ACon: A learning-based approach to deal with uncertainty in contextual requirements at runtime

Abstract

Context: Runtime uncertainty such as unpredictable operational environment and failure of sensors that gather environmental data is a well-known challenge for adaptive systems. Objective: To execute requirements that depend on context correctly, the system needs up-to-date knowledge about the context relevant to such requirements. Techniques to cope with uncertainty in contextual requirements are currently underrepresented. In this paper we present ACon (Adaptation of Contextual requirements), a data-mining approach to deal with runtime uncertainty a↵ecting contextual requirements. Method: ACon uses feedback loops to maintain up-to-date knowledge about contextual requirements based on current context information in which contextual requirements are valid at runtime. Upon detecting that contextual requirements are a↵ected by runtime uncertainty, ACon analyzes and mines contextual data, to (re-)operationalize context and therefore update the information about contextual requirements. Results: We evaluate ACon in an empirical study of an activity scheduling system used by a crew of 4 rowers in a wild and unpredictable environment using a complex monitoring infrastructure. Our study focused on evaluating the data mining part of ACon and analyzed the sensor data collected onboard from 46 sensors and 90,748 measurements per sensor. Conclusion: ACon is an important step in dealing with uncertainty a↵ecting contextual requirements at runtime while considering end-user interaction. ACon supports systems in analyzing the environment to adapt contextual requirements and complements existing requirements monitoring approaches by keeping the requirements monitoring specification up-to-date. Consequently, it avoids manual analysis that is usually costly in today's complex system environments.

Control Strategies for Self-Adaptive Software Systems

“…Uncertainty can be at the same time the driver for and the outcome of adding self-adaptation capabilities to a system. The research community devolved extensive efforts to studying and modeling uncertainty in self-adaptive software (see e.g., [Esfahani and Malek 2013;Esfahani et al 2011;Cheng and Garlan 2007;Ramirez et al 2012a;Ramirez et al 2012b;Bencomo and Belaggoun 2014;Alessia Knauss et al 2016;Cheng et al 2009]) and elicited three main sources for it: (1) requirements can change over time and have different priorities for different users [Baresi et al 2006]; specifications are incomplete, and designs can intention-…”

SACRE: A tool for dealing with uncertainty in contextual requirements at runtime

“…Self-adaptive systems are able to execute basic requirements engineering activities by themselves to cope with changing conditions that appear at runtime [1]. While selfadaptive systems promise to deal with uncertainty, they challenge current software engineering practices, particularly the activities of requirements definition and satisfaction in uncertain environments.…”

“…ACon (Adaptation of Contextual requirements) has emerged as an approach to address the problem of dealing with runtime uncertainty in the presence of contextual requirements [1]. Contextual requirements should be understood as requirements that are characterized to be valid only in a specific context [3,4,5].…”

“…Contextual requirements should be understood as requirements that are characterized to be valid only in a specific context [3,4,5]. More specifically, based on [1]: ACon takes the position that self-adaptive systems, in order to respond to unpredictable changes in their operating environment, need to learn from the environmental data that they have available at runtime and execute the adaptation of their contextual requirements in the basis of this knowledge [1].…”

“…It maintains an up-to-date knowledge about the context in which contextual requirements are valid at runtime. Moreover, ACon includes the interaction with the end-users as part of a semiautomatic approach in which the human is in the loop [1].…”