Description
1 Introduction
This problem set continues the development begun in Problem Set 4 of a simulator for a
population of simple agents attempting to reach consensus on a choice value. The PS4
assignment handout describes two different such agent algorithms: fickle and follow the
crowd. In PS4, you implemented a simulator for a collection of fickle agents.
In the PS5 assignment, you refactored the PS4 solution to add a number of new features.
In particular, you made Agent into a pure abstract class, you split off a new Population
class from the Simulator class, and you changed the method used for building the initial
population from the command line parameters.
In the PS6 assignment, you implemented new classes Block and Blockchain, and you
imported and perhaps modified demo classes SPtr and Serial.
The goal of this assignment is to simulate the blockchain consensus algorithm used
in Bitcoin cryptocurrency, sometimes called Nakamoto consensus, to see how consensus
gradually evolves.
2 Teaching Objectives
• Gain more experience in refactoring code to adapt it to new requirements.
• Learn how to factor out common code in a polymorphic class hierarchy.
• Find additional uses of delegation in order to keep functions close to the data members
that they need.
• Learn how objects of class Blockchain can be passed around freely in the simulator
without concern about storage management issues.
• Take a step closer to simulating a realistic blockchain consensus algorithm.
3 Problem
Integrate and extend your PS5 and PS6 solutions to result in a simulator for agents that
are attempting to agree on a blockchain rather than on a single bit. In particular, you will
need to do the following:
1. Find everywhere in your code from PS5 involved with reaching consensus on an a
0-1 value of type int. Change the value type instead to Blockchain. In particular,
the abstract virtual function choice() in Agent should now return a value of type
Blockchain rather than of type int.
2 Problem Set 7
2. Add a new abstract virtual function extend() to class Agent() that causes the agent
to extend its current blockchain and to make the extended blockchain its new choice.
This will apply to all agent classes, including Fickle and Crowd.
1
3. Add another agent class, Nakamoto, to model the Nakamoto algorithm’s rule of ignoring a new blockchain received from another agent unless the new chain is longer than
the current one, in which case the longer blockchain replaces the shorter one.
4. Add a new class AgentBase that is publicly derived from Agent and from which the
actual agents Fickle, Crowd, and Nakamoto will be publicly derived. The purpose of
AgentBase is to give a place for the data members and functions that are common to
all agents such as the agent’s current choice and the public functions choice() and
extend(). The reason for not putting these things directly in Agent is that Agent
is a pure abstract class, so it cannot be instantiatied and therefore also cannot have
data members.
5. Change Simulator to randomly decide at each step whether to perform an update()
operation or an extend() operation. It does this by calling dRandom() and comparing
the result to a new command line argument probExtend. In case it decides to simulate
an extend, it chooses an agent at random to perform the extend. Similarly, if it decides
to simulate the sending of a message, it works as in PS4 and PS5 by choosing a random
sender and a distinct random receiver for the simulated sending of a message.
6. Instead of running until consensus is reached, the new simulator will run
for maxRounds, which is a new command line argument that is passed to
Simulator::run() as a parameter. Thus, there is no longer any need for the functions and data members that were formerly involved in trying to determine whether
or not consensus had been reached, and if so, what the consensus value was. Rather,
at the end of the simulation, we’ll simply print out a list of agents with each agent’s
current choice.
7. The code in class Population that creates the population should now make a 3-way
choice between Fickle, Crowd, and Nakamoto. New command line parameters provide
the desired probabilities for each kind of agent. All agents, regardless of type, now all
start with copies of the same initial genesis Blockchain for their initial choice. The
genesis Blockchain contains a smart pointer that points to the genesis Block. The
genesis Block is unique in that its SPtr data member has both target and count set
to nullptr.
8. Population should also have functions extend(int receiver) and
sendMessage(int senter, int receiver) to translate between the simulator’s use of integers to identify agents and the agents themselves, which actually carry
out those operations. The agents in turn delegate some of the work to Blockchain
functions that were defined in PS6.
9. Modify main.cpp to accept the following command line arguments,
numAgents maxRounds probNak probFickle probExtend [seed]
where the arguments have the following meanings:
1This is intended to model what happens when a Bitcoin miner successfully solves the current proof-ofwork puzzle and is therefore allowed to add a set of transactions to the current blockchain.
Handout #9—December 3, 2018 3
numAgents The total number of agents (as before).
maxRounds The total number of simulation rounds to perform.
probNak The probability of selecting a Nakamoto agent when building the population.
probFickle The probability of selecting a Fickle agent when building the population.
probExtend The probability that the simulator chooses to simulate an extend() operation rather than a sendMessage() operation.
[seed] Optional seed for the random number generator (as before).
The probability of selecting a Crowd agent is 1.0 − probNak − probFickle. It is an
error if the result does not lie in the closed interval [0.0, 1.0].
10. Modify Population to have two print functions, one which prints the statistics as
in PS5 (but I’m now calling it printStats()), and one that prints out each agent’s
choice of blockchain, one per line (which is what I’m now calling print()). Naturally,
print() delegates the printing of an agent’s current choice to Blockchain::print().
A sample call on your simulator is given on the Zoo in /c/cs427/code/ps7/sample.sh,
along with the output from a run on my machine. To give a better idea of what the
simulator is doing, I have added print statements to the simulator to show what operation
is being performed at each step of the simulation. I’ve also added a print statement to
Population::extend() to print each new blockchain when it is first produced.
4 Programming Notes
1. There should be no public data members and no use of friend classes or functions.
2. Dynamic memory (allocated by new) should only be used in the following places:
(a) Within the furnished classes SPtr and Serial;
(b) For creating objects of type Block;
(c) For creating objects of type Agent and for creating the array of agents.
All Blockchain objects should be stack allocated.
3. The only delete statements outside of class SPtr should be to delete objects created
in case 2c above. You should not explicitly delete any blocks. They should be deleted
automatically by the SPtr objects that manage them.
4 Problem Set 7
5 Grading Rubric
Your assignment will be graded according to the scale given in Figure 1 (see below).
# Pts. Item
1. 3 All relevant standards from previous problem sets are followed regarding submission, identification of authorship on all files, and so forth. A
well-formed Makefile or makefile is submitted that specifies compiler
options -O1 -g -Wall -std=c++17. Running make successfully compiles
and links the project and results in an executable file blockchain. Each
function definition is preceded by a comment that describes clearly what
it does.
2. 2 Sample input and output files are submitted that show good coverage of
the parameter space, e.g., small inputs, large inputs, edge cases for the
probabilities (e.g., 0.0 and 1.0) as well as reasonable intermediate cases.
This is in addition to the furnished sample file.
3. 3 The program shows good style. All functions are clean and concise. Inline
initializations, inline functions, and const are used where appropriate.
Variable names are appropriate to the context. Programs are consistently
indented according to the course indenting style. Each class has a separate
.hpp file and, if needed, a separate .cpp file. However, it is acceptable
to group the three polymorphic agent classes together in the same .hpp
and .cpp files.
4. 2 The restrictions in section 4 are all obeyed.
5. 10 All of the functionality in section 3 is correctly implemented.
20 Total points.
Figure 1: Grading rubric.
