Riccardo De Masellis

Business artifacts with guard-stage-milestone lifecycles: managing artifact interactions with conditions and events

A promising approach to managing business operations is based on business artifacts, a.k.a. business entities (with lifecycles). These are key conceptual entities that are central to guiding the operations of a business, and whose content changes as they move through those operations. An artifact type includes both an information model that captures all of the business-relevant data about entities of that type, and a lifecycle model, that specifies the possible ways an entity of that type might progress through the business. Two recent papers have introduced and studied the Guard-Stage-Milestone (GSM) meta-model for artifact lifecycles. GSM lifecycles are substantially more declarative than the finite state machine variants studied in most previous work, and support hierarchy and parallelism within a single artifact instance. This paper presents the formal operational semantics of GSM, with an emphasis on how interaction between artifact instances is supported. Such interactions are supported both through testing of conditions against the artifact instances, and through events stemming from changes in artifact instances. Building on a previous result for the single artifact instance case, a key result here shows the equivalence of three different formulations of the GSM semantics for artifact instance interaction. One formulation is based on incremental application of ECA-like rules, one is based on two mathematical properties, and one is based on the use of first-order logic formulas.

Foundations of relational artifacts verification

Artifacts are entities characterized by data of interest (constituting the state of the artifact) in a given business application, and a lifecycle, which constrains the artifacts possible evolutions. In this paper we study relational artifacts, where data are represented by a full fledged relational database, and the lifecycle is described by a temporal/ dynamic formula expressed in µ-calculus. We then consider business processes, modeled as a set of condition/action rules, in which the execution of actions (aka tasks, or atomic services) results in new artifact states. We study conformance of such processes wrt the artifact lifecycle as well as verification of temporal/dynamic properties expressed in µ-calculus. Notice that such systems are infinite-state in general, hence undecidable. However, inspired by recent literature on database dependencies developed for data exchange, we present a natural restriction that makes such systems finite-state, and the above problems decidable.

Description logic knowledge and action bases

Description logic Knowledge and Action Bases (KAB) are a mechanism for providing both a semantically rich representation of the information on the domain of interest in terms of a description logic knowledge base and actions to change such information over time, possibly introducing new objects. We resort to a variant of DL-Lite where the unique name assumption is not enforced and where equality between objects may be asserted and inferred. Actions are specified as sets of conditional effects, where conditions are based on epistemic queries over the knowledge base (TBox and ABox), and effects are expressed in terms of new ABoxes. In this setting, we address verification of temporal properties expressed in a variant of first-order µ-calculus with quantification across states. Notably, we show decidability of verification, under a suitable restriction inspired by the notion of weak acyclicity in data exchange.

Conjunctive Artifact-Centric Services

Artifact-centric services are stateful service descriptions centered around “business artifacts”, which contain both a data schema holding all the data of interest for the service, and a lifecycle schema, which specifies the process that the service enacts. In this paper, the data schemas are full-fledged relational databases, and the lifecycle schemas are specified as sets of condition-action rules, where conditions are evaluated against the current snapshot of the artifact, and where actions are suitable updates to database. The main characteristic of this work is that conditions and actions are based on conjunctive queries. In particular, we exploit recent results in data exchange to specify through tuple-generating-dependencies (tgds) the effects of actions. Using such basis we develop sound and complete verification procedures, which, in spite of the fact that the number of states of an artifact-centric service can be infinite, reduce to the finite case through a suitable use of homomorphism induced by the conjunctive queries.

Monitoring business metaconstraints based on LTL and LDL for finite traces

Runtime monitoring is one of the central tasks to provide operational decision support to running business processes, and check on-the-fly whether they comply with constraints and rules. We study runtime monitoring of properties expressed in LTL on finite traces (LTF f ) and its extension LDF f . LDF f is a powerful logic that captures all monadic second order logic on finite traces, which is obtained by combining regular expressions with LTF f , adopting the syntax of propositional dynamic logic (PDL). Interestingly, in spite of its greater expressivity, LDF f has exactly the same computational complexity of LTF f . We show that LDF f is able to capture, in the logic itself, not only the constraints to be monitored, but also the de-facto standard RV-LTL monitors. This makes it possible to declaratively capture monitoring metaconstraints, i.e., constraints about the evolution of other constraints, and check them by relying on usual logical services for temporal logics instead of ad-hoc algorithms. This, in turn, enables to flexibly monitor constraints depending on the monitoring state of other constraints, e.g., “compensation” constraints that are only checked when others are detected to be violated. In addition, we devise a direct translation of LDF f formulas into nondeterministic automata, avoiding to detour to Buchi automata or alternating automata, and we use it to implement a monitoring plug-in for the ProM suite.

VERIFICATION OF CONJUNCTIVE ARTIFACT-CENTRIC SERVICES

An artifact-centric service is a stateful service that holistically represents both the data and the process in terms of a (dynamic) artifact. An artifact is constituted by a data component, holding all the data of interest for the service, and a lifecycle, which specifies the process that the service enacts. In this paper, we study artifact-centric services whose data component is a full-fledged relational database, queried through (first-order) conjunctive queries, and the lifecycle component is specified as sets of condition-action rules, where actions are tasks invocations, again based on conjunctive queries. Notably, the database can evolve in an unbounded way due to new values (unknown at verification time) inserted by tasks. The main result of the paper is that verification in this setting is decidable under a reasonable restriction on the form of tasks, called weak acyclicity, which we borrow from the recent literature on data exchange. In particular, we develop a sound, complete and terminating verification procedure for sophisticated temporal properties expressed in a first-order variant of μ-calculus.

Monitoring data-aware business constraints with finite state automata

Checking the compliance of a business process execution with respect to a set of regulations is an important issue in several settings. A common way of representing the expected behavior of a process is to describe it as a set of business constraints. Runtime verification and monitoring facilities allow us to continuously determine the state of constraints on the current process execution, and to promptly detect violations at runtime. A plethora of studies has demonstrated that in several settings business constraints can be formalized in terms of temporal logic rules. However, in virtually all existing works the process behavior is mainly modeled in terms of control-flow rules, neglecting the equally important data perspective. In this paper, we overcome this limitation by presenting a novel monitoring approach that tracks streams of process events (that possibly carry data) and verifies if the process execution is compliant with a set of data-aware business constraints, namely constraints not only referring to the temporal evolution of events, but also to the temporal evolution of data. The framework is based on the formal specification of business constraints in terms of first-order linear temporal logic rules. Operationally, these rules are translated into finite state automata for dynamically reasoning on partial, evolving execution traces. We show the versatility of our approach by formalizing (the data-aware extension of) Declare, a declarative, constraint-based process modeling language, and by demonstrating its application on a concrete case dealing with web security.

Verification of description logic knowledge and action bases

We introduce description logic (DL) Knowledge and Action Bases (KAB), a mechanism that provides both a semantically rich representation of the information on the domain of interest in terms of a DL KB and a set of actions to change such information over time, possibly introducing new objects. We resort to a variant of DL-Lite where UNA is not enforced and where equality between objects may be asserted and inferred. Actions are specified as sets of conditional effects, where conditions are based on epistemic queries over the KB (TBox and ABox), and effects are expressed in terms of new ABoxes. We address the verification of temporal properties expressed in a variant of first-order μ-calculus where a controlled form of quantification across states is allowed. Notably, we show decidability of verification, under a suitable restriction inspired by the notion of weak acyclicity in data exchange.

Smart home planning programs

In pervasive (ubiquitous) computing an increasing amount of devices are embedded and interconnected in the users environment, e.g., a smart house. The system needs to adapt to the users varying contexts and goals. The aim is to provide transparent services, reacting to input from the users and to the state of the environment. As users requirements increase and new devices are inserted, new services need to be dynamically created. We present a technique that allows the user to express planning programs (i.e., procedures allowing to go through different states of the environment) and to have it realized through automatic service composition techniques.

Runtime Enforcement of First-Order LTL Properties on Data-Aware Business Processes

This paper studies the following problem: given a relational data schema, a temporal property over the schema, and a process that modifies the data instances, how can we enforce the property during each step of the process execution? Temporal properties are defined using a first-order future time LTL FO-LTL and they are evaluated under finite and fixed domain assumptions. Under such restrictions, existing techniques for monitoring propositional formulas can be used, but they would require exponential space in the size of the domain. Our approach is based on the construction of a first-order automaton that is able to perform the monitoring incrementally and by using exponential space in the size of the property. Technically, we show that our mechanism captures the semantics of FO-LTL on finite but progressing sequences of instances, and it reports satisfaction or dissatisfaction of the property at the earliest possible time.