Supporting program comprehension using semantic and structural information
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Aspect-Oriented Requirements Engineering for Component-Based Software Systems
RE '99 Proceedings of the 4th IEEE International Symposium on Requirements Engineering
Recovering documentation-to-source-code traceability links using latent semantic indexing
Proceedings of the 25th International Conference on Software Engineering
Theme: An Approach for Aspect-Oriented Analysis and Design
Proceedings of the 26th International Conference on Software Engineering
Aspect-Oriented Analysis and Design
Aspect-Oriented Analysis and Design
IEEE Software
A Clustering Technique for Early Detection of Dominant and Recessive Cross-Cutting Concerns
EARLYASPECTS '07 Proceedings of the Early Aspects at ICSE: Workshops in Aspect-Oriented Requirements Engineering and Architecture Design
Aspect-oriented requirements engineering: a roadmap
Proceedings of the 13th international workshop on Early Aspects
A theory of aspects as latent topics
Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented programming systems languages and applications
Using information retrieval based coupling measures for impact analysis
Empirical Software Engineering
Proceedings of the 13th International Software Product Line Conference
Mining early aspects based on syntactical and dependency analyses
Science of Computer Programming
Cross-Document dependency analysis for system-of-system integration
Monterey'08 Proceedings of the 15th Monterey conference on Foundations of Computer Software: future Trends and Techniques for Development
Concept location using formal concept analysis and information retrieval
ACM Transactions on Software Engineering and Methodology (TOSEM)
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Aspect-oriented requirements analysis involves the identification of concerns that behaviorally influence other concerns. Such concerns are described in requirements called emphaspectual requirements: requirements that detail the influence of one concern over another. The current state of the art for aspect-oriented requirements analysis is Theme/Doc, which allows lexical analysis of requirements based on a set of developer-chosen keywords. It provides a graphical depiction of how concerns relate to requirements, and affords identification of potential aspectual requirements. In addition, clusters of requirements and concerns are identified to arrive at a more useful set of concerns than those initially identified.Because of the lexical nature of the Theme/Doc approach, aspectual requirements are missed, or wrongly identified. Additionally, requirements may be wrongly clustered if they contain ambiguous terms.In this work we explored whether the use of a statistical approach for textual analysis, Latent Semantic Analysis (LSA), would improve upon the lexical approach used by Theme/Doc. We found that LSA helps identify useful concern clusters, and helps reduce the number of falsely identified aspectual requirements.