analysis of Petri nets learns you more,
    because it permits you to prove that there is no deadlock in the system,
    and the place invariants are mathematically calculated by the following
    system of the given Petri net:

    Transpose(vector) * Incidence matrix = 0

    So you apply the Gaussian Elimination or the Farkas algorithm to
    the incidence matrix to find the Place invariants, and as you will
    notice those place invariants calculations of the Petri nets look
    like Markov chains in mathematics, with there vector of probabilities
    and there transition matrix of probabilities, and you can, using
    Markov chains mathematically calculate where the vector of probabilities
    will "stabilize", and it gives you a very important information, and
    you can do it by solving the following mathematical system:

    Unknown vector1 of probabilities * transition matrix of probabilities =
    Unknown vector1 of probabilities.

    Solving this system of equations is very important in economics and
    other fields, and you can notice that it is like calculating the
    invariants , because the invariant in the system above is the
    vector1 of probabilities that is obtained, and this invariant,
    like in the invariants of the structural analysis of Petri nets,
    gives you a very important information about the system, like where
    market shares will stabilize that is calculated this way in economics.

    About reachability analysis of a Petri net..

    As you have noticed in my Petri nets tutorial example (read below),
    i am analysing the liveness of the Petri net, because there is a rule
    that says:

    If a Petri net is live, that means that it is deadlock-free.

    Because reachability analysis of a Petri net with Tina
    gives you the necessary information about boundedness and liveness
    of the Petri net. So if it gives you that the Petri net is "live" , so
    there is no deadlock in it.

    Tina and Partial order reduction techniques..

    With the advancement of computer technology, highly concurrent systems
    are being developed. The verification of such systems is a challenging
    task, as their state space grows exponentially with the number of
    processes. Partial order reduction is an effective technique to address
    this problem. It relies on the observation that the effect of executing transitions concurrently is often independent of their ordering.

    Tina is using “partial-order” reduction techniques aimed at preventing combinatorial explosion, Read more here to notice it:

    http://projects.laas.fr/tina/papers/qest06.pdf

    About modelizations and detection of race conditions and deadlocks
    in parallel programming..

    I have just taken further a look at the following project in Delphi
    called DelphiConcurrent by an engineer called Moualek Adlene from France:

    https://github.com/moualek-adlene/DelphiConcurrent/blob/master/DelphiConcurrent.pas

    And i have just taken a look at the following webpage of Dr Dobb's journal:

    Detecting Deadlocks in C++ Using a Locks Monitor

    https://www.drdobbs.com/detecting-deadlocks-in-c-using-a-locks-m/184416644

    And i think that both of them are using technics that are not as good
    as analysing deadlocks with Petri Nets in parallel applications ,
    for example the above two methods are only addressing locks or mutexes
    or reader-writer locks , but they are not addressing semaphores
    or event objects and such other synchronization objects, so they
    are not good, this is why i have written a tutorial that shows my
    methodology of analysing and detecting deadlocks in parallel
    applications with Petri Nets, my methodology is more sophisticated
    because it is a generalization and it modelizes with Petri Nets the
    broader range of synchronization objects, and in my tutorial i will add
    soon other synchronization objects, you have to look at it, here it is:

    https://sites.google.com/site/scalable68/how-to-analyse-parallel-applications-with-petri-nets

    You have to get the powerful Tina software to run my Petri Net examples
    inside my tutorial, here is the powerful Tina software:

    http://projects.laas.fr/tina/

    Also to detect race conditions in parallel programming you have to take
    a look at the following new tutorial that uses the powerful Spin tool:

    https://mirrors.edge.kernel.org/pub/linux/kernel/people/paulmck/perfbook/perfbook.html

    This is how you will get much more professional at detecting deadlocks
    and race conditions in parallel programming.


    And about memory safety of Delphi and Freepascal, here is what i said:

    I have just read the following webpage about memory safety:

    Microsoft: 70 percent of all security bugs are memory safety issues

    https://www.zdnet.com/article/microsoft-70-percent-of-all-security-bugs-are-memory-safety-issues/


    And it says:


    "Users who often read vulnerability reports come across terms over and
    over again. Terms like buffer overflow, race condition, page fault, null pointer, stack exhaustion, heap exhaustion/corruption, use after free,
    or double free --all describe memory safety vulnerabilities."

    So as you will notice below, that the following memory safety problems
    has been solved in Delphi:

    And I have just read the following webpage about "Fearless Security:
    Memory safety":

    https://hacks.mozilla.org/2019/01/fearless-security-memory-safety/

    Here is the memory safety problems:

    1- Misusing Free (use-after-free, double free)

    I have solved this in Delphi and Freepascal by inventing a "Scalable"
    reference counting with efficient support for weak references. Read
    below about it.


    2- Uninitialized variables

    This can be detected by the compilers of Delphi and Freepascal.


    3- Dereferencing Null pointers

    I have solved this in Delphi and Freepascal by inventing a "Scalable"
    reference counting with efficient support for weak references. Read
    below about it.

    4- Buffer overflow and underflow

    This has been solved in Delphi by using madExcept, read here about it:

    http://help.madshi.net/DebugMm.htm

    You can buy it from here:

    http://www.madshi.net/


    There remains also the stack exhaustion memory safety problem,
    and here is how to detect it in Delphi:

    Call the function "DoStackOverflow" below once from your code and you'll
    get the EStackOverflow error raised by Delphi with the message "stack overflow", and you can print the line of the source code where
    EStackOverflow is raised with JCLDebug and such:

    ----

    ​function DoStackOverflow : integer;

    begin

    result := 1 + DoStackOverflow;

    end;

    ---



    About my scalable algorithms inventions..


    I am a white arab, and i am a gentleman type of person,
    and i think that you know me too by my poetry that i wrote
    in front of you and that i posted here, but i am
    also a more serious computer developer, and i am also
    an inventor who has invented many scalable algorithms, read about
    them on my writing below:


    Here is my last scalable algorithm invention, read
    what i have just responded in comp.programming.threads:

    About my LRU scalable algorithm..

    On 10/16/2019 7:48 AM, Bonita Montero on comp.programming.threads wrote:
    Amine, a quest for you:
    Database-servers and operating-system-kernels mostly use LRU as
    the scheme to evict old buffers from their cache. One issue with
    LRU is, that an LRU-structure can't be updated by multiple threads simultaneously. So you have to have a global lock.
    I managed to write a LRU-caching-class that can update the links
    in the LRU-list to put the most recent fetched block to the h