The NORMAP Methodology: Non-functional Requirements Modeling for Agile Processes

Agile software development methodologies, such as Scrum, have gained tremendous popularity and proven successful in quickly delivering quality Functional Requirements (FRs). However, agile methodologies have not adequately identified, modeled, and linked Non-Functional Requirements (NFRs) with FRs i...

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Bibliographic Details
Main Author: Farid, Weam Mohamed
Format: Others
Published: NSUWorks 2011
Subjects:
Online Access:http://nsuworks.nova.edu/gscis_etd/147
http://nsuworks.nova.edu/cgi/viewcontent.cgi?article=1146&context=gscis_etd
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Summary:Agile software development methodologies, such as Scrum, have gained tremendous popularity and proven successful in quickly delivering quality Functional Requirements (FRs). However, agile methodologies have not adequately identified, modeled, and linked Non-Functional Requirements (NFRs) with FRs in early development phases. Researchers agree that NFRs have been generally ignored in conventional methodologies, especially ignored in agile environments. This dissertation develops a conceptual framework for NFR modeling in agile processes. The proposed Non-functional Requirements Modeling for Agile Processes (NORMAP) Methodology investigated the feasibility of identifying, linking, and modeling Agile Loose Cases (ALCs) with Agile Use Cases (AUCs) and Agile Choose Cases (ACCs). AUCs are newly proposed hybrid of use cases and agile user stories. ALCs are proposed—loosely—defined agile NFRs. ACCs are proposed potential solutions (operationalizations) for ALCs. A lightweight adapted version of the NFR Framework was developed including 25 important NFRs selected out of 161 for this study. Further, an enhanced risk-driven agile requirements implementation sequence (NORPLAN) was developed and visualized as a tree-like view (NORVIEW). The NORMAP Methodology was validated through developing NORMATIC--a Java-based agile visual modeling simulation tool and two case studies. NORMATIC utilized Natural Language Processing (NLP) tools to parse requirement sentences and identify potential ALCs. The first case study utilized the Predictor Models in Software Engineering (PROMISE) dataset used in NFRs classification. NORMAP successfully parsed and classified ALCs for 529 out of 607 (87.15%) independent user requirements. The second case study utilized the European Union eProcurement System’s 26 functional requirements. NORMAP successfully parsed and classified ALCs for 50 out of 57 sentences that included possible ALCs (87.71%). Furthermore, requirements quality and project management metrics were used to calculate a risk-driven requirements implementation sequence using three priority schemes. Results showed that Riskiest-Requirements-First priority scheme planned requirements in 17 sprints--two months earlier than the Highest-Business-Value-First scheme (21 sprints) and one month earlier than the Riskiest-Requirements-Last scheme (19 sprints). Agile communities can potentially benefit from the NORMAP Methodology by utilizing a systematic and risk-driven lightweight engineering process to visually model and plan NFRs as first-class artifacts in agile environments.