Extensible Structural Analysis of Petri Net Product Lines

Petri nets are a popular formalism to represent concurrent systems. However, their standard form does not o er variability support to model and e ectively analyse large sets of variants of a given system. For this purpose, we propose a notion of product line of Petri nets to represent a set of similar concurrent systems. The formalization enriches Petri nets with a feature model characterizing the variability of the systems. Moreover, places, transitions and arcs can de ne presence conditions that determine the subset of system variants they belong to. To enable an e cient analysis of the set of all net variants, we have lifted several structural analysis methods for Petri nets, to the product line level. Currently, we support the lifted checking of the marked graph, state-machine, and (extended) free-choice properties, which avoids their analysis on each particular net of the product line in isolation. We demonstrate the feasibility of our proposal using examples in the domain of exible assembly lines, and introduce an extensible tool infrastructure. The tool is based on Eclipse and FeatureIDE, and permits adding new analysis methods externally. Moreover, we present an evaluation that shows the e ciency gains of our method with respect to an enumerative approach that analyses the properties on every net within the product line separately.Work funded by the Spanish Ministry of Science (RTI2018-095255-B-I00) and the R&D programme of Madrid (P2018/TCS-4314)

Lifted structural invariant analysis of Petri net product lines

Petri nets are commonly used to represent concurrent systems. However, they lack support for modelling and analysing system families, like variants of controllers, different variations of a process model, or the possible configurations of a flexible assembly line. To facilitate modelling potentially large collections of similar systems, in this paper, we enrich Petri nets with variability mechanisms based on product line engineering. Moreover, we present methods for the efficient analysis of the place and transition invariants in all defined versions of a Petri net. Efficiency is achieved by analysing the system family as a whole, instead of analysing each possible net variant separately. For this purpose, we lift the notion of incidence matrix to the product line level, and rely on constraint solving techniques. We present tool support and evaluate the benefits of our techniques on synthetic and realistic examples, achieving in some cases speed-ups of two orders of magnitude with respect to analysing each net variant separatelyThis work has been funded by the Spanish Ministry of Science (PID2021-122270OB-I00) and the R&D programme of Madrid (P2018/TCS-4314

Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

A Review of Building Information Modeling and Simulation as Virtual Representations Under the Digital Twin Concept

Building Information Modeling (BIM) is a highly promising technique for achieving digitalization in the construction industry, widely used in modern construction projects for digitally representing facilities. Nevertheless, retains limitations in terms of representing construction operations. The digital twin concept may potentially overcome these limitations and initiate advanced digital transformation in the construction industry as it has revolutionized the product lifecycle management in the manufacturing industry. This research provides a critical review of applying digital twin in the construction industry. Altogether, 140 papers from related journals and databases were reviewed. The digital aspect of twinning consists of BIM and simulation modeling. These two techniques have been used to create virtual or digital representations of actual buildings and real-world construction processes. However, integrating and applying BIM and simulation modeling according to the digital twin concept remains to be fully studied. Comprehensive evaluations of BIM, simulation modeling, and digital twin will provide a well-defined framework for this research, to identify direction and potential for digital twin in the construction industry, thereby progressing to the next level of digitalization and improvement in construction management practice

Construction and Verification of Performance and Reliability Models

Over the last two decades formal methods have been extended towards performance and reliability evaluation. This paper tries to provide a rather intuitive explanation of the basic concepts and features in this area. Instead of striving for mathematical rigour, the intention is to give an illustrative introduction to the basics of stochastic models, to stochastic modelling using process algebra, and to model checking as a technique to analyse stochastic models

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal