GODA: A goal-oriented requirements engineering framework for runtime dependability analysis

Abstract

Context: Many modern software systems must deal with changes and uncertainty. Traditional dependability requirements engineering is not equipped for this since it assumes that the context in which a system operates be stable and deterministic, which often leads to failures and recurrent corrective maintenance. The Contextual Goal Model (CGM), a requirements model that proposes the idea of context-dependent goal fulfillment, mitigates the problem by relating alternative strategies for achieving goals to the space of context changes. Additionally, the Runtime Goal Model (RGM) adds behavioral constraints to the fulfillment of goals that may be checked against system execution traces.Objective: This paper proposes GODA (Goal-Oriented Dependability Analysis) and its supporting framework as concrete means for reasoning about the dependability requirements of systems that operate in dynamic contexts.Method: GODA blends the power of CGM, RGM and probabilistic model checking to provide a formal requirements specification and verification solution. At design time, it can help with design and implementation decisions; at runtime it helps the system self-adapt by analyzing the different alternatives and selecting the one with the highest probability for the system to be dependable. GODA is integrated into TAO4ME, a state-of-the-art tool for goal modeling and analysis.Results: GODA has been evaluated against feasibility and scalability on Mobee: a real-life software system that allows people to share live and updated information about public transportation via mobile devices, and on larger goal models. GODA can verify, at runtime, up to two thousand leaf-tasks in less than 35ms, and requires less than 240 kbytes of memory.Conclusion: Presented results show GODA's design-time and runtime verification capabilities, even under limited computational resources, and the scalability of the proposed solution.

A Persona-Based Modelling for Contextual Requirements

“…The major complexity of the algorithm is in the execution of each Refinement d in deps (lines [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. The algorithm recursively invokes itself for the CGM of the Refinement (sub goal, task or delegation).…”

“…If the node is not a task, the Algorithm starts defining an execution plan that fulfills the persona context set (line 11). For each of the applicable refinements (line 13), it will evaluate if it is achievable (line 14). If the refinement is achievable then, for OR-decompositions, the algorithm returns this plan immediately (line 17) and for AND-decompositions it is added to the complete plan (line 20).…”

“…There are few works that adopt CGM as modelling baseline such as Guimaraes et al [15] and Mendonca et al [14]. The work in [15] uses the concept of Pragmatic Goals to enhance the contexts of CGMs.…”

“…Pragmatic Goals are the idea that a goal's interpretation varies according to context. While the work in [14] uses the CGM structure to provide quantitative dependability analysis by means of probabilistic model checking. Despite the benefits of their approach, they do not cater primarily for the human perspective which could hinder altogether their analysis processes in that aspect.…”

GoalD: A Goal-Driven deployment framework for dynamic and heterogeneous computing environments

“…More recently, goal-oriented engineering has paved the way for solutions able to leverage seamless configurations, behavior, and strategies in self-adaptive systems [17,18,19,20]. As Weyns points out as the fourth wave on engineering selfadaptive systems:"...(goal-driven adaptation) puts the focus on key elements for the concrete realization of self-adaptive systems" [20].…”