A Systematic Literature Survey for Detecting Ambiguity in SRS Using Artificial Intelligence
DOI:
https://doi.org/10.26438/ijcse/v6i12.383387Keywords:
Software Requirements Specification, Artificial Intelligence, Deep Learning, Ambiguity DetectionAbstract
Research in recent years has shown integration amongst the significant and dynamic areas of software engineering and semantic web engineering. The success of any software system is depending on how well it meets the requirements of the stakeholders. A software requirement specification written in natural languages, are basically ambiguous, which makes the documentation unclear. Due to unclear requirements, software developers develop software, which is different from the expected software based on the customer needs. Therefore, well documented requirements should be unambiguous and it is possible only when it has only one meaning.The main purpose of this research is to propose a technique that is able to detect ambiguity in software requirements specification document automatically using artificial intelligence. To validate the outcome of the proposed work, generated result of the proposed work will be evaluated and validated by making the comparison between the proposed prototype results, previous ambiguity detection framework and human-generated results to decide how the proposed work is more efficient and reliable for ambiguity detection.
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