student name: Yukang Yin

student email: [email protected] and [email protected]

student number: 300162143 (University of Ottawa)

Three search algorithms are implemented in this course project:

• naive binary search
• iterated searh
• fractional cascading

1. naive binary search solution is organized in naive_binary_search.py

2. iterated search solution is organized in iterated_search_node.py and iterated_search.py

3. fractional cascading search solution is organized in fractional_cascading_node.py and fractional_cascading.py

4. execution code is organized in main.py

1. define input arrays in main.py

   populate arr with valid input arrays, such as [[4, 6, 7, 8, 12], [1, 2, 5, 11, 15], [3, 9, 10, 13, 14]]

2. define query key in main.py

   populate query_key with valid query key, such as 11

3. initialize a search solution by passing input arrays into solution's constructor, such as

   fractional_cascading = FractionalCascading(arrs)
   

4. merge input arrays and calculate pointers, such as

   fractional_cascading.merge_input_arrs()
   fractional_cascading.calculate_pointers()
   

5. invoke search solution's find method by passing into query key, such as

   fractional_cascading.find(query_key)