iStar 2 - Larger models
URL
Change Log
| When | What |
|---|---|
| October 17th, 2015 | Donated by Jennifer Horkoff |
Reference
Studies who have been using the data (in any form) are required to include the following reference:
@article{
year={2014},
issn={0947-3602},
journal={Requirements Engineering},
doi={10.1007/s00766-014-0209-8},
title={Interactive goal model analysis for early requirements engineering},
url={http://dx.doi.org/10.1007/s00766-014-0209-8},
publisher={Springer London},
keywords={Goal-oriented requirements engineering; Goal modeling; Modeling; Model analysis; Model iteration; Interactive modeling; Satisfaction analysis},
author={Horkoff, Jennifer and Yu, Eric},
pages={1-33},
language={English}
}
About the Data
Overview of Data
.vsd files are essentially .xml files which cannot be parsed as we cannot estimate a generic pattern amongst the files to construct a parser. A domain specific language in python is used to draw these models. The template for the DSL can be accessed here and a sample model can be accessed here.
Attribute Information
Goal-oriented requirements engineering - Goal modeling - Modeling - Model analysis - Model iteration - Interactive modeling - Satisfaction analysis
Paper Abstract
In goal-oriented requirements engineering, goal models have been advocated to express stakeholder objectives and to capture and choose among system requirement candidates. A number of highly automated procedures have been proposed to analyze goal achievement and select alternative requirements using goal models. However, during the early stages of requirements exploration, these procedures are difficult to apply, as stakeholder goals are typically high-level, abstract, and hard-to-measure. Automated procedures often require formal representations and/or information not easily acquired in early stages (e.g., costs, temporal constraints). Consequently, early requirements engineering (RE) presents specific challenges for goal model analysis, including the need to encourage and support stakeholder involvement (through interactivity) and model improvement (through iterations). This work provides a consolidated and updated description of a framework for iterative, interactive, agent-goal model analysis for early RE. We use experiences in case studies and literature surveys to guide the design of agent-goal model analysis specific to early RE. We introduce analysis procedures for the i* goal-oriented framework, allowing users to ask “what if?” and “are certain goals achievable? how? or why not?” The i* language and our analysis procedures are formally defined. We describe framework implementation, including model visualization techniques and scalability tests. Industrial, group, and individual case studies are applied to test framework effectiveness. Contributions, including limitations and future work, are described.