Achieving real-time agility and adaptation with respect to changing requirements in existing IT infrastructure can pose a complex challenge. We describe a goal-oriented approach to manage this complexity. We argue that a goal-oriented perspective can form an effective basis for devising and deploying responses to changed requirements at runtime. We offer an extended vocabulary of goal types by presenting two novel conceptions: differential goals and integral goals, which we formalize in both linear-time and branching-time settings. We describe goal lifecycles and interactions and the extended notion of context for the representation of rapidly changing, complex operating environments. We then illustrate the working of the approach by presenting a detailed scenario of adaptation in a Kubernetes setting, in the face of a Distributed Denial-of-Service (DDoS) attack.

Entity resolution (ER) is the problem of accurately identifying multiple, differing, and possibly contradicting representations of unique real-world entities in data. It is a challenging and fundamental task in data cleansing and data integration. In this work, we propose graph differential dependencies (GDDs) as an extension of the recently developed graph entity dependencies (which are formal constraints for graph data) to enable approximate matching of values. Furthermore, we investigate a special discovery of GDDs for ER by designing an algorithm for generating a non-redundant set of GDDs in labelled data. Then, we develop an effective ER technique, Certus, that employs the learned GDDs for improving the accuracy of ER results. We perform extensive empirical evaluation of our proposals on five real-world ER benchmark datasets and a proprietary database to test their effectiveness and efficiency. The results from the experiments show the discovery algorithm and Certus are efficient; and more importantly, GDDs significantly improve the precision of ER without considerable trade-off of recall.

In large organizations, multiple stakeholders may modify the same business process. This paper addresses the problem when stakeholders perform changes on process views which become inconsistent with the business process and other views. Related work addressing this problem is based on execution trace analysis which is performed in a post-analysis phase and can be complex when dealing with large business process models. In this paper, we propose a design-based approach that can efficiently check consistency criteria and propagate changes on-the-fly from a process view to its reference process and related process views. The technique is based on consistent specialization of business processes and supports the control flow aspect of processes. Consistency checks can be performed during the design time by checking simple rules which support an efficient change propagation between views and reference process.