Broadcast protocols are a crucial building block for some Agreement protocols. These are protocols used to reach an agreement on common values, action or datum in a distributed system through sending it in a message for other processes to accept it \cite{bracha1987asynchronous}. Byzantine processes are processes that hinder the network from reaching the agreement by sending malicious (malicious processes) or faulty messages(faulty processes).\newline \newline Many broadcast protocols for distributed systems have been presented, depending on the topology, synchronicity(the network is asynchronous or synchronous), etc. One of these protocols, we are going to refer to as Bracha-Dolev, has been presented in the paper Practical Byzantine Reliable Broadcast on Partially Connected Networks\cite{bonomi2021practical}. Bracha-Dolev protocol can be used to reach an agreement in at least 2f+1-connected, asynchronous network \cite{bonomi2021practical}.\newline The second protocol we're going to come across in this paper is a protocol we're going to refer to as Bracha-CPA. Both Bracha-Dolev and Bracha-CPA are built by combining two protocols. Bracha-Dolev is built through combining the protocol presented by Gabriel Bracha \cite{bracha1987asynchronous} and the protocol presented by Danny Dolev et al \cite{dolev1982efficient}. We're going to refer to these protocols with Bracha's and Dolev's protocol. Bracha-CPA is built combining Bracha's broadcast protocol and the protocol presented by Chiu-Yuen \cite{koo2004broadcast} called Certified Propagation Algorithm.\newline There are two important metrics when talking about broadcast protocol the first one is the average message complexity which is the average number of messages until all processes accept the message. The second is the average delivery time, which is the average time until all the processes deliver the message. This paper demonstrates that by applying some of the optimizations applied to Bracha-Dolev \cite{bonomi2019multi}, we can decrease the average message complexity of Bracha-CPA up to 20\%. the average delivery time doesn't seem to decrease. The paper will also demonstrate that CPA has the highest probability of succeeding on a network with a k-diamond or k-pasted graph when we have a maximum number of Byzantine nodes.

The most crucial choices a student will make is about which college and major they decide to join. Accord- ing to a statistical analysis performed by Koenig (2018) in the U.S. News World Report, majors such as Computer and information science, Engineering and Engineering technology yield the highest employment rates and salaries compared to other majors. In an article they wrote about the factors that influence youths career choices, Akosah-Twumasi (2018) argued that the knowledge of issues related to ’job security’ and ’salaries’ may pressure youth to choose a career path based on the benefits associated with a particular profession. This causes an influence in the decision making of a student who will not necessarily apply for a major they would enjoy doing, but instead their choice is going to shift to a more reliable major. Thus, many students will apply for studies such as Computer Science even though it might not be well-suited for them. Our team has been asked by the Delft University of Technology’s communication department to develop a Chatbot in order to help students with their decision making, and specifically students interested in the master program Embedded Systems. The communication department gave our team a set of requirements that needed to be fulfilled. The final product needed to be a chatbot with which it is possible to have a conversation on the Embedded Systems study program. It should coach the student into making a decision as well as be able to answer frequently asked questions. The chatbot needed to be accompanied by a content management system which should allow the communication department to modify some of the content of the chatbot as well as provide them with useful statistics about the interactions with the chatbot. Our team was also required to use the Rasa (2019) open source machine learning tool for conversational artificial intelligence as back-end of our chatbot system in order to provide feedback about this framework which might be used in future projects at TU Delft.