\documentclass[letterpaper,10pt]{article}
\usepackage{amssymb}
\usepackage{url}
% pagelayout
%header
%\setlength{\topmargin}{-0.5in}
\setlength{\headheight}{0in}
\setlength{\headsep}{0in}
%side margin
\setlength{\oddsidemargin}{0in}
\setlength{\evensidemargin}{0in}
% text size
\setlength{\textwidth}{6.5in}
\setlength{\textheight}{9in}
% footer
\setlength{\footskip}{.25in}

% define the title
\author{Phillip Green II}
\title{Meetings}
\begin{document}


Accounts\\
unbox.org/08ai13:philip/toe\\
unbox.org/08ai12:phillip/car\\
wisp:phillip/pillihp\\
system space: ssh stuff
/srv/bronze/phillip


Ous's Email: orawas@gmail.com\\

Rules for picking printing reading
Journal > conference > workshop >> webpage
recent > old
guru > outsider
review > result
short > long


\section*{2008-05-20}
\begin{itemize}
\item setup meeting time to be Tuesdays 1:30pm to 2:30pm
\item Meet with Ous on Thursday to figure out deltas between Star and Nova.
      \begin{itemize}
      \item look at group 12 code
      \item look at ous's code
      \end{itemize}
\item Reading
      \begin{itemize}
      \item Boehm book Ch2,5,front and back covers
      \item xomo ase paper
      \item keys paper
      \end{itemize}
\item check why ett isn't used in nova
\item scripts should use local tmp when autogenerating instead of writing to wisp dir
\end{itemize}

\section*{2008-05-27}
\begin{itemize}
\item concepts of research
      \begin{itemize}
      \item machine vs human when dealing with software cost estimation
      \item using search engines allow more flexibility when ``grading''.  programmers could be ``better than average'' (4-6) instead of 4.2
      \item doesn't require local calibration
      \end{itemize}
\item search engines
      \begin{itemize}
      \item modifications to keys
            \begin{itemize}
            \item keys-squared is the idea of biasing a portion of the next era's inputs based on the better choices of the current era
            \item greg's wiggle is choosing top 1 then 2 then 3 then \dots
            \end{itemize}
      \item radial basis function
      \item look on creating my own which works best for this domain
      \end{itemize}
\item User trials for estimation using nova
      \begin{itemize}
      \item talk to Kate, Sara, \dots
      \end{itemize}
\end{itemize}


\section*{2008-06-03}
no meeting

\section*{2008-06-12}
\begin{itemize}
\item updated NOVA TODO (google notebooks)
\item define interface to front-end
      \begin{itemize}
      \item input and outputs for ed
      \item output (xml)
      \item input (lisp, xml) ?
      \end{itemize}
\item need to research on my own (read more)
\item nova results for (all, osp, osp2, flight, ground) (compare to star)
\item design and implement a search engine
\item switch paperwork to have Dr. Menzies as my advisor
\end{itemize}

\section*{2008-06-17}
no meeting

\section*{2008-06-24}
cancelled meeting due to meeting at work

\section*{2008-06-26}
\begin{itemize}
\item make Dr. Menzies my supervisor
\item discussed project/application
\item inputs
      \begin{itemize}
      \item search engine (choice)
      \item case-study (user defined) 
      \item policy (user defined)
      \item runs?
      \end{itemize}
\item output
      \begin{itemize}
      \item results of a search engine
      \item order list of decisions
      \item scores of each decision (effort, months, threat, defects)
      \item calculations for each decision (median, spread)
      \end{itemize}
\item functional by July
\end{itemize}

\section*{2008-07-01}
\begin{itemize}
\item XML output to Ed
\item make meeting time with Ed
\item get code working on stuff
\item check results (star vs nova)
      \begin{itemize}
      \item defect removal is only worth it if 5 or 6
      \item check reduction amounts (final/original) (braile chart)
      \item better,faster,cheaper
            \begin{itemize}
            \item coefficents order (effort, defects, threats, months)
            \item BFC 1,1,1,1
            \item BF 0,2,0,2; RD=1.8
            \item FC 2,0,0,2; RD=0
            \item BC 2,2,0,0; RD=1.8
            \end{itemize}
      \item strategies
            \begin{itemize}
            \item /trunk/STAR/STAR\_Projects
            \item ksloc is a multipliers on any specified range
            \item find more in Dr. Menzies book
            \end{itemize}
      \end{itemize}
\item policy can be variable instead of 0/1.  value could be handled in scoring function to skew neighbors based on policy
\item update ase07 paper with nova numbers (copy file to /var/phillip/...)
\item get LC input format from us
      \begin{itemize}
      \item example: \url{http://unbox.org/wisp/var/ous/LC_comparo-data/data}
      \item code: \url{http://unbox.org/wisp/var/omid/star-vs-lc/}
      \end{itemize}
\item generate win-loss tables
\end{itemize}

\section*{2008-07-03}
\begin{itemize}
\item Dr. Menzies is leaving town July 19
\item LC output is multiple runs (1000) of final constraints
\item get code working on stuff
\item seesaw
      \begin{itemize}
      \item either pick (random) or find best state with attribute pushed to extreme
      \item \url{http://unbox.org/wisp/branches/nova1}
            \begin{itemize}
            \item seesaw - random
            \item seesaw2 - deterministic
            \end{itemize}
      \end{itemize}
\end{itemize}

\section*{2008-07-08}
\begin{itemize}
\item Create a single executable for Ed (Server based execution can be later if necessary)
\item rename google notebook to include name
\item "redo of run of baseline ; 1 line per run" ?WR
\item get output format from ous so that our results can be compared
      \begin{itemize}
      \item csv with columns
            \begin{itemize}
            \item project (case-study)
            \item policy
            \item minEnergy
            \item minEffort
            \item minMonths
            \item minThreats
            \item minDefects
            \item strategy (hohin)
            \item BFC
            \end{itemize}
      \item multiple runs per file
      \item code to compare output: timtoy in /var/ous
      \end{itemize}
\item ***Get ous LC output
\item ***add backtracker using t-test (speed)
\item ***
\item max scoreshould be correlated to kloc
      \begin{itemize}
      \item run 1000 sims (get make score)
      \item reset sead and re-run to get scores
      \end{itemize}
\item Get supervisor paper to Dr. Menzies, Dr. Atkins is CS graduate Coordinator
\item READING
      \begin{itemize}
      \item /var/omid/thesis - struggle to do calbration
      \item check references: Boehm, Briand, Demsar, Kitchenham, Jorgenson, Sheppard
      \item check references: Software Cost and Estimation
      \end{itemize}
\item Calibration
      \begin{itemize}
      \item effort/months: calibration from historical data (nasa93)
      \item defects calibration: generate random data where mean is 12 defects per 1000 kloc with stdev ~3
      \end{itemize}
\end{itemize}

\section*{2008-07-15}
\begin{itemize}
\item Back tracking - start at mi-n and work to beginning
\item case-studies and policies may have dependence
\item SF's can now go up to 6
\item get paperwork for Dr. Menzies
\item braile charts
\end{itemize}

\section*{2008-08-12}
\begin{itemize}
\item Why force rely to max? \\ 
The problem is that currently, defect removal methods (la,etat,Pt) are free.  
They will effect rely so that there is a feed back loop into cocomo.
\item risk weight need re-evaluated.
\item Fix for dr (la,etat,pr)
      \begin{itemize}
      \item rely = max(5, rely0 + max(la-3,0) + max(etat-3,0) + max(pr-3,0))
      \item tool = max(5, tool0 + max(aa-3,0) + max(etat-3,0))
      \item rely and tool go up if drs are high
      \item rely and tool could be higher than user constraints 
            (rely0 and tool0 will be constrainted by user)
      \end{itemize}
\item calibration 
      \begin{itemize}
      \item focus on effort,months,defects (ignore threats)
      \item effort uses a and b
      \item months uses c and d
      \item defects has multiple options
            \begin{itemize}
            \item 6 variables: defectRemoval r,d,c  and defectIntroduced r,d,c (weights)
            \item 3 variables: defectIntroduced r,d,c (weights)
            \item 2 variable defectRemoval and defectIntroducded
            \end{itemize}
      \end{itemize}
\item thesis extension (ROI)
      \begin{itemize}
      \item Ch4 huang paper
      \item Boehm value based software engineering (VBSE)
      \end{itemize}
\item thesis needs to be finished by November
\item thesis extension (ROI)
      \begin{itemize}
      \item /var/omid has latex thesis templates
      \item /var/STAR has latex files for STAR information
      \end{itemize}
\end{itemize}

\section*{2008-08-19}
\begin{itemize}
\item Correlation of a and b was apart of jpl, so it doesn't need to be taken account into for calibration.
\item Implement domain specific ROI for using jpl information from huang paper (averge time to fix a problem ~ 150 yr)
\item convert nasa93 from cocomo to cocomoII format
\item extensions to STAR
      \begin{itemize}
      \item calibration
      \item value based scoring
      \end{itemize}
\item nova is to be a suite of methods
      \begin{itemize}
      \item need user manual
      \item need programmers manual
      \end{itemize}
\item redo unit tests (giga monkeys)
\item calibrate with search
\item get results of BFC and LC (one search engine each: seesaw-r)
\item start thesis
\end{itemize}

\section*{2008-08-26}
\begin{itemize}
\item Read ``Avoid Drastic Change'' paper
\item Do LC comparison
\item Do Braile comparison
  \begin{itemize}
  \item wisp/var/tim/08/startracker
  \end{itemize}
\item do Baseline comparison
  \begin{itemize}
  \item baselineout similar to xomo101 or webnova output (charts with decisions)
  \end{itemize}
\item nova components
  \begin{itemize}
  \item simulation
  \item learning
    \begin{itemize}
    \item value-based scoring
    \end{itemize}
  \item calibration
  \item subcomponent: search engine comparison
  \end{itemize}
\item web-nova
  \begin{itemize}
  \item make attributes links to info pages at \url{http://sunset.usc.edu/research/COCOMOII/expert_cocomo/expert_cocomo2000.html}
  \item web interface needs to handle all three main components of nova
    \begin{itemize}
    \item simulation output will be quartile charts
    \end{itemize}
  \end{itemize}
\item meeting with Ed about nova-web
  \begin{itemize}
  \item input.xml needs kloc specified
  \item need to exampand input and output formats for simulation and calibration
  \item Ed needs a list of all attributes and default ranges
  \item components
    \begin{itemize}
    \item simulation
      \begin{itemize}
      \item input: attribute constraints, tuning parameters constraints, kloc constraints, score methods, number of runs
      \item output: scores
      \item process: webinputs to web, web creates xml, xml to lispapp, processing, xml to web, output conversion
      \end{itemize}
    \item learning
      \begin{itemize}
      \item input: attribute constraints, tuning parameters constraints, kloc constraints, evaluation method (value base, energy, bfc), search engine
      \item output: decisions with scores
      \item process: webinputs to web, web creates xml, xml to lispapp, processing, xml to web, output conversion
      \end{itemize}
    \item calibration
      \begin{itemize}
      \item input: attribute values, kloc values, score values, models to calibrate, search engine
      \item output: tuning parameters
      \item process: csv to web, web creates xml, xml to lispapp, processing, xml to web, output conversion
      \end{itemize}
    \item after meeting thoughts
      \begin{itemize}
      \item use cookies and add a copy-and-paste type feature in order to calibrate and use values to run learners, then use results in simulations
      \item define schema for xml input and output
      \item specify error output type
      \end{itemize}
    \end{itemize}
  \end{itemize}
\end{itemize}

\section*{2008-09-02}
\begin{itemize}
\item Results
\item Pages
\item Risk Exposure\\
\begin{tabular}{l@{=}l@{:}l}
$RE$ & $RE_m + RE_q$ & Risk Exposure \\
$RE_m$ & $PM \cdot M_c$ & Market Share Erosion Risk Exposure\\
$RE_q$ & $P(L) \cdot S(L)$ & Software Quality Investment Risk Exposure\\
$S_c$ & $\prod_{x}{C_s(x)}$ & Size of loss coefficient\\
$M_c$ & $\prod_{x}{C_m(x)}$ & Market Share Erosion Risk coefficient\\
$C_s(x)$ & $1 - C_m(x)$ & Attribute Curve relationship\\
$P(L)$ & $\frac{DR}{DR_{vl}}$ & Probability of loss do to unacceptable quality\\
$S(L)$ & $\log{(KLOC)} \cdot PM \cdot S_c$ & Size of loss do to unacceptable quality\\
\end{tabular}
\end{itemize}

\section*{2008-09-11}
\begin{itemize}
\item justifiy value based function (describe why certain choice/variables/methods were used)
\item make decision plots with energy/valuebased/xomo-scores first scoring by energy then by valuebased (2 sets of graphs)
\item lc comparision
\item disable zap because of augmented-em
\end{itemize}

\end{document}
