Applying Machine Learning to Conflict Management in Software Requirement

Software requirements is a field within software engineering that deals with the establishing the needs of the stakeholders [1]. In this paper, the concern is about the new approach and techniques for incorporating precision and consistency in requirements specifications. Besides these software requirements should be ambiguity free and complete by all means. This paper also reviews the existing work about how the ambiguity can be resolved through machine learning algorithms that can learn from the data stored through especially through data analytics. Since Machine learning deals with the issue of how to build the programs that improve their performances at some task through experience and Machine learning algorithms has proven to be of great practical value in variety of application domains. This paper focuses on approach of existing applying machine learning algorithms and their methods to specify software requirements. General terms Artificial intelligence, Data analytics , Pattern recognition, Associative learning, ambiguity .