DAOs have emerged as a novel approach to collective governance, facilitated by blockchain technology. However, the effectiveness and legitimacy of decision-making within DAOs can be compromised by low voter turnout. Given the limited lifespan of each proposal, conventional recommender system techniques are unsuitable. In response to these issues, this Master’s Thesis introduces a recommender system specifically designed for DAOs.

Decentralized Autonomous Organizations (DAOs) are a new kind of organization that relies on blockchain software to govern their projects. Typically, DAO members may put forward and vote on proposals. For instance these proposals may consist on someone doing some tasks in exchange for a share of the DAO crypto-funds. In recent times, DAOs have gained a remarkable adoption, and yet they are still understudied by the academic literature. In this work, we present a visual analytics tool to study DAO activity focusing on their participation and temporal evolution. Our tool will hopefully help to stimulate research on this new kind of online community and collaborative software.

Network on a Chip (NoC) is an emergent technology alternative to traditional inter connection methods, in which network design methods are applied to the connexions between modules. In this Final Degree Project, we apply this technology inside the execution unit of the RISC-V based processor SWerv-EL2. For this, we have studied in-depth and designed a NoC, trying to minimize the resources utilized and its impact on the core. Afterwards, we modified the execution unit of the core to include said network, using it to interconnect its submodules. In both cases, we used the hardware description language SystemVerilog.