2025-01-08 13:50:24

.obsidian/workspace.json

@@ -11,10 +11,14 @@
             "id": "a4868a0d0ec2cb3a",
             "type": "leaf",
             "state": {
-              "type": "empty",
-              "state": {},
+              "type": "markdown",
+              "state": {
+                "file": "UNB/Year 5/Semester 2/CS3383/Lecture Notes.md",
+                "mode": "source",
+                "source": false
+              },
               "icon": "lucide-file",
-              "title": "New tab"
+              "title": "Lecture Notes"
             }
           }
         ]
@@ -161,8 +165,10 @@
       "obsidian-git:Open Git source control": false
     }
   },
-  "active": "46a6eee907728856",
+  "active": "a4868a0d0ec2cb3a",
   "lastOpenFiles": [
+    "UNB/Year 5/Semester 2/CS3383/Lecture Notes.md",
+    "UNB/Year 5/Semester 2/CS3383",
     "UNB/Year 5/Semester 2",
     "UNB/Year 5/Semester 1/CS3113/Exam Review.md",
     "UNB/Year 5/Semester 1/HIST1001/Exam Stuff.md",

UNB/Year 5/Semester 2/CS3383/Lecture Notes.md

@@ -0,0 +1,6 @@
+### Running Time
+Most Algorithms transform input objects into output objects. The running time typically grows with the input size. Average case time is often difficult to determine. We focus on the worst case running time, as it's easier to analyze and its crucial to applications such as games, finance, and robotics.
+### Space Complexity
+In algorithms, you need to think about the amount of space, memory, that you need to compute the algorithm. 
+### Algorithm Structure?
+Need to think about how complex an algorithm is in implementation, the simpler the better. Code organization is also important in the structure.