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Requirements-aware Systems for Self-adaptation under Uncertainty Research Statement

The development of software-intensive systems is driven by their requirements. Traditional requirements engineering (RE) methods focus on resolving ambiguities in requirements and advocate specifying requirements in sufficient detail so that the implementation can be checked against them for conformance. In an ideal world, this way of thinking can be very effective. Requirements can be specified clearly, updated as necessary, and evolutions of the software design can be made with the requirements in mind. Increasingly, however, it is not sufficient to fix requirements statically because they will change at runtime as the operating environment changes. Furthermore, as software systems become more pervasive, there is growing uncertainty about the environment and so requirements changes cannot be predicted at design-time [12, 24, 39, 1, 20]. It is considerations such as these that have led to the development of self-adaptive systems (SASs) [11], which have the ability to dynamically and autonomously reconfigure their behavior to respond to changing external conditions. Consider a scenario involving a robot vacuum cleaner for domestic apartments. The vacuum cleaner has goals clean apartment, avoid tripping hazard and minimize energy costs. Further, it has the domain assumption energy is cheapest at night. To satisfy the avoid tripping hazard goal, a requirement is derived that it should stop operating as soon as any human activity is detected. Night operation satisfies the minimize energy costs goal. Thus all the goals are satisfiable, with no trade-offs necessary. In operation, the sound of the cleaner awakens a light sleeper. In the dark, they trip over the now stopped and therefore silent cleaner. Key features of this scenario are: