Within information system, faults can occur by the difference in understanding of the parties involved regarding the meaning of data. This is a well-known problem for software engineering and defects of this type have been responsible for catastrophic failures, such as the Mars Climate Orbiter in 1999. The current scenario of data processing and exchange, with high information traffic volume and heterogeneous participants, increases system’s vulnerability to these defects. Besides that, techniques of software quality assurance are typically oriented to data structure and physical properties, failing to efficiently address semantics issues. This work has the objective to evaluate the use of static analysis to detect semantic conflicts in data types, investigating its efficacy through an qualitative study comparing different software quality assurance approaches. The static analysis tool VERITAS (VERIficador esTÁtico Semântico) and the SemTypes notation were exclusively developed to address the problem of semantic conflicts - adding a semantic control to the types recognized by compilers – and are presented in this work.