A Graded Approach to Requirement Satisfaction for Evolving Systems

Trevor P. Martin, E. Ratih N. Anggraini

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


There has been a strong trend towards autonomous and semi-autonomous systems in recent years. Evolving and adaptive systems embody the notion of autonomy, by changing their behavior (and possibly their structure) in response to changes in their environment. A consequence is that a designer may not be able to fully define the functional behavior of a system. Hence, formal verification and testing may not be possible. As a result, the self-adapting aspect of an evolving system is often implemented in an informal, ad hoc, manner and there is potential for causing significant harm if a system malfunctions in some way. A safety case requires more than an assertion that a system will work because it has not failed in testing. A more rigorous approach is essential, in which we can formally show that an evolving system meets its requirements and specifications. This paper outlines initial work in combining the X-mu approach (to model fuzzy uncertainty) with flexible requirements for an evolving system specified in RELAX, a formal framework to capture the uncertainty in evolving system requirements. A simple case study is used to illustrate some of the principles.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538617281
Publication statusPublished - Jun 2019
Externally publishedYes
Event2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019 - New Orleans, United States
Duration: 23 Jun 201926 Jun 2019

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584


Conference2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019
Country/TerritoryUnited States
CityNew Orleans


  • Evolving Systems
  • Fuzzy
  • Graded
  • Requirements
  • Self-Adaptation
  • Verification
  • X-mu


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