Computer Systems Lab TJHSST Current Projects 2004-2005 First Period

1
Computer Systems LabTJHSSTCurrent Projects
2004-2005First Period
2
Current Projects, 1st Period

• Caroline Bauer Archival of Articles via RSS and
  Datamining Performed on Stored Articles
• Susan Ditmore Construction and Application of a
  Pentium II Beowulf Cluster
• Michael Druker Universal Problem Solving Contest
  Grader

2
3
Current Projects, 1st Period

• Matt Fifer The Study of Microevolution Using
  Agent-based Modeling
• Jason Ji Natural Language Processing Using
  Machine Translation in Creation of a
  German-English Translator
• Anthony Kim A Study of Balanced Search Trees
  Brainforming a New Balanced Search Tree
• John Livingston Kernel Debugging User-Space API
  Library (KDUAL)

3
4
Current Projects, 1st Period

• Jack McKay Saber-what? An Analysis of the Use of
  Sabermetric Statistics in Baseball
• Peden Nichols An Investigation into
  Implementations of DNA Sequence Pattern Matching
  Algorithms
• Robert Staubs Part-of-Speech Tagging with
  Limited Training Corpora
• Alex Volkovitsky Benchmarking of Cryptographic
  Algorithms

4
5
Archival of Articles via RSS and Datamining
Performed on Stored ArticlesRSS (Really Simple
Syndication, encompassing Rich Site Summary and
RDF Site Summary) is a web syndication protocol
used by many blogs and news websites to
distribute information it saves people having to
visit several sites repeatedly to check for new
content. At this point in time there are many RSS
newsfeed aggregators available to the public, but
none of them perform any sort of archival of
information beyond the RSS metadata. The purpose
of this project is to create an RSS aggregator
that will archive the text of the actual articles
linked to in the RSS feeds in some kind of
linkable, searchable database, and, if all goes
well, implement some sort of datamining
capability as well.
5
6
Archival of Articles via RSS, and Datamining
Performed on Stored ArticlesCaroline Bauer

• Abstract
• RSS (Really Simple Syndication, encompassing
  Rich Site Summary and RDF Site Summary) is a web
  syndication protocol used by many blogs and news
  websites to distribute information it saves
  people having to visit several sites repeatedly
  to check for new content. At this point in time
  there are many RSS newsfeed aggregators available
  to the public, but none of them perform any sort
  of archival of information beyond the RSS
  metadata. As the articles linked may move or be
  eliminated at some time in the future, if one
  wants to be sure one can access them in the
  future one has to archive them oneself
  furthermore, should one want to link such
  collected articles, it is far easier to do if one
  has them archived. The purpose of this pro ject
  is to create an RSS aggregator that will archive
  the text of the actual articles linked to in the
  RSS feeds in some kind of linkable, searchable
  database, and, if all goes well, implement some
  sort of datamining capability as well.

7
Archival of Articles via RSS, and Datamining
Performed on Stored ArticlesCaroline Bauer

• Introduction
• This paper is intended to be a detailed summary
  of all of the author's findings regarding the
  archival of articles in a linkable, searchable
  database via RSS.
• Background RSS
• RSS stands for Really Simple Syndication, a
  syndication protocol often used by weblogs and
  news sites. Technically, RSS is an xml-based
  communication standard that encompasses Rich Site
  Summary (RSS 0.9x and RSS 2.0) and RDF Site
  Summary (RSS 0.9 and 1.0). It enables people to
  gather new information by using an RSS aggregator
  (or "feed reader") to poll RSS-enabled sites for
  new information, so the user does not have to
  manually check each site. RSS aggregators are
  often extensions of browsers or email programs,
  or standalone programs alternately, they can be
  web-based, so the user can view their "feeds"
  from any computer with Web access.
• Archival Options Available in Existing RSS
  Aggregators Data Mining
• Data mining is the searching out of information
  based on patterns present in large amounts of
  data. //more will be here.

8
Archival of Articles via RSS, and Datamining
Performed on Stored ArticlesCaroline Bauer

• Purpose
• The purpose of this project is to create an RSS
  aggregator that, in addition to serving as a feed
  reader, obtains the text of the documents linked
  in the RSS feeds and places it into a database
  that is both searchable and linkable. In addition
  to this, the database is intended to reach an
  implementation wherein it performs some manner of
  data mining on the information contained therein
  the specifics on this have yet to be determined.
• Development Results Conclusions Summary
  References
• 1. "RSS (protocol)." Wikipedia. 8 Jan. 2005. 11
  Jan. 2005 lthttp//en. wikipedia.org/wiki/RSS_28pr
  otocol29gt. 2. "Data mining." Wikipedia. 7 Jan.
  2005. 12 Jan. 2005. lthttp//en.
  wikipedia.org/wiki/Data_mininggt.

9
Construction and Application of a Pentium II
Beowulf ClusterI plan to construct a super
computing cluster of about 15-20 or more Pentium
II computers with the OpenMosix kernel patch.
Once constructed, the cluster could be configured
to transparently aid workstations with
computationally expensive jobs run in the lab.
This project would not only increase the
computing power of the lab, but it would also be
an experiment in building a lowlevel, lowcost
cluster with a stripped down version of Linux,
useful to any facility with old computers they
would otherwise deem outdated.
9
10
Construction and Application of a Pentium II
Beowulf ClusterSusan Ditmore

• Text version needed
• (your pdf file won't copy to text)

11
Universal Problem Solving Contest GraderMichael
Druker(poster needed)
11
12
Universal Problem Solving Contest GraderMichael
Druker

• Steps so far
• Creation of directory structure for the grader,
  the contests, the users, the users' submissions,
  the test cases.
• -Starting of main grading script itself.
• Refinement of directory structure for the grader.
• -Reading of material on bash scripting language
  to be able to write the various scripts that will
  be necessary.

13
Universal Problem Solving Contest GraderMichael
Druker

• Current program
• !/bin/bash
• CONDIR"/afs/csl.tjhsst.edu/user/mdruker/techlab/c
  ode/new/"
• syntax is "grade contest user program"
• contest1
• user2
• program3
• echo "contest name is " 1
• echo "user's name is " 2
• echo "program name is " 3

14
Universal Problem Solving Contest GraderMichael
Druker

• Current program continued
• get the location of the program and the test
  data
• make sure that the contest, user, program are
  valid
• PROGDIRCONDIR"contests/"contest"/users/"u
  ser
• echo "user's directory is" PROGDIR
• if -d PROGDIR
• then echo "good input"
• else echo "bad input, directory doesn't exist"
• exit 1 fi
• exit 0

15
Study of Microevolution Using Agent-Based
Modeling in CThe goal of the project is to
create a program that uses an agent-environment
structure to imitate a very simple natural
ecosystem one that includes a single type of
species that can move, reproduce, kill, etc. The
"organisms" will contain genomes (libraries of
genetic data) that can be passed from parents to
offspring in a way similar to that of animal
reproduction in nature. As the agents interact
with each other, the ones with the
characteristics most favorable to survival in the
artificial ecosystem will produce more children,
and over time, the mean characteristics of the
system should start to gravitate towards the
traits that would be most beneficial. This
process, the optimization of physical traits of a
single species through passing on heritable
advantageous genes, is known as microevolution.
15
16
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• Abstract
• The goal of the project is to create a program
  that uses an agent-environment structure to
  imitate a very simple natural ecosystem one that
  includes a single type of species that can move,
  reproduce, kill, etc. The "organisms" will
  contain genomes (libraries of genetic data) that
  can be passed from parents to offspring in a way
  similar to that of animal reproduction in nature.
  As the agents interact with each other, the ones
  with the characteristics most favorable to
  survival in the artificial ecosystem will produce
  more children, and over time, the mean
  characteristics of the system should start to
  gravitate towards the traits that would be most
  beneficial. This process, the optimization of
  physical traits of a single species through
  passing on heritable advantageous genes, is known
  as microevolution.

17
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• Purpose
• One of the most controversial topics in science
  today is the debate of creationism vs. Darwinism.
  Advocates for creationism believe that the world
  was created according to the description detailed
  in the 1st chapter of the book of Genesis in the
  Bible. The Earth is approximately 6,000 years
  old, and it was created by God, followed by the
  creation of animals and finally the creation of
  humans, Adam and Eve. Darwin and his followers
  believe that from the moment the universe was
  created, all the objects in that universe have
  been in competition. Everything - from the
  organisms that make up the global population, to
  the cells that make up those organisms, to the
  molecules that make up those cells has beaten all
  of its competitors in the struggle for resources
  commonly known as life.

18
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• This project will attempt to model the day-today
  war between organisms of the same species.
  Organisms, or agents, that can move, kill, and
  reproduce will be created and placed in an
  ecosystem. Each agent will include a genome that
  codes for its various characteristics. Organisms
  that are more successful at surviving or more
  successful at reproducing will pass their genes
  to their children, making future generations
  better suited to the environment. The competition
  will continue, generation after generation, until
  the simulation terminates. If evolution has
  occurred, the characteristics of the population
  at the end of the simulation should be markedly
  different than at the beginning.

19
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• Background
• Two of the main goals of this project are the
  study of microevolution and the effects of
  biological mechanisms on this process. Meiosis,
  the formation of gametes, controls how genes are
  passed from parents to their offspring. In the
  first stage of meiosis, prophase I, the strands
  of DNA floating around the nucleus of the cell
  are wrapped around histone proteins to form
  chromosomes. Chromosomes are easier to work with
  than the strands of chromatin, as they are
  packaged tightly into an "X" structure (two "gt"s
  connected at the centromere). In the second
  phase, metaphase I, chromosomes pair up along the
  equator of the cell, with homologous chromosomes
  being directly across from each other.
  (Homologous chromosomes code for the same traits,
  but come from different parents, and thus code
  for different versions of the same trait.) The
  pairs of chromosomes, called tetrads, are
  connected and exchange genetic material.

20
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• This process, called crossing over, results in
  both of the chromosomes being a combination of
  genes from the mother and the father. Whole genes
  swap places, not individual nucleotides. In the
  third phase, anaphase I, fibers from within the
  cell pull the pair apart. When the pairs are
  pulled apart, the two chromosomes are put on
  either side of the cell. Each pair is split
  randomly, so for each pair, there are two
  possible outcomes. For instance, the paternal
  chromosome can either move to the left or right
  side of the cell, with the maternal chromosome
  moving to the opposite end. In telophase I, the
  two sides of the cell split into two individual
  cells. Thus, for each cell undergoing meiosis,
  there are 2n possible gametes. With crossing
  over, there are almost an infinite number of
  combinations of genes in the gametes. This large
  number of combinations is the reason for the
  genetic biodiversity that exists in the world
  today, even among species. For example, there are
  6 billion humans on the planet, and none of them
  is exactly the same as another one.

21
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• Procedure
• This project will be implemented with a matrix
  of agents. The matrix, initialized with only
  empty spaces, will be seeded with organisms by an
  Ecosystem class. Each agent in the matrix will
  have a genome, which will determine how it
  interacts with the Ecosystem. During every step
  of the simulation, an organism will have a choice
  whether to 1. do nothing 2. move to an empty
  adjacent space 3. kill an organism in a
  surrounding space, or 4. reproduce with an
  organism in an adjacent space. The likelihood of
  the organism performing any of these tasks is
  determined by the organism's personal variables,
  which will be coded for by the organism's genome.
  While the simulation is running, the average
  characteristics of the population will be
  measured. In theory, the mean value of each of
  the traits (speed, agility, strength, etc.)
  should either increase with time or gravitate
  towards a particular, optimum value.

22
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• At its most basic level, the program written to
  model microevolution is an agentenvironment
  program. The agents, or members of the Organism
  class, contain a genome and have abilities that
  are dependent upon the genome. Here is the
  declaration of the Organism class
• class Organism
• public Organism()
• //constructors Organism(int ident, int row2, int
  col2)
• Organism(Nucleotide mDNA, Nucleotide dDNA, int
  ident,
• bool malefemale, int row2, int col2)
• Organism() //destructor void printGenome()
• void meiosis(Nucleotide gamete)
• Organism reproduce(Organism mate, int ident,
  int r, int c)
• int Interact(Organism neighbors, int nlen) ...
  

23
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• //assigns a gene a numeric value int Laziness()
• //accessor functions int Rage() int SexDrive()
  int Activity() int DeathRate() int
  ClausIndex() int Age() int Speed() int Row()
  int Col() int PIN() bool Interacted() bool
  Gender() void setPos(int row2, int col2) void
  setInteracted(bool interacted) private void
  randSpawn(Nucleotide DNA, int size) //randomly
  generates a genome Nucleotide mom, dad
  //genome int ID, row, col, laziness, rage,
  sexdrive, activity, deathrate, clausindex, speed
  //personal characteristics double age bool male,
  doneStuff ...

24
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• The agents are managed by the environment class,
  known as Ecosystem. The Ecosystem contains a
  matrix of Organisms.
• Here is the declaration of the Ecosystem class
• class Ecosystem public Ecosystem()
  //constructors Ecosystem(double oseed)
  Ecosystem() //destructor void Run(int steps)
  //the simulation void printMap() void print(int
  r, int c) void surrSpaces(Organism neighbors,
  int r, int c, int friends) //the neighbors of
  any cell private Organism Population //the
  matrix of Organisms

25
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• The simulation runs for a predetermined number of
  steps within the Ecosystem class. During every
  step of the simulation, the environment class
  cycles through the matrix of agents, telling each
  one to interact with its neighbors. To aid in the
  interaction, the environment sends the agent an
  array of the neighbors that it can affect. Once
  the agent has changed (or not changed) the array
  of neighbors, it sends the array back to the
  environment which then updates the matrix of
  agents. Here is the code for the Organisms
  function which enables it to interact with its
  neighbors

26
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• int OrganismInteract(Organism neighbors, int
  nlen) //returns 0 if the organism hasn't moved
  1 if it has fout ltlt row ltlt " " ltlt col ltlt " "
  if(!ID)//This Organism is not an organism fout
  ltlt "Not an organism, cannot interact!" ltlt endl
  return 0 if(doneStuff)//This Organism has
  already interacted once this step fout ltlt "This
  organism has already interacted!" ltlt endl return
  0 doneStuff true int loop for(loop 0
  loop lt GENES CHROMOSOMES GENE_LENGTH loop)
  if(rand() RATE_MAX lt MUTATION_RATE) momloop
  (Nucleotide)(rand() 4) if(rand() RATE_MAX
  lt MUTATION_RATE)

27
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• The Organisms, during any simulation step, can
  either move, kill a neighbor, remain idle,
  reproduce, or die. The fourth option,
  reproduction, is the most relevant to the
  project. As explained before, organisms that are
  better at reproducing or surviving will pass
  their genes to future generations. The most
  critical function in reproduction is the meiosis
  function, which determines what traits are passed
  down to offspring. The process is completely
  random, but an organism with a "good" gene has
  about a 50 chance of passing that gene on to its
  child. Here is the meiosis function, which
  determines what genes each organism sends to its
  offspring
• void Organismmeiosis(Nucleotide gamete) int
  x, genect, chromct, crossover Nucleotide
  chromo new NucleotideGENES GENE_LENGTH,
  chromo2 new NucleotideGENES GENE_LENGTH
  Nucleotide gene new NucleotideGENE_LENGTH,
  gene2 new NucleotideGENE_LENGTH ... (more
  code)

28
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• The functions and structures above are the most
  essential to the running of the program and the
  actual study of microevolution. At the end of
  each simulation step, the environment class
  records the statistics for the agents in the
  matrix and puts the numbers into a spreadsheet
  for analysis. The spreadsheet can be used to
  observe trends in the mean characteristics of the
  system over time. Using the spreadsheet created
  by the environment class, I was able to create
  charts that would help me analyze the evolution
  of the Organisms over the course of the
  simulation.

29
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• The first time I ran the simulation, I set the
  program so that there was no mutation in the
  agent's genomes. Genes were strictly created at
  the outset of the program, and those genes were
  passed down to future generations. If
  microevolution were to take place, a gene that
  coded for a beneficial characteristic would have
  a higher chance of being passed down to a later
  generation. Without mutation, however, if one
  organism possessed a characteristic that was far
  superior to the comparable characteristics of
  other organisms, that gene should theoretically
  allow that organism to "dominate" the other
  organisms and pass its genetic material to many
  children, in effect exterminating the genes that
  code for less beneficial characteristics.

30
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• For example, if an organism was created that had
  a 95 chance of reproducing in a given simulation
  step, it would quickly pass its genetic material
  to a lot of offspring, until its gene was the
  only one left coding for reproductive tendency,
  or libido.

31
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• As you can see from Figure 1, the average
  tendency to reproduce increases during the
  simulation. The tendency to die decreases to
  almost nonexistence. The tendency to remain
  still, since it has relatively no effect on
  anything, stays almost constant. The tendency to
  move to adjacent spaces, thereby spreading one's
  genes throughout the ecosystem, increases to be
  almost as likely as reproduction. The tendency to
  kill one's neighbor decreases drastically,
  probably because it does not positively benefit
  the murdering organism. In Figure 2, we can see
  that the population seems to stabilize at about
  the same time as the average characteristics.
  This would suggest that there was a large amount
  of competition among the organisms early in the
  simulation, but the competition quieted down as
  one dominant set of genes took over the
  ecosystem.

32
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• Figure 4 These figures show the results from the
  second run of the program, when mutation was
  turned on. As you can see, many of the same
  trends exist, with reproductive tendency
  skyrocketing and tendency to kill plummeting.
  Upon reevaluation, it seems that perhaps the
  tendencies to move and remain idle do not really
  affect an agent's ability survive, and thus their
  trends are more subject to fluctuations that
  occur in the beginning of the simulation. One
  thing to note about the mutation simulation is
  the larger degree of fluctuation in both
  characteristics and population. The population
  stabilizes at about the same number, but swings
  between simulation steps are more pronounced. In
  Figure 3, the stabilization that had occurred in
  Figure 1 is largely not present.

33
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• Conclusion
• The goal of this project at the outset was to
  create a system that modeled trends and processes
  from the natural world, using the same mechanisms
  that occur in that natural world. While this
  project by no means definitively proves the
  correctness of Darwin's theory of evolution over
  the creationist theory, it demonstrates some of
  the basic principles that Darwin addressed in his
  book, The Origin of Species. Darwin addresses two
  distinct processes--natural selection and
  artificial selection. Artificial selection, or
  selective breeding, was not present in this
  project at all. There was no point in the program
  where the user was allowed to pick organisms that
  survived. Natural selection, though it is a
  stretch because nature was the inside of a
  computer, was simulated. Natural selection,
  described as the "survival of the fittest," is
  when an organism's characteristics enable it to
  survive and pass those traits to its offspring.

34
THE STUDY OF MICROEVOLUTION USING AGENTBASED
MODELINGMatt Fifer

• In this program, "nature" was allowed to run its
  course, and at the end of the simulation, the
  organisms with the best combination of
  characteristics had triumphed over their
  predecessors. "Natural" selection occurred as
  predicted.
• All of the information in this report was either
  taught last year in A.P. Biology last year and,
  to a small degree, Charles Darwin's The Origin of
  Species. I created all of the code and all of the
  charts in this paper. For my next draft, I will
  be sure to include more outside information that
  I have found in the course of my research

35
Using Machine Translation in a German English
TranslatorThis project attempts to take the
beginning steps towards the goal of creating a
translator program that operates within the scope
of translating between English and German.
35
36
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• Abstract
• The field of machine translation - using
  computers to provide translations between human
  languages - has been around for decades. And the
  dream of an ideal machine providing a perfect
  translation between languages has been around
  still longer. This pro ject attempts to take the
  beginning steps towards that goal, creating a
  translator program that operates within an
  extremely limited scope to translate between
  English and German. There are several different
  strategies to machine translation, and this pro
  ject will look into them - but the strategy taken
  to this pro ject will be the researcher's own,
  with the general guideline of "thinking as a
  human."

37
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• For if humans can translate between language,
  there must be something to how we do it, and
  hopefully that something - that thought process,
  hopefully - can be transferred to the machine and
  provide quality translations.
• Background
• There are several methods of varying difficulty
  and success to machine translation. The best
  method to use depends on what sort of system is
  being created. A bilingual system translates
  between one pair of languages a multilingual
  system translates between more than two systems.

38
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• The easiest translation method to code, yet
  probably least successful, is known as the direct
  approach. The direct approach does what it sounds
  like it does - takes the input language (known as
  the "source language"), performs 2 morphological
  analysis - whereby words are broken down and
  analyzed for things such as prefixes and past
  tense endings, performs a bilingual dictionary
  look-up to determine the words' meanings in the
  target language, performs a local reordering to
  fit the grammar structure of the target language,
  and produces the target language output. The
  problem with this approach is that it is
  essentially a word-for-word translation with some
  reordering, resulting often in mistranslations
  and incorrect grammar structures.

39
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• Furthermore, when creating a multilingual system,
  the direct approach would require several
  different translation algorithms - one or two for
  each language pair. The indirect approach
  involves some sort of intermediate representation
  of the source language before translating into
  the target language. In this way, linguistic
  analysis of the source language can be performed
  on the intermediate representation. Translating
  to the intermediary also enables semantic
  analysis, as the source language input can be
  more carefully to detect idioms, etc, which can
  be stored in the intermediary and then
  appropriately used to translate into the target
  language.

40
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• The transfer method is similar, except that the
  transfer is language dependent - that is to say,
  the French-English intermediary transfer would be
  different from the EnglishGerman transfer. An
  interlingua intermediary can be used for
  multilingual systems.
• Theory
• Humans fluent in two or more languages are at the
  moment better translators than the best machine
  translators in the world. Indeed, a person with
  three years of experience in learning a second
  language will already be a better translator than
  the best machine translators in the world as
  well.

41
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• Yet for humans and machines alike, translation is
  a process, a series of steps that must be
  followed in order to produce a successful
  translation. It is interesting to note, however,
  that the various methods of translation for
  machines - the various processes - become less
  and less like the process for humans as they
  become more complicated. Furthermore, it was
  interesting to notice that as the method of
  machine translation becomes more complicated, the
  results are sometimes less accurate than the
  results of simpler methods that better model the
  human rationale for translation.

42
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• Therefore, the theory is, an algorithm that
  attempts to model the human translation process
  would be more successful than other, more
  complicated methods currently in development
  today. This theory is not entirely plausible for
  full-scale translators because of the sheer
  magnitude of data that would be required. Humans
  are better translators than computers in part
  because they have the ability to perform semantic
  analysis, because they have the necessary
  semantic information to be able to, for example,
  determine the difference in a word's definition
  based on its usage in context. Creating a
  translator with a limited-scope of vocabulary
  would require less data, leaving more room for
  semantic information to be stored along with
  definitions.

43
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• A limited-scope translator may seem unuseful at
  first glance, but even humans fluent in any
  language, including their native language, don't
  know the entire vocabulary of the language. A
  language has hundreds of thousands of words, and
  no human knows even half of them all. A computer
  with a vocabulary of commonly used words that
  most people know, along with information to avoid
  semantic problems, would therefore be still
  useful for nonprofessional work.
• Development
• On the most superficial level, a translator is
  more user-friendly for an average person if it is
  GUI-based, rather than simply text-based. This
  part of the development is finished. The program
  presents a GUI for the user.

44
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• A JFrame opens up with two text areas and a
  translate button. The text areas are labeled
  "English" and "German". The input text is typed
  into the English window, the "Translate" button
  is clicked, and the translator, once finished,
  outputs the translated text into the German text
  area. Although typing into the German text area
  is possible, the text in the German text area
  does not affect the translator process. The first
  problem to deal with in creating a machine
  translator is to be able to recognize the words
  that are inputted into the system. A sentence or
  multiple sentences are input into the translator,
  and a string consisting of that entire sentence
  (or sentences) is passed to the translate()
  function.

45
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• The system loops through the string, finding all
  space (' ') characters and punctuation characters
  (comma, period, etc) and records their positions.
  (It is important to note the position of each
  punctuation mark, as well as what kind of a
  punctuation mark it is, because the existence and
  position of punctuation marks alter the meaning
  of a sentence.)
• The number of words in the sentence is determined
  to be the number of spaces plus one. By recording
  the position of each space, the string can then
  be broken up into the words. The start position
  of each word is the position of each space, plus
  one, and the end position is the position of the
  next space. This means that punctuation at the
  end of any given word is placed into the String
  with that word, but this is not

46
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• a problem the location of each punctuation mark
  is already recorded, and the dictionary look-up
  of each word will first check to ensure that the
  last character of each word is a letter if not,
  it will simply disregard the last character. The
  next problem is the biggest problem of all, the
  problem of actual translation itself. Here there
  is no code yet written, but development of
  pseudocode has begun already. As previously
  mentioned, translation is a process. In order to
  write a translator program that follows the human
  translation process, the human process must first
  be recognized and broken down into programmable
  steps. This is no easy task. Humans with five
  years of experience

47
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• in learning a language may already translate any
  given text quickly enough, save time to look up
  unfamiliar words, that the process goes by too
  quickly to fully take note of. The basic process
  is not entirely determined yet, but there is some
  progress on it. The process to determine the
  process has been as followed given a random
  sentence to translate, the sentence is first
  translated by a human, then the process is noted.
  Each sentence given has ever-increasing
  difficulty to translate.

48
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• For example the sentence, "I ate an apple," is
  translated via the following process 1) Find the
  sub ject and the verb. (I ate) 2) Determine the
  tense and form of the verb. (ate past,
  imperfekt form) a) Translate sub ject and verb.
  (Ich ass) (note - "ass" is a real German verb
  form.) 3) Determine what the verb requires. (ate
  - eat requires a direct ob ject) 4) Find what
  the verb requires in the sentence. (direct ob
  ject comes after verb and article apple) 5)
  Translate the article and the direct ob ject.
  (ein Apfel) 6) Consider the gender of the direct
  ob ject, change article if necessary. (der Apfel
  ein - einen) Ich ass einen Apfel.

49
Natural Language Processing Using Machine
Translation in Creation of a German-English
TranslatorJason Ji

• References
• (I'll put these in proper bibliomumbo
  jumbographical order later!)
• 1. http//dict.leo.org (dictionary) 2. "An
  Introduction To Machine Translation" (available
  online at http//ourworld.compuserve.com/homepages
  /WJHutchins/IntroMT-TOC.htm) 3.
  http//www.comp.leeds.ac.uk/ugadmit/cogsci/spchlan
  /machtran.htm (some info on machine translation)
  4.

50
A Study of Balanced Search TreesThis project
investigates four different balanced search trees
for their advantages anddisadvantages, thus
ultimately their efficiency. Runtime and memory
space management are two main aspects under the
study. Statistical analysis is provided to
distinguish subtledifference if there is any. A
new balanced search tree is suggested and
compared with the four balanced search trees.
50
51
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Abstract
• This project investigates four different balanced
  search trees for their advantages and
  disadvantages, thus ultimately their efficiency.
  Run time and memory space management are two main
  aspects under the study. Statistical analysis is
  provided to distinguish subtle differences if
  there is any. A new balanced search tree is
  suggested and compared with the four balanced
  search trees under study. Balanced search trees
  are implemented in C extensively using pointers
  and structs.

52
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Introduction
• Balanced search trees are important data
  structures. A normal binary search tree has some
  disadvantages, specifically from its dependence
  on the incoming data, that significantly affects
  its tree structure hence its performance. Height
  of search tree is the maximum distance from the
  root of the tree to a leaf. An optimal search
  tree is one that tries to minimize its height
  given some number of data. To improve its height
  thus its efficiency, balanced search trees have
  been developed that self-balance themselves into
  optimal tree structures that allows quicker
  access to data stored in the trees, For example
  red-black treee is a balanced binary tree that
  balances according to color pattern of nodes (red
  or black) by rotation functions.

53
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Rotation function is a hall mark of nearly all
  balanced search tree they rotate or adjust
  subtree heights from a pivot node. Many balanced
  trees have been suggested and developed
  red-black tree, AVL tree, weight-balanced tree, B
  tree, and more.

54
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Background Information
• Search Tree Basics
• This pro ject requires a good understanding of
  binary trees and general serach tree basics. A
  binary tree has nodes and edges. Nodes are the
  elements in the tree and edges represent
  relationship between two nodes. Each node in a
  binary tree is connected by edgesto zero to two
  nodes. In general search tree, each node can have
  more than 2 nodes as in the case of B-tree. The
  node is called a parent and nodes connected by
  edges from this parent node are called its
  children. A node with no child is called a leaf
  node. Easy visualization of binary tree is a real
  tree put upside down on a paper with roots on the
  top and branches on the bottom.

55
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• The grandparent of a binary tree is called root.
  From the root, the tree branches out to its
  immediate children and subsequent descendents.
  Each node's children are designated by left child
  and right child. One property of binary search
  tree is that the value stored in the left child
  is less than or equal to the value stored in
  parent. The right child's value is, on the other
  hand, greater than the parent's. (Lef t lt
  Parent, P arent lt Right)

56
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 3.2 Search Tree Functions
• There are several main functions that go along
  with binary tree and general search trees
  insertion, deletion, search, and traversal. In
  insertion, a data is entered into the search
  tree, it is compared with the root. If the value
  is less than or equal to the root's then the
  insertion functino proceeds to the left child of
  the root and compares again. Otherwise the
  function proceeds to the right child and compares
  the value with the node's. When the function
  reaches the end of the tree, for example if the
  last node the value was compared with was a leaf
  node, a new node is created at that position with
  the new inserted value. Deletion function works
  similarly to find a node with the value of
  interest (by going left and right accordingly).

57
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Then the funciton deletes the node and fixes the
  tree (changing parent children relationship etc.)
  to keep the property of binary tree or that of
  general search tree. Search function or basically
  data retrieval is also similar. After traversing
  down the tree (starting from the rot), two cases
  are possible. If there is a value in interest is
  encountered on the traversal, then the functino
  replys that there is such data in the tree. If
  the traversal ends at a leaf node with no
  encounter of the value in search, then the
  function simply returns the otherwise. There are
  three kinds of travesal functions to show the
  structure of a tree preorder, inorder and
  postorder.

58
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• They are recursive functions that print the data
  in special order. For example in preorder
  traversal, as the prefix pre suggests, first the
  value of node is printed then the recursive
  repeats to the left subtree and then to the right
  subtree. Similary, in inorder traversal, as the
  prefix in suggests, first the left subtree is
  output, then the node's value, then the right
  subtree. (Thus the node's value is output in the
  middle of the function.) Same pattern applies to
  the postorder transversal.

59
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 3.3 The Problem
• It is not hard to see that the structure of a
  binary search tree (or general search tree) that
  the order of data input is important. In a
  optimal binary tree, the data are input so that
  insertion occurs just right which makes the tree
  balanced, the size of left subtree is
  approximately equal to the size of right subtree
  at each node in the tree. In an optimal binary
  tree, the insertion, deletion, and search
  function occur in O(log N ) with N as the number
  of data in the tree. This follows from that
  whenever data comparison occurs and subsequent
  traversal (to the left or to the right) the
  number of possible subset divides in half at each
  turn. However that's only when the input is
  nicely ordered and the search tree is balanced.

60
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• It's also possible that the data are input so
  that only right nodes are added. (Root- gt right-
  gt right- gt right...)It's obvious that the search
  tree now looks like just a linear array. And it
  is. And this give O(N ) to do insertion, deletion
  and search operation. This is not efficient. Thus
  search trees are developed to perform its
  functions efficiently regardless of data input.
• 4 Balanced Search Trees
• Four ma jor balanced search trees are
  investigated. Three of them, namely red-black
  tree, height-balanced tree, and weight-balanced
  tree are binary search trees. The fourth, B-tree,
  is multiple children (gt 2) search tree.

61
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 4.1 Red-black tree
• Red-black search tree is a special binary with a
  color scheme each node is either black or red.
  There are four properties that makes a binary
  tree a red-black tree. (1) The root of the tree
  is colored black. (2) All paths frmo the root to
  the leaves agree on the number of black nodes.
  (3) No path from the root to a leaf may contain
  two consecutive nodes colored red. (4) Every path
  from a node to a leaf (of the descendents) has
  the same number of black nodes. The performance
  of balanced search is directly related to the
  height of the balanced tree. For a binary, lg
  (number of nodes) is usually the optimal height.
  In the case of Red-black tree with n nodes, it
  has height at most 2lg (n 1). The proof is
  noteworthy, but difficult to understand.

62
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• In order the prove the assertion that Red-black
  tree's height is at most 2lg (n 1) we should
  first define bh(x). bh(x) is defined to be the
  number of black nodes on any path from, but not
  including a node x, to a leaf.Notice that black
  height (bh) is well defined under the property 2
  of Red-black tree. It is easy to see that black
  height of a tree is the black height of its root.
  First we shall prove that the subtree rooted at
  any given node x contains at least ( 2 bh(x)) - 1
  nodes. We can prove this by induction on the
  height of a node x The base case is bh(x) 0,
  which suggests that x must be a leaf (NIL). This
  is true then it follows that subtree rooted at x
  contains 20 - 1 0. The following is the
  inductive step. Let say node x has positive
  height and has two children.

63
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Note that each child has a black-height of either
  bx(x), if it is a red node, or bh(x)-1, if it is
  a black node. It follows that the subtree rooted
  at xcontains at least 2(2( bh(x)) - 1 - 1) 1
  2( bh(x)) - 1. The first term refers to the
  minimum bounded by the sum of black height left
  and right. and the second term (the 1) refers to
  the root. Doing some algedra this leades to the
  right side of the equaiton. Having proved this
  then the maximum height of Red-black tree is
  fairly straightforward method. Not Let h be the
  height of the tree. Then by property 3 of
  Red-black tree, at least half of the nodes on any
  simple path from the root to a leaf must be
  black. So then the black-height of the root must
  be at least h/2. n gt 2( h/2) - 1 which is
  equivalent to n gt 2( bh(x)) - 1 n 1 gt 2( h/2)
  lg (n 1) gt lg (2( h/2)) h/2 h lt 2lg (n 1)
  4

64
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Therefore we just proved that a red-black tree
  with n nodes has height at most 2lg (n 1).
• 4.2 Height Balanced Tree
• Height balanced tree is a different approach to
  bound the maximum height of a binary search tree.
  For each node, heights of left subtree and right
  subtree are stored. The key idea is to balance
  the tree by rotating around a node that has
  greater than threshold height difference between
  the left subtree and the right subtree. All boils
  down to the following property (1) At each node,
  the difference between height of left subtree and
  height of right subtree is less than threshold
  value. Height balanced tree should yield lg (n)
  height depends on the threshold value.

65
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• An intuitive, less rigorous and yet valid proof
  is provided. Imagine a simple binary tree in the
  worst case scenario, a line of nodes. If the
  simple binary tree were to be transformed into a
  height balanced tree, the following process
  should do it. (1) Pick some node near the middle
  of a given strand of nodes so that the threshold
  property satisfies (absolute value(leftH () -
  rightH ())) (2) Define this node as a parent and
  the resulting two strands (nearly equal in
  length) as leftsubtree and rightsubtree
  appropriately. (3) Repeat steps (1) and (2) on
  the leftsubtree and the rightsubtree. First note
  this process will terminate. It's because at each
  step, the given strand will be split in two
  halves smaller than the original tree. So this
  shows the number of nodes in a given strand will
  decrease.

66
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• This will eventually reach a terminal size of
  nodes determined by the threshold height
  difference. If a given strand is impossible to
  divide so that the threshold height difference
  holds, then that is the end for that sub
  recursive routine. Splitting into two halves
  recursively is analogous to dividing a mass into
  two halves each time. Dividing by 2 in turn leads
  to lg (n). So it follows the height of
  height-balanced tree should be lg (n), or
  something around that magnitude. It is
  interesting to note that height balanced tree is
  roughly complete binary tree. This is because
  height balancing allows nodes to gather around
  the top. There is probably a decent proof for
  this observation, but simple intuition is enough
  to see this.

67
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 4.3 Weight Balanced Tree
• Weight balanced tree is very similar to height
  balanced tree. It is very the same idea, but just
  different nuance. The overall data structure is
  also similar. Instead of heights of left subtree
  and right subtree, weights of left subtree and
  right subtree are kept. The weight of a tree is
  defined as the number of nodes in that tree. The
  key idea is to balance the tree by rotating
  around a node that has greater than threshold
  weight difference between the left subtree and
  the right subtree. Rotating around a node shifts
  the weight balance to a favorable one,
  specifically the one with smaller difference of
  weights of left subtree and right subtree. Weight
  balanced tree has the following main property
  (1) At each node, the difference between weight
  of left subtree and weight of right subtree is
  less than the threshold value.

68
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Similar approach used to prove height balanced
  tree is used to show lg (n) of weight balanced
  tree. The proof uses mostly intuitive argument
  built on recursion and induction. Transforming a
  line of nodes, the worst case scenario in a
  simple binary tree, to a weight balanced tree can
  be done by the following steps. (1) Pick some
  node near the middle of a given strand of nodes
  so that the threshold property satisfies
  (absolutev alue(lef tW () - rig htW ())) (2)
  Define this node as a parent and the resulting
  two strands (nearly equal in length) as
  leftsubtree and rightsubtree appropriately. (3)
  Repeat steps (1) and (2) on the leftsubtree and
  the rightsubtree. It is easy to confuse the
  first step in height balanced tree and weight
  balanced tree, but picking the middle node surely
  satisfies both the height balanced tree property
  and weight balanced tree.

69
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Maybe the weight balanced tree property is well
  defined, since the middle node presumably has
  same number of nodes before and after its
  position. This process will terminate. It's
  because at each step, the given strand will be
  split in two halves smaller than the original
  strand. So this shows the number of nodes in a
  given strand will decrease. This will eventually
  reach a terminal size of nodes determined by the
  threshold weight difference. Splitting into two
  halves recursively is analogous to dividing a
  mass into two halves each time. Dividing by 2 in
  turn leads to lg (n). So it follows the height of
  weight-balanced tree should be lg (n), or
  something around that magnitude. Like height
  balanced tree, weight balanced tree is roughly
  complete binary tree.

70
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• A New Balanced Search Tree(?)
• A new balanced search tree has been developed.
  The binary tree has no theoretical value to
  computer science, but probably has practical
  value. The new balanced search tree will referred
  as median-weight-mix tree for each node will have
  a key, zero to two children, and some sort of
  weight.
• 5.1 Background
• Median-weight-mix tree probably serves no
  theoretical purpose because its not perfect. It
  has no well defined behavior that obeys a set of
  properties. Rather it serves practical purpose
  mostly likely in statistics.

71
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Median-weight-mix tree is based on following
  assumption in data processing (1) Given lower
  bound and upper bound of total data input, random
  behavior is assumed, meaning data points will be
  evenly distributed around in the interval. (2)
  Multiple bells is assumed to be present in the
  interval. The first property is not hard to
  understand. This is based on the idea that nature
  is random. The data points will be scatter about,
  but evenly since random means each data value has
  equal chance of being present in the data input
  set. An example of this physical modeling would
  be a rain. In a rain, rain drops fall randomly
  onto ground. In fact, one can estimate amount of
  rainfall by sampling a small area.

72
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Amount of rain is measured in the small sampling
  area and then total rail fall can be calculated
  by numerical pro jection, ratio or whatever
  method. The total rain fall would be
  rainfall-in-small-area area-of-totalarea /
  area-of-small-area. The second assumption is
  based upon less apparent observation. Nature is
  not completely random, which means some numbers
  will occur more often than others. When the data
  values and the frequency of those data values are
  plotted on 2D plane, a wave is expected. There
  are greater hits in some range of data values
  (the crests) than in other range of data values
  (the trough). A practical example would be
  height. One might expect well defined
  bell-shaped curve based on the average
  height.(People tends to be 5 foot 10 inches.) But
  this is not true when you look at it global
  scale, because there are isolated populations
  around the world. The average height of Americans
  is not necessarily the average height of Chinese.
  So this wave shaped curve is assumed.

73
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 5.2 Algorithm
• Each node will have a key (data number), an
  interval (with lower and upper bounds of its
  assigned interval) and weights of left subtree
  and right subtree. The weights of each subtree
  are calculated is based on constants R and S.
  Constant R represents the importance of focusing
  frequency heavy data points. Constant S
  represents the importance of focusing frequency
  weak data points. So the ratio R/S consequently
  represents the relative importance of frequency
  heavy vs. frequency weak data points. Then tree
  will be balanced to adjust to a favorable R/S
  ratio at each node by means of rotating, left
  rotating and right rotating.

74
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 6 6.1 Methodology
• Idea
• Evaluating binary search trees can be done in
  various ways because they can serve number of
  purposes. For this pro ject, a binary search tree
  was developed to take some advantage of random
  nature of statistics with some assumption.
  Therefore it is reasonable to do evaluation on
  this basis. With this overall purpose, several
  behaviors of balanced search trees will be
  examined. Those are (1) Time it takes to process
  a data set (2) Average time retrieval of data (3)
  Height of the binary tree The above properties
  are the ma jor ones that outline the analysis.
  Speed is important and each binary tree is timed
  to check how long it takes to process input data.
  But average time retrieval of data is also
  important because it is best indication of
  efficiency of the data structures. What is the
  use when you can input a number quick but
  retrieve it slow? Lastly, height of the binary
  tree is check to see if how theoretical idea
  works out in practical situation.

75
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• 6.2 Detail
• It is worthwhile to note how each behaviors are
  measured in C. For measuring time it take to
  process a data set, the starting time and the
  ending time will be recorded by function clock ()
  under time.h library. Then the time duration will
  be (End-Time - StartTime) / CLOCKS PER SEC. The
  average time retrieval of data will be calculated
  by first summing time it takes check each data
  points in the tree and dividing this sum by the
  number of data points in the binary tree. Height
  of the binary tree, the third behavior under
  study, is calculated by tree traversal, pre-, in-
  or post-order, by simply taking the maximum
  height/depth visited as each node is scanned.
  There will be several test cases (identical) to
  check red-black binary tree, height-balanced
  tree, weight-balanced tree, and median-weight-mix
  tree. First category of test run will be test
  cases with gradually increasing number of
  randomly generated data points. Second category
  of test run will be hand manipulated.

76
A Study of Balanced Search Trees Brainforming a
New Balanced Search TreeAnthony Kim

• Data points will still be randomly generated
  however under some statistical behaviors, such a
  "wave," a single bell curve, etc. Third category
  of test run will be real life data points such as
  heights, ages, and others. Due to immense amount
  of data, some proportional scaling might be used
  to accommodate the memory capability of the
  balanced binary trees.
• 7 Result Analysis
• C codes of the balanced search trees will be
  provided. Testing of balanced search trees for
  their efficiency and such. Graphs and table will
  be provided. Under construction
• 8 Conclusion Under Construction 9 Reference
  Under Construction http//newds.zefga.net/snips/Do
  cs/BalancedBSTs.html
• App endix A Other Balanced Search Trees App
  endix B Co des

77
Linux Kernel Debugging APIThe purpose of this
project is to create an implementation of much of
the kernel API that functions in user space, the
normal environment that processes run in. The
issue with testing kernel code is that the live
kernel runs in kernel space, a separate area that
deals with hardware interaction and management of
all the other processes. Kernel spacedebuggers
are unreliable and very limited in scope a
kernel failure can hardly dump useful error
information because there's no operating system
left to write that information to disk.
77
78
Kernel Debugging User-Space API Library (KDUAL)
John Livingston

• Abstract
• The purpose of this project is to create an
  implementation of much of the kernel API that
  functions in user space, the normal environment
  that processes run in. The issue with testing
  kernel code is that the live kernel runs in
  kernel space, a separate area that deals with
  hardware interaction and management of all the
  other processes. Kernel space debuggers are
  unreliable and very limited in scope a kernel
  failure can hardly dump useful error information
  because there's no operating system left to write
  that information to disk. Kernel development is
  quite likely the most important active project in
  the Linux community.

79
Kernel Debugging User-Space API Library (KDUAL)
John Livingston

• Any aids to the development process would be
  appreciated by the entire kernel development
  team, allowing them to do their work faster and
  pass changes along to the end user quicker. This
  program will make a direct contribution to kernel
  developers, but an indirect contribution to every
  future user of Linux.
• Introduction and Background
• The Linux kernel is arguably the most complex
  piece of software ever crafted. It must be held
  to the most stringent standards of performance,
  as any malfunction, or worse, security flaw,
  could be potentially fatal for a critical
  application. However, because of the nature of
  the kernel and its close interaction with
  hardware, it's extremely difficult to debug
  kernel code.

80
Kernel Debugging User-Space API Library (KDUAL)
John Livingston

• The goal of this pr