Software complexity refers to the factors that determine the complexity level of a software project. High complexity is caused by the many attributes used in the system and the complex logic relationships among these attributes and features. The increased complexity of software is undesirable and affects maintenance. Over the years, Software Engineering scholars recommended several metrics like Halstead metric, cyclomatic complexity, and line of code metrics to deal with the complexity. With the complexity increasing as time goes by, there is a need for better metrics that can evaluate software more effectively. This research aims to develop a metrics model to determine the features that cause high complexity in software design architectures and to implement the multi-language complexity evaluation model for software architectures. Although this is the case, the literature on complexity metrics that implement diagram-centric complexity measures are inadequate. This study presents the outcomes obtained from our survey on metrics utilized in object-oriented environments. The survey comprises a small set of the most common and frequently implemented software metrics, which could be adopted to a group of object-oriented metrics and object-oriented programming. After reviewing the literature, Findings indicate that metrics that employ diagram-centric complexity measures are lacking.