Miguel Goulão

There are several tools currently available in the i * community. These tools have different features and purposes. Choosing the most adequate tool for a specific modelling situation can be a challenge. To overcome this diffculty, we present a systematic comparison of the i * tools listed in the i * wiki page, according to their features, syntax coverage and semantic analysis support. Our comparison highlights the
different strengths of those tools, to help identifying situations for which each tool might be particularly useful. We contribute with an aggregated vision of current i * tool support to the body of knowledge of the i * community. In addition, this comparison also helps identifying opportunities for further evolution of the surveyed tools.

Domain-Specific Languages (DSLs) are claimed to bring important productivity improvements to developers,
when compared to General-Purpose Languages (GPLs). The increased Usability is regarded as one of the key benefits of DSLs when compared to GPLs, and has an important impact on the achieved productivity of the DSL users. So, it is essential to build in good usability while developing the DSL. The purpose of this proposal is to contribute to the systematic activity of Software Language Engineering by focusing on the
issue of the Usability evaluation of DSLs. Usability evaluation is often skipped, relaxed, or at least omitted from papers reporting development of DSLs. We argue that a systematic approach based on User Interface experimental validation techniques should be used to assess the impact of new DSLs. For that purpose, we propose to merge common Usability evaluation processes with the DSL development process. In order to provide reliable metrics and tools we should reuse and identify good practices that exist in Human-Computer
Interaction community.

The usability of requirements engineering (RE) techniques has been recognised as a key factor for their successful adoption by industry. RE techniques must be accessible to stakeholders with different backgrounds, so they can be empowered to effectively and efficiently contribute to building successful systems. When selecting an appropriate requirements engineering technique for a given context, one should consider the usability supported by each of the candidate techniques. The first step towards achieving this goal is to gather the best evidence available on the usability of RE approaches by performing a systematic literature review, to answer one research question: How is the usability of requirements engineering techniques and tools addressed? We systematically review articles published in the Requirements Engineering Journal, one of the main sources for mature work in RE, to motivate a research roadmap to make RE approaches more accessible to stakeholders with different backgrounds.

A rapidly changing market leads to software systems with highly volatile requirements. In many cases, new demands in software can often be met by extending the functionality of systems already in operation. By modularizing volatile requirements that can be altered at the client’s initiative or according to market demands, we can build a stepping-stone for management of requirements change. The volatility must be managed in a way that reduces the time and costs associated with updating a system to meet the new requirements. In this chapter, we present an approach for handling volatile concerns during early life cycle software modeling. The key insight is that techniques for aspect-oriented software development can be applied to modularize volatility and to weave volatile concerns into the base software artifacts.

The i* community has published guidelines, including model layout guidelines, for the construction of models. Our goal is to evaluate the effect of the layout guidelines on the i* novice stakeholders’ ability to understand and review i* models. We conducted a quasi-experiment where participants were given two understanding and two reviewing tasks. Both tasks involved a model with a bad layout and another model following the i* layout guidelines. We evaluated the impact of layouts by combining the success level in those tasks and the required effort to accomplish them. Effort was assessed using time, perceived complexity (with NASA TLX), and eye-tracking data. Participants were more successful in understanding than in reviewing tasks. However, we found no statistically significant difference in the success, time taken, or perceived complexity, between tasks conducted with models with a bad layout and models with a good layout. Most participants had little to no prior knowledge in i*, making them more representative of stakeholders with no requirements engineering expertise. They were able to understand the models fairly well after a short tutorial, but struggled when reviewing models. Adherence to the existing i* layout guidelines did not significantly impact i* model understanding and reviewing performance.