In the realm of software engineering, understanding the architecture and measuringthe quality of a source code is essential for maintaining and enhancing softwaresystems. However, many existing tools fall short in evaluating architectural aspects,such as detecting architectural erosion or addressing architecture-related metrics andconstraints tailored to the unique context of their systems or organisations. Thisdeficiency restricts proactive architecture governance and hinders the mitigation ofarchitecture-related risks, creating a critical gap in the analysis of software sourcecode. This thesis presents a novel approach to tackle these challenges. It proposes a graphdatabase as a data structure for analysing the source code and architecture quality andcalculating various architectural metrics of interest. The tool developed in this thesisrepresents the source code structural elements and their relationships in the graphdatabase, enabling an intuitive analysis of the source code architecture. The tool also integrates different code quality metrics parsed from Visual Studiocode metrics results, mapped to their correspondent nodes to assess the source codeoverall quality and identify potential areas of improvement. This empowers softwareengineers and developers to make informed decisions regarding refactoring, codeoptimisation, and architectural enhancements. Furthermore, the tool allows users to define the intended architecture in terms ofmodules to reveal any Architecture erosion (AEr). It also provides the flexibility toestablish custom constraints and metrics through tailored queries, accommodating theunique requirements of their system and company. A case study conducted on a real-world software project validates the effectivenessand usefulness of the proposed approach. The case study demonstrates how the toolanalysis reveals valuable insights into the source code health and identifies patternsthat can impact maintainability and scalability. The results of this research showcasethe potential of our tool as a powerful instrument for analysing the code qualityand architecture of source code, fostering more resilient and sustainable softwaresystems.