Context. Several early requirements approaches focus on modeling objectives, interest or benefits of related stakeholders. However, as they can be used for different purposes as identifying problems, exploring system solutions, evaluating alternatives, etc., there are no clear guidelines on how to build these models, which constructs of the language must be used in each case, and most importantly, how to use these models downstream to the software requirements and design artifacts. Background. In a previous work, we proposed a specialization of the GRL language ([email protected]) to specify stakeholders' goals when dealing with early requirements in the context of incremental software development. Goal/Method. This paper reports on a controlled experiment aimed at comparing the goal model quality and the productivity, perceived ease of use, and perceived usefulness of participants when using [email protected] and i* languages. Results. The results showed that [email protected] obtained better results than i* as a goal modeling language indicating that it can be considered as a promising emerging approach in this area. Conclusions. [email protected] allows obtaining goal models with good quality that may be later used downstream software development activities.
Context. Several early requirements approaches focus on modeling objectives, interest or benefits of related stakeholders. However, as they can be used for different purposes as identifying problems, exploring system solutions, evaluating alternatives, etc., there are no clear guidelines on how to build these models, which constructs of the language must be used in each case, and most importantly, how to use these models downstream to the software requirements and design artifacts. Background. In a previous work, we proposed a specialization of the GRL language ([email protected]) to specify stakeholders' goals when dealing with early requirements in the context of incremental software development. Goal/Method. This paper reports on a controlled experiment aimed at comparing the goal model quality and the productivity, perceived ease of use, and perceived usefulness of participants when using [email protected] and i* languages. Results. The results showed that [email protected] obtained better results than i* as a goal modeling language indicating that it can be considered as a promising emerging approach in this area. Conclusions. [email protected] allows obtaining goal models with good quality that may be later used downstream software development activities.
Identifying relationships between requirements described in natural language (NL) is a difficult task in requirements engineering (RE). This paper presents a novel approach that uses Semantic Frames in FrameNet to find the relationships between requirements. Our initial validation shows that the approach is promising, with an F-Score of 83%. Our next step is to use the approach to identify implicit requirements relationships and finding requirements traceability links.