Dynamic Recursive Petri Nets

International audienceIn the early two-thousands, Recursive Petri nets (RPN) have been introduced in order to model distributed planning of multi-agent systems for which counters and recursivity were necessary. While having a great expressive power, RPN suffer two limitations: (1) they do not include more general features for transitions like reset arcs, transfer arcs, etc. (2) the initial marking associated the recursive "call" only depends on the calling transition and not on the current marking of the caller. Here we introduce Dynamic Recursive Petri nets (DRPN) which address these issues. We show that the standard extensions of Petri nets for which decidability of the coverability problem is preserved are particular cases of DPRN. Then we establish that w.r.t. coverability languages, DRPN are strictly more expressive than RPN. Finally we prove that the coverability problem is still decidable for DRPN

Service orchestration with priority constraints

Business process management is an operational management approach that focuses on improving business processes. Business processes, i.e., collections of important activities in an organization, are represented in the form of a workflow, an orchestrated and repeatable pattern of activities amenable to automated analysis and control. Priority is an important concept in modeling workflows. We need priority to model cancelable and compensable tasks within transactional business processes. We use the Reo coordination language to model and formally analyze workflows. In this paper, we propose a constraint-based approach to formalize priority in Reo. We introduce special channels to propagate and block priority flows, define their semantics as constraints, and model priority propagation as a constraint satisfaction problem

Agile development with software process mining

Modern companies continue investing more and more in the creation, maintenance and change of software systems, but the proper specification and design of such systems continues to be a challenge. The majority of current approaches either ignore real user and system runtime behavior or consider it only informally. This leads to a rather prescriptive top-down approach to software development. In this paper, we propose a bottom-up approach, which takes event logs (e.g., trace data) of a software system for the analysis of the user and system runtime behavior and for improving the software. We use well-established methods from the area of process mining for this analysis. Moreover, we suggest embedding process mining into the agile development lifecycle. The goal of this position paper is to motivate the need for foundational research in the area of software process mining (applying process mining to software analysis) by showing the relevance and listing open challenges. Our proposal is based on our experiences with analyzing a big productive touristic system. This system was developed using agile methods and process mining could be effectively integrated into the development lifecycle

Using event logs for local correction of process models

\u3cp\u3eDuring the life-cycle of an Information System (IS) its actual behavior may not correspond to the original system model. However, to the IS support it is very important to have the latest model that reflects the current system behavior. To correct the model the information from the event log of the system may be used. In this paper, we consider the problem of process model adjustment (correction) using the information from event log. The input data for this task is the initial process model (a Petri net) and an event log. The result of correction should be a new process model, better reflecting the real IS behavior than the initial model. The new model could be also built from scratch, for example, with the help of one of the known algorithms for automatic synthesis of the process model from an event log. However, this may lead to crucial changes in the structure of the original model, and it will be difficult to compare the new model with the initial one, hindering its understanding and analysis. Then it is important to keep the initial structure of the model as much as possible. In this paper we propose a method for process model correction based on the principle of “divide and conquer”. The initial model is decomposed into several fragments. For each of the fragments its conformance to the event log is checked. Fragments, which do not match the log, are replaced by newly synthesized ones. The new model is then assembled from the fragments via transition fusion. The experiments demonstrate that our correction algorithm gives good results when it is used for correcting local discrepancies. The paper presents the description of the algorithm, the formal justification for its correctness, as well as the results of experimental testing on artificial examples.\u3c/p\u3

Process mining can be applied to software too!

Modern information systems produce tremendous amounts of event data. The area of process mining deals with extracting knowledge from this data. Real-life processes can be effectively discovered, analyzed and optimized with the help of mature process mining techniques. There is a variety of process mining case studies and experience reports from such business areas as healthcare, public, transportation and education. Although nowadays, these techniques are mostly used for discovering business processes. The goal of this industrial paper is to show that process mining can be applied to software too. Here we present and analyze our experiences on applying process mining in different productive software systems used in the touristic domain. Process models and user interface workflows underlie the functional specifications of the systems we experiment with. When the systems are utilized, user interaction is recorded in event logs. After applying process mining methods to these logs, process and user interface flow models are automatically derived. These resulting models provide insight regarding the real usage of the software, motivate the changes in the functional specifications, enable usability improvements and software redesign. Thus, with the help of our examples we demonstrate that process mining facilitates new forms of software analysis. The user interaction with almost every software system can be mined in order to improve the software and to monitor and measure its real usage

Process model repair by detecting unfitting fragments?

\u3cp\u3eProcess models often do not adequately reect the behavior of real-life systems. In the general case, it is possible to construct a new adequate model by applying one of the discovery algorithms. At the same time, there are cases when the original model is of particular value. In such cases, it is better to apply model repair algorithms. Those algorithms construct a model which reects real behavior according to some criteria. Moreover, the repaired model remains as similar to the original one as possible. This paper proposes a modular approach which consists of three parts: (1) decomposing the process model and event log into model fragments and sub-logs, (2) selecting the fragments which need to be repaired, (3) repairing the selected fragments using a process discovery algorithm.\u3c/p\u3

Checking properties of adaptive workflow nets

n this paper we consider adaptive workflow nets, a class of nested nets that allows more comfort and expressive power for modeling adaptability and exception handling in workflow nets. We define two important behavioural properties of adaptive workflow nets: soundness and circumspectness. Soundness means that a proper final marking (state) can be reached from any marking which is reachable from the initial marking, and no garbage will be left. Circumspectness means that the upper layer is always ready to handle any exception that can happen in a lower layer. We define a finite state abstraction for adaptive workflow nets and show that soundness and circumspectness can be verified on this abstraction