Sustainability has become a critical topic, not only from an environmental perspective, but in the creation of software systems which are themselves sustainable. The sustainability literature has made use of the doughnut model from economics to understand the delicate balance needed for sustainable development. This model emphasizes the notion of having just the right amount of a resource (e.g., food, water) and not too much, else negative consequences (water depletion, starvation) may be felt by others in the ecosystem. Although iStar has covered well the notion of trade-o s between qualities (e.g. security vs. usability, performance vs. maintainability), the implicit aim of the work is always to maximize qualities. In this work we aim for \just enough" quality by applying the doughnut economic model to quality requirements in iStar. Overall, we propose a visually appealing model which emphasizes a sustainable balance between qualities.
Sustainability has become a critical topic, not only from the perspective of
environmental or natural sustainability, but in creating software systems which are
themselves sustainable [
Many methods exist to model and reason over the achievement of NFRs
and qualities (e.g., the NFR Framework [
In this work we apply the doughnut economic model to qualities in iStar.
We evaluate our idea through application to historical goal model examples,
focusing on qualities, considering changes to existing reasoning techniques. By
aiming to achieve just enough of various qualities, we argue that systems are
easier to construct and maintain, and are therefore more likely to be successful
and sustainable. Although other models for sustainable software development
have been proposed (e.g., [
In this paper, we brie y introduce the doughnut model in Sec. 2, then present our ideas via an example in Sec. 3. We discuss issues such as semantics and reasoning, including the notion of over-saturation in Sec. 4. We conclude and describe future plans in Sec. 5. 2
The doughnut model combines together both planetary boundaries (climate
change, land use) with social boundaries (income, education) into one
holistic view of sustainable development [
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SHORTFALL lluop cehm tno ilca i pniotropgheonru&sloading h s ronmental dimensions. The idea is to nd a safe space for humanity that balances all of these environmental and social factors. In our work, we are inspired by this model, but adapt a simpler version to better suit quality requirements, keeping the general principle of balance. 3
In order to further motivate the need for the new visualization and to
demonstrate how it would look and work in practice, we present two examples. We
start with a simple example from [
In the second example, we recreate two of the three actors in Fig. 3a, again focusing on qualities. Here we can see the doughnut model beginning to scale to more qualities, in this case seven and ve. Due to the increasing number of qualities in the doughnut, we can no longer use straight internal contribution links as in the rst example, here we use curved green and red arrows for help and hurt contributions within the doughnut and straight links from functional elements to quality. Again, we indicate positive/negative via color, and severity by link thickness (to be evaluated and improved in future studies). Here we start to explore doughnuts in iStar actors with typical dependencies. We see the
administrative privledges
Maintain network address integrity Authenticate to access the host Access to host remotely +
Restrict Administrative
Privileges Immediacy [Services]
Café/Portal/ Chat Room Cyber Café/ Portal/Chat Room Service Immediacy [Service]
Messaging Service
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common visual clutter, but there is also a clear distinction between quality and function in the model. 4
Existing descriptions of NFR or iStar/i* semantics, supporting goal reasoning, can be adjusted to account for our proposal. Traditionally, satisfaction is thought of on a scale from fully denied to fully satis ed, as is shown in Fig. 4a, with some variation in the names, colors, and format of the labels. In this work, we introduce the notion of Over-Saturation, to show that going beyond satisfaction (or satis cing) is both possible and undesirable (see left side of Fig. 4b). We de ned over-saturation in this case as: satisfying a quality to a degree that is more than is necessary to achieve a desirable state. This de nition is vague by construction, as satisfaction and over-saturation depend on the quality and context. For example, for security, satisfaction may mean that the majority of users are happy with the level of security provided by a system. Here even `majority' will depend on the size of the user base, if there are only ve major customers, one customer being dissatis ed with security is signi cant. However, if there are 1000 customers, it may be acceptable that 90% of customers are satis ed with the system security. One can satisfy the additional 10% by adding more security features, but this may negatively a ect cost, usability, or performance in such a way that the overall trade-o is negative. In such a case, adding more security interventions may lead to over-saturation.
Existing goal model reasoning approaches such as reasoning described in the
NFR Framework [
(b) New Proposal for Quality Satisfaction
Fig. 4: Satisfaction of Qualities: Old vs. New
goal is partially satis ed, satis ed, partially saturated, or over-saturated. For
other procedures, e.g., [
We have proposed an alternative way to visualize, think about, and reason over quality requirements, including the notion of quality over-saturation. Through examples, we have begun to show practical feasibility, and we have discussed how the new concepts could in uence existing goal reasoning techniques.
Future work will consider views over the model, e.g., incrementally showing the Doughnut model elements, contribution links, contributing elements, etc. Tooling should be adapted, ideally automatically transform existing i* or iStar models into the new notation. We are working on an evaluate plan involving surveys, prototypes and user studies with both iStar experts and novices. We welcome others to participate in the use and development of these ideas.
Supported by Vetenskapsradet project \Non-Functional Requirements for Machine Learning: Facilitating Continuous Quality Awareness (iNFoRM)".