Effective requirements traceability: Models, tools, and practices

2008 ◽  
Vol 12 (4) ◽  
pp. 143-157 ◽  
Author(s):  
Vassilka Kirova ◽  
Neil Kirby ◽  
Darshak Kothari ◽  
Glenda Childress
Keyword(s):  
Requirements Traceability

Requirements Traceability Matrix: Automatic Generation and Visualization

2012 ◽  
Author(s):  
Andre Di Thommazo ◽  
Gabriel Malimpensa ◽  
Thiago Ribeiro de Oliveira ◽  
Guilherme Olivatto ◽  
Sandra C. P. F. Fabbri
Keyword(s):  
Automatic Generation ◽  
Requirements Traceability ◽  
Traceability Matrix

RETRIEVAL BY CONSTRUCTION: A TRACEABILITY TECHNIQUE TO SUPPORT VERIFICATION AND VALIDATION OF UML FORMALIZATIONS

2005 ◽  
Vol 15 (05) ◽  
pp. 837-872 ◽  
Author(s):  
MIN DENG ◽  
R. E. K. STIREWALT ◽  
BETTY H. C. CHENG
Keyword(s):  
Case Studies ◽  
Verification And Validation ◽  
Requirements Traceability ◽  
Rigorous Analysis ◽  
Target Model ◽  
Domain Specific ◽  
Natural Means

Recently, there has been growing interest in formalizing UML, thereby enabling rigorous analysis of its many graphical diagrams. Two obstacles currently limit the adoption and use of UML formalizations in practice. First is the need to verify the consistency of artifacts under formalization. Second is the need to validate formalization approaches against domain-specific requirements. Techniques from the emerging field of requirements traceability hold promise for addressing these obstacles. This paper contributes a technique called retrieval by construction (RBC), which establishes traceability links between a UML model and a target model intended to denote its semantics under formalization. RBC provides an approach for structuring and representing the complex one-to-many links that are common between UML and target models under formalization. RBC also uses the notion of value identity in a novel way that enables the specification of the link-retrieval criteria using generative procedures. These procedures are a natural means for specifying UML formalizations. We have validated the RBC technique in a tool framework called UBanyan, written in C++. We applied the tool to three case studies, one of which was obtained from the industry. We have also assessed our results using the two well-known traceability metrics: precision and recall. Preliminary investigations suggest that RBC can be a useful traceability technique for validating and verifying UML formalizations.

scholarly journals Uma Proposta de Modelagem para a Generalização de Elos de Rastreabilidade

2008 ◽  
Vol 15 (2) ◽  
pp. 181-202
Author(s):  
Elias Canhadas Genvigir ◽  
Nandamudi Lankalapalli Vijaykumar
Keyword(s):  
Requirements Traceability

Several models proposed traceability links that provide pre–definedgroups of links for requirements traceability. These models are limited to pre–defined links without the ability to add new attributes to the existing links. This work proposes a model for requirements traceability that generalizes the types of links already establishedin the literature and enables addition of new standards allowing the inclusion of attributes to the links that will be used in a specific traceability process.

Decision tree classifiers for unmanned aircraft configuration selection

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
João Antônio Dantas de Jesus Ferreira ◽  
Ney Rafael Secco
Keyword(s):  
Decision Tree ◽  
Aircraft Design ◽  
Classification Problem ◽  
Unmanned Aircraft ◽  
Requirements Traceability ◽  
Content Type ◽  
Configuration Selection ◽  
Incomplete Databases ◽  
Engine Type ◽  
Selection Of

Purpose This paper aims to investigate the possibility of lowering the time taken during the aircraft design for unmanned aerial vehicles by using machine learning (ML) for the configuration selection phase. In this work, a database of unmanned aircraft is compiled and is proposed that decision tree classifiers (DTC) can understand the relations between mission and operational requirements and the resulting aircraft configuration. Design/methodology/approach This paper presents a ML-based approach to configuration selection of unmanned aircraft. Multiple DTC are built to predict the overall configuration. The classifiers are trained with a database of 118 unmanned aircraft with 57 characteristics, 47 of which are inputs for the classification problem, and 10 are the desired outputs, such as wing configuration or engine type. Findings This paper shows that DTC can be used for the configuration selection of unmanned aircraft with reasonable accuracy, understanding the connections between the different mission requirements and the culminating configuration. The framework is also capable of dealing with incomplete databases, maximizing the available knowledge. Originality/value This paper increases the computational usage for the aircraft design while retaining requirements’ traceability and increasing decision awareness.

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