  The ability of a system to meet its requirements is a strong determinant of
success. Thus effective requirements specification is crucial. Explicit
Requirements are well-defined needs for a system to execute. IMplicit
Requirements (IMRs) are assumed needs that a system is expected to fulfill
though not elicited during requirements gathering. Studies have shown that a
major factor in the failure of software systems is the presence of unhandled
IMRs. Since relevance of IMRs is important for efficient system functionality,
there are methods developed to aid the identification and management of IMRs.
In this paper, we emphasize that Common Sense Knowledge, in the field of
Knowledge Representation in AI, would be useful to automatically identify and
manage IMRs. This paper is aimed at identifying the sources of IMRs and also
proposing an automated support tool for managing IMRs within an organizational
context. Since this is found to be a present gap in practice, our work makes a
contribution here. We propose a novel approach for identifying and managing
IMRs based on combining three core technologies: common sense knowledge, text
mining and ontology. We claim that discovery and handling of unknown and
non-elicited requirements would reduce risks and costs in software development.
