In the design of autonomous systems, it is important to consider the preferences of the interested parties to improve the user experience. These preferences are often associated with the contexts in which each system is likely to operate. The operational behavior of a system must also meet various non-functional requirements (NFRs), which can present different levels of conflict depending on the operational context. This work aims to model correlations between the individual contexts and the consequent conflicts between NFRs. The proposed approach is based on analyzing the system event logs, tracing them back to the leaf elements at the specification level and providing a contextual explanation of the system’s behavior. The traced contexts and NFR conflicts are then mined to produce Context-Context and Context-NFR conflict sequential rules. The proposed Contextual Explainability (ConE) framework uses BERT-based pre-trained language models and sequential rule mining libraries for deriving the above correlations. Extensive evaluations are performed to compare the existing state-of-the-art approaches. The best-fit solutions are chosen to integrate within the ConE framework. Based on experiments, an accuracy of 80%, a precision of 90%, a recall of 97%, and an F1-score of 88% are recorded for the ConE framework on the sequential rules that were mined.

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Non-functional requirements (NFRs) play a significant role in the software development process. However, the classical requirement prioritization methods for incremental software development, typically, consider the attributes of functional features only, often neglecting the non-functional constraints. This might lead to catastrophic defects in the system design, as the conflicts among the NFRs are ignored. In this paper, a novel prioritization approach for functional requirements (FRs) is introduced within the incremental software development process. The proposed approach considers the conflicts among NFRs, in the prioritization process, to minimize the incon sistencies of software development. The devised NFR-aware prioritization algorithm can be tuned according to the weights that the analyst assigns to NFR conflicts and FR-NFR dependencies. We have assessed our prioritization approach using available requirements data sets and have compared the results in different scenarios.

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