User:Velle~enwiki/Things not to forget

Web Services

 * distributed information systemyer
 * MEP
 * RPC
 * middleware
 * REST, Representational State Transfer, software architectural style for distributed hypermedia systems, coined by Roy Fielding, there are originally four principles
 * Web 2.0
 * Chimera
 * Structural computing
 * Layers and Tiers
 * presentation layer
 * application logic layer
 * resource management layer
 * MEP, message exchange pattern, used in SOAP
 * RPC, remote procedure call, a protocol for invoking procedures on other computers
 * SOAP, protocol for exchanging XML based messages over a network.
 * XML RPC, a protocol that encodes its calls in XML
 * CRUD Create Read Update Delete, refers to the basic operations of a database (I think data tier).
 * RDF.
 * Java Remote Method Invocation, Java RMI, noget de brugte i dDist, en form for RPC.

Security

 * security objective
 * confidentiality
 * authenticity
 * availability
 * security policy
 * threat model
 * security mechanism
 * cryptography
 * stenography
 * public-key vs. private-key vs. secret-key
 * ciphertext
 * exhaustive key search
 * c is used for the cipher text
 * m is used for the unencrypted message
 * The function E(m) is used for encrypting
 * The function D(c) is used for decrypting
 * A subfix after the E or D function is the key
 * while encrypting we use more than a message and a key, but also a random number or a nonce.

New words

 * instigator
 * eavesdropper
 * bias
 * zealous
 * governance
 * almanac
 * monetize

Miscellenous computer science

 * fork (software development)

Linear Algebra

 * algebraic structure
 * talomraade!!!, associativity, distributivity, commutativity, e.g. the natural numbers N = {1,2,3,4 ...} (N er sommetider ogsaa med 0)
 * ring, furthermore: 1-element, O-element, opposite element, e.g. the rational numbers Q (fractions) and the integer numbers Z = {... -2, -1, 0, 1, 2 ...}
 * field (legeme), furthermore: reciproc element
 * bijection, a transformation that is both injective and surjective.
 * kernel, the null space for a matrix. ker(A).
 * rank, of a matrix, the number of pivots when bringing A to row echelon form
 * row echelon form
 * reduced row echelon form
 * dimension of et subspace, the number of elements in a basis
 * basis of a subspace W, a minimum set of vectors that span W, can be infinite
 * null space,
 * vector space
 * finitely generated vector space
 * span
 * orthogonal vector, two vectors are orthogonal, denoted u _|_ v, if u dot v = 0
 * orthogonal matrix, a matrix A, where A^T * A = I
 * orthogonal complement of a subspace W, denoted W^(_|_), the set of all vectors orthogonal to every vector in W.
 * transposed matrix, maybe called the transponent
 * euclidian space
 * association for binary operators
 * associative
 * non associative
 * left associative, ( )
 * right associative, ( )
 * distributivity for binary operators
 * left-distributive x * (a + b) = (x*a) + (x*b)
 * right-distributive (a + b) * x = (a*x) + (b*x)
 * left-distributive, if both right- and left-distributive
 * schwarz inequality
 * triangle inequality
 * closure
 * perpendicularity
 * orthogonality
 * pivot
 * unit matrix
 * vector translation
 * biimplikation
 * minimal vs. minimum basis
 * field (legeme)
 * transformation vs. afbildning
 * phi lower case and upper case, how do you write a upper case phi in handwriting?
 * Lambda uppercase
 * quantifier, uppercase A turned upside down
 * mirrored E
 * onto, in the context of transformations
 * quadratic matrix
 * diagonal matrix
 * vector space
 * affine space
 * standard matrix representation
 * range
 * nullity
 * identity matrix
 * unit matrix
 * axiom
 * theorem
 * cofactor
 * expansion by minors
 * general expansion by minors

Can two vectors be orthonormal? The distributive law is applicable for algebra with two different binary operators with different precedence. Why are there no commutative property for scalar multiplication in def 3.1 of a Vector Space? The symbol U| hmmm, vertical, it means is a subset of when talking about sets. It means is a subspace when doing on a vectorspace V.

Proofs:
 * Theorem 3.1, pt. 1
 * det(A) = det(transposed(A))

Programming Languages

 * lambda calculus in Dk. lambda kalkylen vist nok
 * quantifier
 * type annotation
 * Haskell
 * currying
 * lazy evaluation