process of Engineering: chronological order

• User Interviews + User Stories
• Requirements Analysis
• Documentation and Specification
• Build the damned thing
  • Project Management and Development Methodology (SDLC)
  • Task Estimation
  • Software Design and Architecture Patterns
  • Testing
• Build and Release engineering (TODO)

Other topics

• Query optimization (TODO)

Fucking acronyms to know

• AAA Method
• SOLID principles
• STAR method: state behaviorals in Situation, Task, Action, Results

fundamental trade-off of Software Engineering

The MIT vs. New Jersey problem: in Software Engineering, you can only choose one of FAST or ROBUST.

This will have no explicit boundary conditions in \(x\)!

Assume \(|U(t,x)|\) decays quickly as \(|x| \to \infty\).

Apply Fourier Transform

Step one is to apply the Fourier Transform on our PDE

\begin{equation} \hat{U}(t, \lambda) = \int_{R} U(t,x) e^{-i\lambda x} \dd{x} \end{equation}

Leveraging the fact that Derivative of Fourier Transform is a multiplication, we can simply our Fourier transform in terms of one expression in \(x\).

Apply a Fourier Transform on \(f(x)\)

This allows you to plug the initial conditions into your transformed expression above.

So let’s say given a system:

\begin{equation} \begin{cases} x + 2y + z = 0 \\ 2x + 0y - z = 1 \\ x - y + 0z = 2 \end{cases} \end{equation}

We can represent this using a matricies.

\begin{equation} \begin{pmatrix} 1 & 2 & 1 \\ 2 & 0 & -1 \\ 1 & -1 & 0 \end{pmatrix} \begin{pmatrix} x \\ y \\ z \end{pmatrix} = \begin{pmatrix} 0 \\ 1 \\ 2 \end{pmatrix} \end{equation}

• “laws.als”: “drumuomup”
• “ping.als”: “walking down the street, eating children”""
• “planets.als”: “sing a song among the starlight”
• “songs.als”: “thank you klint for your discussion”

Other things I have to finish

• “Tunel2.als”

qsort: sort an array of any type

bsearch binary search of an array of any type

lfind: linear search in a array of any find

lsearch: lfind, but perform insertion as well