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content/notes/aymptotic-notation.md

@@ -10,7 +10,7 @@ Asymptotic notations are used in computer science to classify algorithms based h
 
 # big O notation
 
-Big O defines a bound for the *upper limit* of the running time (or space) of a algorithm. However, it is possible that the actual running time is much less as it does not take into account special cases
+Big O defines a bound for the *upper*  bound of the running time (or space) of a algorithm. However, it is possible that the actual running time is much less as it does not take into account special cases
 
 
 ## 1 Formal definition
@@ -20,7 +20,7 @@ $f(n) = O(g(n))$ if there is some constant $A$ such that $f(n) < A \times g(n)$
 
 # big theta notation
 
-Big theta defines an upper and a lower bound for a the running time (or space) of an algorithm. 
+Big theta defines an *upper and a lower* bound for a the running time (or space) of an algorithm. 
 
 
 ## 2 Formal definition

content/notes/big-theta-notation.md

@@ -1,18 +0,0 @@
----
-title: "big-theta-notation"
-tags: 
-- cosc201
----
-
-
-
-
->Big theta means $f(n) = \Theta(g(n))$ if there are constants 0 < B < A such that for all sufficiently large n, ==$B × g(n) ≤ f(n) ≤ A × g(n)$==
-
-- Upper and lower bound
-- $Θ$ says that $g(n)$ provides **upper** and **lower** bound for $f(n)$
-	- "selection sort is $\Theta(n^2)$" -> the maximum number of operations will be bounded both above and below by some constant times $n^2$
-- $f(n) = \Theta(g(n))$ means that f and g have similar growth rates
-- if $f(n) = \Theta(g(n))$ then the opposite is also true
-- usually $f(n)$ is complex but $g(n)$ is very simple
-

content/notes/cosc-201-outline.md

@@ -6,7 +6,6 @@ tags:
 ---
 
 - [[notes/aymptotic-notation]]
-- [[notes/big-theta-notation]]
 - [[notes/induction]]
 - [[notes/analysis-of-recursive-algorithms]]
 - [[notes/union-find]]
@@ -15,4 +14,3 @@ tags:
 - [[notes/heapsort]]
 - [[notes/mergesort]]
 - [[notes/quicksort]]
-

content/notes/cosc-202-outline.md

@@ -10,3 +10,10 @@ tags:
 - [[notes/ethics-in-cs]]
 - [[notes/integrated-development-environments]]
 - [[notes/branch]]
+- [[notes/testing]]
+- [[notes/test-driven-development]]
+- [[notes/unit-testing]]
+- [[notes/debugging]]
+- [[notes/documentation]]
+- [[notes/continuous-integration]]
+- 

content/notes/cosc-202.md

@@ -10,9 +10,9 @@ tags:
 - [[notes/cosc-202-lectures]]
 - [[notes/cosc-202-outline]]
 
-## 2 Assignments
+## 1 Assignments
 
 - 
 
-## 3 Resources
+## 2 Resources
 

content/notes/induction.md

@@ -33,7 +33,7 @@ Four parts
 e.g., 
 - we will prove that, for every non-negative integer $n$, *insert property here*
 - For $n = 0$, *The property* is true because *explicit verification of this case*
-- for any $n > 0$, assuming *the property* is true for $n-1$ (or, for all $k < n$), *the property* is true at $n$ because *explain why we can take a step up*
+- for any $n > 0$, assuming *the property*  is true for $n-1$ (or, for all $k < n$), *the property* is true at $n$ because *explain why we can take a step up*
 - Therefore, by induction, *the property* is true for all n.
 
 ### 1.3 Checking

content/templates/induction-proof-template.md

@@ -0,0 +1,7 @@
+We will prove that, for every non-negative integer $n$, *insert property here*
+
+For $n = 0$, *The property* is true because *explicit verification of this case*
+
+For any $n > 0$, assuming *the property*  is true for $n-1$ (or, for all $k < n$), *the property* is true at $n$ because *explain why we can take a step up*
+
+Therefore, by induction, *the property* is true for all n.