<p>Cognitive diagnostic assessment (CDA) enables direct exploration of participants’ cognitive structures or psychological latent traits (referred to as attributes), offering unique advantages within psychological methodologies. The Q-matrix, which delineates the relationship between items and attributes in CDA, is crucial for accurate diagnosis. However, ensuring the accuracy of the Q-matrix in practical applications is often challenging. Constructing a Q-matrix typically requires extensive calibration efforts from both test developers and domain experts, and even then, issues of accuracy and subjectivity remain. Although various Q-matrix validation methods have been developed to improve its quality, their implementation often presents a steep technical barrier for typical psychological researchers. These challenges have limited the broader application of CDA in psychological research. This paper provides a systematic review of Q-matrix validation methods under saturated cognitive diagnosis models (CDMs) and introduces Qval, a user-friendly and powerful R package that offers a one-stop solution for implementing a wide range of state-of-the-art validation procedures, including parameter estimation, validation methods, iterative procedures, and search algorithms. The Qval package leverages C++ code and parallel computing to improve computational efficiency. Additionally, this paper provides detailed guidance on how to implement Q-matrix validation procedures effectively.</p>