Gerd Gröner

Modeling and validation of business process families

Process modeling is an expensive task that needs to encompass requirements of different stakeholders, assure compliance with different standards, and enable the flexible adaptivity to newly emerging requirements in todays dynamic global market. Identifying reusability of process models is a promising direction towards reducing the costs of process modeling. Recent research has offered several solutions. Such solutions promote effective and formally sound methods for variability modeling and configuration management. However, ensuring behavioral validity of reused process models with respect to the original process models (often referred to as reference process models) is still an open research challenge. To address this challenge, in this paper, we propose the notion of business process families by building upon the well-known software engineering discipline-software product line engineering. Business process families comprise (i) a variability modeling perspective, (ii) a process model template (or reference model), and (iii) mappings between (i) and (ii). For business process families, we propose a correct validation algorithm ensuring that each member of a business process family adheres to the core intended behavior that is specified in the process model template. The proposed validation approach is based on the use of Description Logics, variability is represented by using the well-known Feature Models and behavior of process models is considered in terms of control flow patterns. The paper also reports on the experience gained in two external trial cases and results obtained by measuring the tractability of the implementation of the proposed validation approach.

Model driven engineering with ontology technologies

Ontologies constitute formal models of some aspect of the world that may be used for drawing interesting logical conclusions even for large models. Software models capture relevant characteristics of a software artifact to be developed, yet, most often these software models have limited formal semantics, or the underlying (often graphical) software language varies from case to case in a way that makes it hard if not impossible to fix its semantics. In this contribution, we survey the use of ontology technologies for software modeling in order to carry over advantages from ontology technologies to the software modeling domain. It will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers.

Validation of families of business processes

A Software Product Line (SPL) is a set of programs that are developed as a whole and share a set of common features. Product lines variability is typically specified using problem space models (i.e., feature models), solution space models that specify the realization of functionality and mapping models that link problem and solution space artifacts. In this paper, we consider this concept in the scope of families of business processes, whose specificity is that the solution space is defined with business process models. Solution space models are typically specified as model templates, and thus in the rest of the paper we will refer to business process model templates. While the previous research tackled the concepts of families of business processes, there have been very limited research on their validation.

Online dating recommender systems: the split-complex number approach

A typical recommender setting is based on two kinds of relations: similarity between users (or between objects) and the taste of users towards certain objects. In environments such as online dating websites, these two relations are difficult to separate, as the users can be similar to each other, but also have preferences towards other users, i.e., rate other users. In this paper, we present a novel and unified way to model this duality of the relations by using split-complex numbers, a number system related to the complex numbers that is used in mathematics, physics and other fields. We show that this unified representation is capable of modeling both notions of relations between users in a joint expression and apply it for recommending potential partners. In experiments with the Czech dating website Libimseti.cz we show that our modeling approach leads to an improvement over baseline recommendation methods in this scenario.

Semantic recognition of ontology refactoring

Ontologies are used for sharing information and are often collaboratively developed. They are adapted for different applications and domains resulting in multiple versions of an ontology that are caused by changes and refactorings. Quite often, ontology versions (or parts of them) are syntactical very different but semantically equivalent. While there is existing work on detecting syntactical and structural changes in ontologies, there is still a need in analyzing and recognizing ontology changes and refactorings by a semantically comparison of ontology versions. In our approach, we start with a classification of model refactorings found in software engineering for identifying such refactorings in OWL ontologies using DL reasoning to recognize these refactorings.

Modelling and reasoning in metamodelling enabled ontologies

Ontologies are expected to play an important role in many application domains, as well as in software engineering in general. One problem with using ontologies within software engineering is that while UML, a widely used standard for specifying and constructing the models for a software-intensive system, has a four-layer metamodelling architecture, the standard Web Ontology Language (OWL) does not support reasoning over layered metamodels. OWL 2 provides simple metamodelling by using a punning approach, however, the interpretation function is different based on the context, which leads to non-intuitive results. The OWL FA Language has a well defined metamodelling architecture. However, there is no study and tool for support reasoning over OWL FA. In this paper, we discuss some reasoning tasks in OWL FA. We also introduce the OWL FA Tool kit, a simple tool kit for manipulating and reasoning with OWL FA.

Development and validation of customized process models

Abstract Configurable reference process models encompass common and variable processes of organizations from different business domains. These reference process models are designed and reused to guide and derive customized business processes according to the requirements of stakeholders. The customization process is generally initiated by a configuration step, selecting a subset of the reference process model. Configuration is followed by a customization step, which assumes adapting or extending the configured business process based on the specific or unforeseen requirements. Hence, it is crucial to validate the correctness and compliance of the final customized business process with respect to the patterns and business constraints that are specified in the reference model. In this paper, we firstly introduce a technique to develop a customized process model and then present a set of identified inconsistency patterns that may happen during the configuration of a reference model and the customization of configured process models. Furthermore, we describe our proposed approach including formal representations and algorithms that provide logical reasoning and enable automatic inconsistency detection by leveraging description logic. In order to explore the scalability of the approach, we designed the experiments with various process models sizes and inconsistency distributions. The results of the experiments revealed the scalability of our approach with large size process models (500 activities).

OWLizing: transforming software models to ontologies

Today Model Driven Development (MDD) has a quite high importance in describing and building software systems. Although there are formal methodologies for defining software modeling languages we have analyzed some open challenges. Semantics of software modeling languages often are not defined within the language definition. In addition syntactic well-formedness constraints are often not explicitly defined in the language definition. To tackle these challenges we suggest the use of ontology technologies. Ontology technologies are used to extend the expressive of software modeling languages and to enable automated reasoning on all model artifacts in MDD. In this paper we show methodologies to bridge software modeling with ontology technologies and show applications where to adopt them.

Goal-oriented modeling and verification of feature-oriented product lines

Goal models represent requirements and intentions of a software system. They play an important role in the development life cycle of software product lines (SPLs). In the domain engineering phase, goal models guide the development of variability in SPLs by providing the rationale for the variability, while they are used for the configuration of SPLs in the application engineering phase. However, variability in SPLs, which is represented by feature models, usually has design and implementation-induced constraints. When those constraints are not aligned with variability in goal models, the configuration with goal models becomes error prone. To remedy this problem, we propose a description logic (DL)-based approach to represent both models and their relations in a common DL knowledge base. Moreover, we apply reasoning to detect inconsistencies in the variability of goal and feature models. A formal proof is provided to demonstrate the correctness of the reasoning approach. An empirical evaluation shows computational tractability of the inconsistency detection.

Validation of user intentions in process models

Goal models and business process models are complementary artifacts for capturing the requirements and their execution flow in software engineering. Usually, goal models serve as input for designing business process models, and it requires mappings between both types of models. Due to the large number of possible configurations of elements from both goal models and business process models, developers struggle with the challenge of maintaining consistent configurations of both models and their mappings. Managing these mappings manually is error-prone. In our work, we propose an automated solution that relies on Description Logics and automated reasoners for validating mappings that describe the realization of goals by activities in business process models. The results are the identification of two inconsistency patterns --- strong inconsistency and potential inconsistency, and the development of the corresponding algorithms for detecting inconsistencies.