Enabling Time-Aware Process Support with the ATAPIS Toolset

The proper handling of temporal constraints is crucial for business processes in many application domains. Contemporary process-aware information systems (PAIS), however, lack a sophisticated support of time-aware processes. First of all, at design time it should be possible to specify the temporal constraints of a business process. In turn, this should be accompanied by checking the respective time-aware process schema for inconsistencies that may emerge due to hidden interdependencies among the temporal constraints. The latter is crucial to enable a robust and error-free execution of the time-aware process schema. At run time, corresponding process instances need to be monitored for violations of their temporal constraints. This demo paper presents the ATAPIS Toolset for modeling and enacting time-aware processes. The toolset is based on AristaFlow BPM Suite---an industrial-strength process management system. The ATAPIS Toolset enables process engineers to correctly specify and implement time-aware processes. Further, time-aware process instances can be efficiently executed, whilst monitoring their temporal constraints. Altogether, the ATAPIS Toolset covers the temporal perspective of processes at design as well as run time in a comprehensive way

Dynamic Consistency of Conditional Simple Temporal Networks via Mean Payoff Games: a Singly-Exponential Time DC-Checking

Conditional Simple Temporal Network (CSTN) is a constraint-based graph-formalism for conditional temporal planning. It offers a more flexible formalism than the equivalent CSTP model of Tsamardinos, Vidal and Pollack, from which it was derived mainly as a sound formalization. Three notions of consistency arise for CSTNs and CSTPs: weak, strong, and dynamic. Dynamic consistency is the most interesting notion, but it is also the most challenging and it was conjectured to be hard to assess. Tsamardinos, Vidal and Pollack gave a doubly-exponential time algorithm for deciding whether a CSTN is dynamically-consistent and to produce, in the positive case, a dynamic execution strategy of exponential size. In the present work we offer a proof that deciding whether a CSTN is dynamically-consistent is coNP-hard and provide the first singly-exponential time algorithm for this problem, also producing a dynamic execution strategy whenever the input CSTN is dynamically-consistent. The algorithm is based on a novel connection with Mean Payoff Games, a family of two-player combinatorial games on graphs well known for having applications in model-checking and formal verification. The presentation of such connection is mediated by the Hyper Temporal Network model, a tractable generalization of Simple Temporal Networks whose consistency checking is equivalent to determining Mean Payoff Games. In order to analyze the algorithm we introduce a refined notion of dynamic-consistency, named \epsilon-dynamic-consistency, and present a sharp lower bounding analysis on the critical value of the reaction time \hat{\varepsilon} where the CSTN transits from being, to not being, dynamically-consistent. The proof technique introduced in this analysis of \hat{\varepsilon} is applicable more in general when dealing with linear difference constraints which include strict inequalities

Simple Temporal Networks with Partially Shrinkable Uncertainty (Extended Version)

The Simple Temporal Network with Uncertainty (STNU) model focuses on the representation and evaluation of temporal constraints on time-point variables (timepoints), of which some (i.e., contingent timepoints) cannot be assigned (i.e., executed by the system), but only be observed. Moreover, a temporal constraint is expressed as an admissible range of delays between two timepoints. Regarding the STNU model, it is interesting to determine whether it is possible to execute all the timepoints under the control of the system, while still satisfying all given constraints, no matter when the contingent timepoints happen within the given time ranges (controllability check). Existing approaches assume that the original contingent time range cannot be modified during execution. In real world, however, the allowed time range may change within certain boundaries, but cannot be completely shrunk. To represent such possibility more properly, we propose Simple Temporal Network with Partially Shrinkable Uncertainty (STNPSU) as an extension of STNU. In particular, STNPSUs allow representing a contingent range in a way that can be shrunk during run time as long as shrinking does not go beyond a given threshold. We further show that STNPSUs allow representing STNUs as a special case, while maintaining the same efficiency for both controllability checks and execution

Reducing Dynamic-Consistency (DC) Checking for Conditional Simple Temporal Networks (CSTNs) with Bounded Reaction Times to Standard DC Checking for CSTNs

Recent work on Conditional Simple Temporal Networks (CSTNs) has introduced the problem of checking the dynamic consistency (DC) property for the case where the reaction of an execution strategy to observations is bounded below by some fixed \u3b5 > 0. This paper shows how the \u3b5-DC-checking problem can be easily reduced to the standard DC-checking problem for CSTNs. Given any CSTN S with k observation time-points, the paper defines a new CSTN S0 that is the same as S, except that it includes k new observation time-points. For each observation time-point P? in S that observes some proposition p, the time-point P? in S0 is demoted from an observation time-point to an ordinary time-point; and the job of observing p is taken over by a new observation time-point P0? that is constrained to occur exactly \u3b5 after P?. The paper proves that S is \u3b5-DC if and only if S0 is DC; and shows that the application of the \u3b5-DC- checking constraint-propagation rules to S is equivalent to the application of the corresponding DC-checking constraint-propagation rules to S0. Two versions of these results are presented, depending on whether a dynamic strategy for S0 can react instantaneously or only after some arbitrarily small, positive delay. Finally, the paper demonstrates empirically that the performance of building S0 and DC-checking it is even better than \u3b5-DC-checking the original instance S

Managing Decision Tasks and Events in Time-Aware Business Process Models

Time-aware business process models capture processes where temporal properties and constraints have to be suitably managed to achieve proper completion. Temporal aspects also constrain how decisions are made in processes: while some constraints hold only along certain paths, decision outcomes may be restricted to satisfy temporal constraints. In this paper, we present time-aware BPMN processes and discuss how to: (i) add temporal features to process elements, by considering also the impact of events on temporal constraint management; (ii) characterize decisions based on when they are made and used within a process; (iii) specify and use two novel kinds of decisions based on how their outcomes are managed; (iv) deal with intertwined temporal and decision aspects of time-aware BPMN processes to ensure proper execution

Checking Dynamic Consistency of Conditional Hyper Temporal Networks via Mean Payoff Games (Hardness and (pseudo) Singly-Exponential Time Algorithm)

In this work we introduce the \emph{Conditional Hyper Temporal Network (CHyTN)} model, which is a natural extension and generalization of both the \CSTN and the \HTN model. Our contribution goes as follows. We show that deciding whether a given \CSTN or CHyTN is dynamically consistent is \coNP-hard. Then, we offer a proof that deciding whether a given CHyTN is dynamically consistent is \PSPACE-hard, provided that the input instances are allowed to include both multi-head and multi-tail hyperarcs. In light of this, we continue our study by focusing on CHyTNs that allow only multi-head or only multi-tail hyperarcs, and we offer the first deterministic (pseudo) singly-exponential time algorithm for the problem of checking the dynamic-consistency of such CHyTNs, also producing a dynamic execution strategy whenever the input CHyTN is dynamically consistent. Since \CSTN{s} are a special case of CHyTNs, this provides as a byproduct the first sound-and-complete (pseudo) singly-exponential time algorithm for checking dynamic-consistency in CSTNs. The proposed algorithm is based on a novel connection between CSTN{s}/CHyTN{s} and Mean Payoff Games. The presentation of the connection between \CSTN{s}/CHyTNs and \MPG{s} is mediated by the \HTN model. In order to analyze the algorithm, we introduce a refined notion of dynamic-consistency, named $\epsilon$-dynamic-consistency, and present a sharp lower bounding analysis on the critical value of the reaction time $\hat{\varepsilon}$ where a \CSTN/CHyTN transits from being, to not being, dynamically consistent. The proof technique introduced in this analysis of $\hat{\varepsilon}$ is applicable more generally when dealing with linear difference constraints which include strict inequalities.Comment: arXiv admin note: text overlap with arXiv:1505.0082

Dynamic-Consistency Checking for Conditional Simple Temporal Networks: Strengthening the Theoretical Foundations and Presenting a Faster Algorithm

Recent work on Conditional Simple Temporal Networks (CSTNs) has focused on checking the dynamic consistency (DC) property for the case where an execution strategy can react instantaneously to observations. Three alternative semantics for such strategies\u2014IR-dynamic, 0-dynamic, and \u3c0-dynamic\u2014have been presented. However, the most practical DC-checking algorithm has only been analyzed with respect to the IR semantics. Meanwhile, 0-dynamic strategies were shown to permit a kind of circular dependence among simultaneous observations, making them impossible to implement, whereas \u3c0-dynamic strategies prohibit this kind of circularity. Whether IR-dynamic strategies allow this kind of circularity and, if so, what the consequences would be for the above-mentioned DC-checking algorithm remained open questions. This paper makes the following contributions: (1) it shows that IR-dynamic strategies do allow circular dependence and, thus, that the IR semantics does not properly capture instantaneous reactivity; (2) it shows that one of the constraint-propagation rules from the IR-DC-checking algorithm is unsound with respect to the IR semantics; (3) it presents a simpler DC-checking algorithm, called the \u3c0-DC-checking algorithm, that uses half of the rules from the earlier algorithm, and that it proves is sound and complete with respect to the \u3c0-DC semantics; (4) it empirically evaluates the new algorithm. Thus, the paper places practical DC checking for CSTNs in the case of instantaneous reaction on a solid theoretical foundation