Reference no: EM132394364

COMP1002 Data Structures and Algorithms Assignment, Semester 2, 2019, Department of Computing, Curtin University, Australia

1. Introduction

In practicals you have implemented and learned about a number of algorithms and ADTs and will be implementing more of these in the remaining practicals. In this assignment, you will be making use of this knowledge to implement a system to explore and compare a variety of ADT implementations. Feel free to re-use the generic ADTs from your practicals. However, remember to self-cite; if you submit work that you have already submitted for a previous assessment (in this unit or any other) you have to specifically state this. Do not use the Java implementations of ADTs - if in doubt, ask.

2. The Problem

This assignment requires the extension of your graph code to apply it to social network analysis. You will be simulating the spread of information (or disease) through a social network. In the network, at each time step, there will be a probability of "liking" a post, which will expose your followers to the information. Liking a post also gives a probability of "following" the original poster - making a direct connection to the original source. Sample input files are available.

Your program should be called SocialSim, and have three starting options:

• No command line arguments : provides usage information
• "-i" : interactive testing environment
• "-s" : simulation mode (usage: SocialSim -s netfile eventfile prob_like prob_foll)

When the program starts in interactive mode, it should show the following main menu:

(1) Load network

(2) Set probabilities

(3) Node operations (find, insert, delete)

(4) Edge operations (like/follow - add, remove)

(5) New post

(6) Display network

(7) Display statistics

(8) Update (run a timestep)

(9) Save network

You can structure the menu/UI differently, just make sure at least those options are included.

When running in simulation mode, you will give the input files and probabilities on the command line, then output (append) the simulation state and statistics for each "timestep" to a file (unique filename per run).

In interactive mode you should be able to display the following statistics/information:

• Posts in order of popularity
• People in order of popularity
• A person's record - #posts, #followers, #following etc.

Once you have a working program, you will investigate the behaviour of social networks, and the impact of their structure on their performance. This investigation will be written up as The Report.

Documentation and Report - You need to submit documentation in docx or pdf format.

Your Documentation will be minimum 2-4 pages (excluding UML and Javadocs) and should include the following:

• An overview of your code, explaining any questions that the marker may have. This is supplemented by the comments in your code. In general, if the marker is looking at your code and isn't sure why you have done something in that particular way, they will check your documentation to see if they can find an explanation.
• A UML Class diagram of your code.
• A description of any classes you have, you need to let us know not only what the purpose of that class is but why you chose to create it. As part of this, also identify and justify any places where it was possibly useful to create a new class but you chose not to, especially when it comes to inheritance.
• Justification of all major decisions made. In particular, when you choose an ADT, underlying data structure or an algorithm, you need to justify why you chose that one and not one of the alternatives. These decisions are going to be of extreme importance in this assignment.

The Report will follow the structure of a standard academic report or paper. It should be at least 4-6 pages long. Required sections are:

• Abstract: Explain the purpose of the report and state what you are investigating, and the outcomes/recommendations.
• Background: Discuss your approach to developing the simulation code, and the aspects of the simulation that you will be investigating.
• Methodology: Describe how you have chosen to profile and compare multiple runs of the simulation, and why. You should give some prediction of the expected "performance" of the aspects of your code you are investigating - this includes time complexity and/or memory usage. Include the commands, input files, outputs - anything needed to reproduce your results.
• Results: Present the results of your simulations, and what you discovered.
• Conclusion and Future Work: Give your conclusions and what further investigations could follow. Do the actual results match your prediction?

Attachment:- Data Structures and Algorithms Assignment File.rar