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An important software engineering artifact used by developers and maintainers to assist in software comprehension and maintenance is source code documentation. It provides the insight needed by software engineers when performing a task, and therefore ensuring the quality of documentation is extremely important. Since software documentation is written in informal natural language, ensuring its quality needs to be performed manually. In this works, we present a novel and automated approach for assessing the quality of in-line documentation using Natural Language Processing (NLP), also known as Computational Linguistics. We gear our efforts towards targeting both the quality of the language used within API documentation, and determining the consistency between source source code and its comments.