Abstract—Optical system management software has been migrating toward software-defined networking (SDN) methods and interfaces. The increased programmability of SDN promises greater flexibility, dynamic operation, and multivendor compatibility for optical systems. However, physical layer control systems are complicated by transmission engineering requirements, including quality of transmission, optical power stability, and multidomain service guarantees. These challenges and recent commercial and research efforts to address them are examined.
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Management of Implicit Requirements Data in Large SRS Documents: Taxonomy and Techniques
Implicit Requirements (IMR) identification is part of the Requirements Engineering (RE) phase in Software Engineering during which data is gathered to create SRS (Software Requirements Specifications) documents. As opposed to explicit requirements clearly stated, IMRs constitute subtle data and need to be inferred. Research has shown that IMRs are crucial to the success of software development. Many software systems can encounter failures due to lack of IMR data management. SRS documents are large, often hundreds of pages, due to which manually identifying IMRs by human software engineers is not feasible. Moreover, such data is evergrowing due to the expansion of software systems. It is thus important to address the crucial issue of IMR data management. This article presents a survey on IMRs in SRS documents with the definition and overview of IMR data, detailed taxonomy of IMRs with explanation and examples, practices in managing IMR data, and tools for IMR identification. In addition to reviewing classical and state-of-the-art approaches, we highlight trends and challenges and point out open issues for future research. This survey article is interesting based on data quality, hidden information retrieval, veracity and salience, and knowledge discovery from large textual documents with complex heterogeneous data.
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- Award ID(s):
- 2018575
- PAR ID:
- 10385907
- Date Published:
- Journal Name:
- ACM SIGMOD Record
- Volume:
- 51
- Issue:
- 2
- ISSN:
- 0163-5808
- Page Range / eLocation ID:
- 18 to 29
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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