Key Performance Indicators (KPIs) are becoming essential elements for measuring business performance. In recent years, KPIs management has been the subject to sustained interests for researchers and practitioners alike, deriving into a large research corpus of approaches addressing aspects in matters as varied as modelling, maintenance or expressiveness of KPIs. In particular, since both businesses and processes have to be adapted to ever-changing requirements, the KPIs that measure their performance must evolve accordingly. However, based on a previous review of the literature, we found that little attention has been paid to the provision of mechanisms to manage KPIs evolution. Our long-term research goal is to provide a fully proposal for supporting KPIs evolution management. In this position paper, we present the first ideas of a conceptual framework for addressing this issue, proposing a pattern-driven KPI evolution specification and a KPI evolution metamodel made up of two interconnected views. Our proposal is general enough to be applied regardless of the specific KPIs management approach being used.

In a competitive market, business process improvement is a requirement for any organization. This improvement can only be achieved with the support of comprehensive systems that fully monitor business processes. We propose an occurrence - based approach to business process monitoring that provides a holistic perspective of system dynamics, lending support to evolution aspects. More specifically, we present a three-dimensional artifact, called Occurrence, in which structure, behavior, and guidance are considered simultaneously. Based on this, we define more complex structures, namely Occurrence Base and Occurrence Management System, which serve as scaffolding to develop business process monitoring systems. We also present a specific occurrence-based design strategy that, using an MDE approach, has been applied by our research group for the development of successful monitoring applications.

System monitoring is typically performed by means of log files storing the sequential trace of the system events. However, these files constitute a poor solution when improved auditing features are required. For this reason, we advocate defining specific persistence structures for registering a more complete system trace. In particular, when the system behaviour is specified by means of a UML statechart, we propose to automatically generate a stereotyped UML class diagram containing information for tracing the system behaviour without loosing the statechart dynamic semantics. To do this, we have formally defined a Statechart Execution Persistence (SEP) UML profile which (1) eases audit and process improvement, (2) ensures accuracy and consistency of data, and (3) guides during the automatic generation of the system's storage mechanisms, following a MDD approach.

A clear understanding of the dynamic semantics of UML State Machines is essential for a large and varied audience such as final users of the language, CASE tool builders or method engineers. Our proposal aims at achieving such an understanding by suggesting a different metamodeling approach. This approach is based on a two-layer architecture which puts forward the explicit distinction between the generic behavior represented in a dynamic model (Base Layer) and the behavior represented in relation to a particular situation (Snapshot Layer). Using this architecture as a starting point, a metamodel of UML State Machines is proposed, which consists basically of two UML class diagrams (one diagram for each layer of the architecture) and two maps. These maps represent, respectively, the determination of the initial status and the process performed by a run-to-completion step as defined in the UML semantics.

This paper is devoted to state and prove a Digital Index Theorem for digital (n - 1)-manifolds in a digital space (Rn, f), where f belongs to a large family of lighting functions on the standard cubical decomposition Rn of the n-dimensional Euclidean space. As an immediate consequence we obtain the corresponding theorems for all (α, β)-surfaces of Kong–Roscoe, with α, β ∈ {6, 18, 26} and (α, β) ≠ (6, 6), (18, 26), (26, 26), as well as for the strong 26-surfaces of Bertrand–Malgouyres.