SACRE

Title: Smart Adaptation through Contextual REquirements

Context and goal: Nowadays, software systems are able to automatically adapt their behaviour and structure in order to respond to changes in the environment and their own operation. This kind of systems are known as Self-Adaptive Systems (SASs). Contextual requirements are a particular type of requirements that have been proposed for supporting the adaptation capabilities in SASs and keeping track of user needs and environmental conditions at the same time. 

Since contextual requirements depend on context, runtime uncertainty such as unpredictable resource unavailability, changing environmental conditions and user needs, as well as system intrusions or faults represents one of their main current challenges. Moreover, today’s systems are increasingly more complex, distributed, decentralized, etc. and therefore have to reason about and cope with more and more unpredictable events. The SACRE project aims at dealing with this challenging situation supporting the adaptation of contextual requirements affected by runtime uncertainty in modern self-adaptive systems.

Results: As part of the results of the SACRE project, an approach that leverages an adaptation feedback loop to detect self-adaptive systems’ contextual requirements affected by uncertainty and to integrate machine learning techniques to determine the best operationalization of context based on sensed data at runtime has been developed. Moreover, the approach has been implemented for the extremely demanding domain of smart vehicles and evaluated in different uncertainty scenarios in real-time. Contextual requirements have been modeled for supporting drivers at different drowsiness levels. The evaluation has been conducted in a simulated environment in which the smart vehicle and the driver behaviour have been implemented through software components.

UPC team: Edith Zavala (PhD student), Xavier Franch (Supervisor), Jordi Marco (Co-supervisor)

Collaborations: SACRE (Smart Adaptation through Contextual REquirements) is a collaboration project that is constantly integrating new partners. The first results have been obtained thanks to the combination of the expertise of the GESSI research group, the Dept. of Computer Science and Engineering of Chalmers and the University of Gothenburg (Sweden), and the Dept. of Computer Science of the University of Victoria (Canada) in requirements engineering, self-adaptive systems and autonomous vehicles. In the last year, two new partners have started to participate in this project: the University of Valecia (Spain) and the vehicles lab REVERE which is part of the Chalmers research infrastructure (Sweden). These new collaborations have as main objectives: the extension of SACRE for supporting the adaptation of the data gathering activity in modern self-adaptive systems in order to correctly respond to unpredictable events at runtime and the evaluation of the solution in more realistic environments such miniature vehicles and real vehicles.

Related publications:

• Zavala, E., Franch, X., Marco, J., Knauss, A., & Damian, D. (2015). SACRE: A tool for dealing with uncertainty in contextual requirements at runtime. In 23rd IEEE International Requirements Engineering Conference (RE) (pp. 278–279). IEEE. https://doi.org/10.1109/RE.2015.7320437

• Zavala, E., Franch, X., Marco, J., Knauss, A., & Damian, D. (2018). SACRE: Supporting contextual requirements’ adaptation in modern self-adaptive systems in the presence of uncertainty at runtime. Expert Systems with Applications, 98, 166–188. https://doi.org/10.1016/J.ESWA.2018.01.009

Tool: SACRE implementation

Demo video: SACRE video

Dates: Started on January 2015