Summary of Cross-level Requirement Traceability: a Novel Approach Integrating Bag-of-words and Word Embedding For Enhanced Similarity Functionality, by Baher Mohammad et al.
Cross-level Requirement Traceability: A Novel Approach Integrating Bag-of-Words and Word Embedding for Enhanced Similarity Functionality
by Baher Mohammad, Riad Sonbol, Ghaida Rebdawi
First submitted to arxiv on: 20 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed approach automates requirement traceability by linking high-level business requirements with technical system requirements. A Bag of-Words (BOW) model and Term Frequency-Inverse Document Frequency (TF-IDF) scoring function represent each requirement. An enhanced cosine similarity uses word embedding representation to correct limitations. The method is evaluated on COEST, WARC(NFR), and WARC(FRS) datasets, showing significant efficiency improvements compared to existing methods, with an increase of approximately 18.4% in one dataset, measured by the F2 score. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper helps computers understand how different requirements are connected. This is important because it can make it easier for developers to create software that meets users’ needs. The new method uses special ways to look at words and sentences to match business goals with technical details. It works better than other methods on certain kinds of data, making it a useful tool for software development. |
Keywords
» Artificial intelligence » Bag of words » Cosine similarity » Embedding » Tf idf
