Format README

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@@ -1,5 +1,7 @@
 # CSCI 4061: Project 1
 
+## Fall 2020
+
 test machine: apollo.cselabs.umn.edu
 date: 10/3/2020
 name: Andrea Smith , Matt Strapp
@@ -7,15 +9,17 @@ x500: smit9523, strap012
 
 The purpose of this program is to recreate the mapreduce programming model for Big Data Analytics. In order to compile this program, simply run the included Makefile, which takes no arguments.
 
-Program structure:
-mapreduce.c:
-    Mapreduce is the master phase of this program. It is responsible for calling the mapper and reducer processes. It will wait for each process to finish executing before exiting the code.
+#### Program structure
+
+```mapreduce.c:```
+Mapreduce is the master phase of this program. It is responsible for calling the mapper and reducer processes. It will wait for each process to finish executing before exiting the code.
+
+````mapper.c:```
+ Mapper receives a chunk of data and emits it into an intermediate data structure, which is a two-level linked list. writeIntermediateDS() formats the data, writing each word and its associated "1's" in the form "word 1 1 1..." to its own file, word.txt.
 
-mapper.c:
-    Mapper receives a chunk of data and emits it into an intermediate data structure, which is a two-level linked list. writeIntermediateDS() formats the data, writing each word and its associated "1's" in the form "word 1 1 1..." to its own file, word.txt.
+```reducer.c:```
+Reducer receives the word.txt files and "reduces" them into n files (where n is an input) containing the words and amount of 1's associated with the word in the format "word number_of_1's"
 
-reducer.c:
-    Reducer receives the word.txt files and "reduces" them into n files (where n is an input) containing the words and amount of 1's associated with the word in the format "word number_of_1's"
+#### Team Contributions:
 
-Team Contributions:
 As can be seen by the number of back-and-forth GitHub commits, this project was thoroughly a team effort. However, for the purposes of appropriating (what I am sure will be) praise from the professors and TA's (just kidding!), Matt wrote mapreduce, Andrea wrote reducer, and mapper was written by both of us.