Adjustment Strategies for Non-Compliant Process Instances

Enabling changes at both process type and process instance level is an essential requirement for any adaptive process-aware information system (PAIS). Particularly, it should be possible to migrate a (long-)running process instance to a new type schema version, even if this instance has been individually modified before. Further instance migration must not violate soundness; i.e., structural and behavorial consistency need to be preserved. Compliance has been introduced as basic notion to ensure that instances, whose state has progressed too far, are prohibited from being migrated. However, this also excludes them from further process optimizations, which is not tolerable in many practical settings. This paper introduces a number of strategies for coping with non-compliant instances in the context of process change such that they can benefit from future process type changes on the one hand, but do not run into soundness problems on the other hand. We show, for example, how to automatically adjust process type changes at instance level to enable the migration of a higher number of instances. The different strategies are compared and discussed along existing approaches. Altogether, adequate treatment of non-compliant process instances contributes to full process lifecycle support in adaptive PAIS

Realizing Adaptive Process-aware Information Systems with ADEPT2

In dynamic environments it must be possible to quickly implement new business processes, to enable ad-hoc deviations from the defined business processes on-demand (e.g., by dynamically adding, deleting or moving process activities), and to support dynamic process evolution (i.e., to propagate process schema changes to already running process instances). These fundamental requirements must be met without affecting process consistency and robustness of the process-aware information system. In this paper we describe how these challenges have been addressed in the ADEPT2 process management system. Our overall vision is to provide a next generation technology for the support of dynamic processes, which enables full process lifecycle management and which can be applied to a variety of application domains

An approach for the formal verification of DSP designs using Theorem proving

This paper proposes a framework for the incorporation of formal methods in the design flow of digital signal processing (DSP) systems in a rigorous way. In the proposed approach, DSP descriptions were modeled and verified at different abstraction levels using higher order logic based on the higher order logic (HOL) theorem prover. This framework enables the formal verification of DSP designs that in the past could only be done partially using conventional simulation techniques. To this end, a shallow embedding of DSP descriptions in HOL at the floating-point (FP), fixed-point (FXP), behavioral, register transfer level (RTL), and netlist gate levels is provided. The paper made use of existing formalization of FP theory in HOL and a parallel one developed for FXP arithmetic. The high ability of abstraction in HOL allows a seamless hierarchical verification encompassing the whole DSP design path, starting from top-level FP and FXP algorithmic descriptions down to RTL, and gate level implementations. The paper illustrates the new verification framework on the fast Fourier transform (FFT) algorithm as a case study

Correct Configuration of Process Variants in Provop

When engineering process-aware information systems (PAISs) one of the fundamental challenges is to cope with the variability of business processes. While some progress has been achieved regarding the configuration of process variants, there exists only little work on how to accomplish this in a correct manner. Configuring process variants constitutes a non-trivial challenge when considering the large number of process variants that exist in practice as well as the many syntactical and semantical constraints a configured process variant has to obey in a given context. In previous work we introduced the Provop approach for configuring and managing process variants. This paper picks up the Provop framework and shows how it ensures correctness of configurable process variants by construction. We discuss advanced concepts for the context- and constraint-based configuration of process variants, and show how they can be utilized to ensure correctness of the configured process variants. In this paper we also consider correctness issues in conjunction with dynamic variant re-configurations. Enhancing PAISs with the capability to correctly configure process models fitting to the given application context, and to correctly manage the resulting process variants afterwards, will enable a new quality in PAIS engineering

Time Patterns for Process-aware Information Systems: A Pattern-based Analysis

Formal specification and operational support of time constraints constitute fundamental challenges for any enterprise information system. Although temporal constraints play an important role in the context of long-running business processes, time support is very limited in existing process management systems. By contrast, different kinds of planning tools (e.g., calendar systems and project management tools) provide more sophisticated facilities for handling task-related time constraints, but lack an operational support for business processes. This paper presents a set of 10 time patterns to foster the systematic comparison of these different technologies in respect to time management. The proposed patterns are all based on empirical evidence from several large case studies. In addition, we provide an in-depth evaluation of selected process management systems, calendar systems and project management tools based on the suggested patterns. The presented work will not only facilitate comparison of these different technologies in respect to their support of time constraints, but also make evident that their integration offers promising perspectives in respect to time support for long-running business processes

Dealing with Variability in Process-aware Information Systems: Language Requirements, Features, and Existing Proposals

The increasing adoption of Process-aware Information Systems (PAISs), together with the variability of Business Processes (BPs) across different application contexts, has resulted in large process model repositories with collections of related process model variants. To reduce both costs and occurrence of errors, the explicit management of variability throughout the BP lifecycle becomes crucial. In literature, several proposals dealing with BP variability have been proposed. However, the lack of a method for their systematic comparison makes it difficult to select the most appropriate one meeting current needs best. To close this gap, this work presents an evaluation framework that allows analyzing and comparing the variability support provided by existing proposals developed in the context of BP variability. The framework encompasses a set of language requirements as well as a set of variability support features. While language requirements allow assessing the expressiveness required to explicitly represent variability of different process perspectives, variability support features reflect the tool support required to properly cover such expressiveness. Our evaluation framework has been derived based on an in-depth analysis of several large real-world process scenarios, an extensive literature review, and an analysis of existing PAISs. In this vein, the framework helps to understand BP variability along the BP lifecycle. In addition, it supports PAISs engineers in deciding, which of the existing BP variability proposals meets best their needs

Engineering an Advanced Location-Based Augmented Reality Engine for Smart Mobile Devices

Daily business routines more and more require to access information systems in a mobile manner, while preserving a desktop-like feeling at the same time. The goal of this work is to outline the engineering process of a sophisticated mobile service running on a smartphone. More precisely, we show how to develop the core of a location-based augmented reality engine for the iPhone 4S based on the operating system iOS 5.1 (or higher). We denote this engine as AREA. In particular, we develop concepts for coping with limited resources on a mobile device, while providing a smooth user augmented reality experience at the same time. We further present and develop a suitable application architecture in this context, which easily allows integrating augmented reality with a wide range of applications

Linguistically-Informed Neural Architectures for Lexical, Syntactic and Semantic Tasks in Sanskrit

The primary focus of this thesis is to make Sanskrit manuscripts more accessible to the end-users through natural language technologies. The morphological richness, compounding, free word orderliness, and low-resource nature of Sanskrit pose significant challenges for developing deep learning solutions. We identify four fundamental tasks, which are crucial for developing a robust NLP technology for Sanskrit: word segmentation, dependency parsing, compound type identification, and poetry analysis. The first task, Sanskrit Word Segmentation (SWS), is a fundamental text processing task for any other downstream applications. However, it is challenging due to the sandhi phenomenon that modifies characters at word boundaries. Similarly, the existing dependency parsing approaches struggle with morphologically rich and low-resource languages like Sanskrit. Compound type identification is also challenging for Sanskrit due to the context-sensitive semantic relation between components. All these challenges result in sub-optimal performance in NLP applications like question answering and machine translation. Finally, Sanskrit poetry has not been extensively studied in computational linguistics. While addressing these challenges, this thesis makes various contributions: (1) The thesis proposes linguistically-informed neural architectures for these tasks. (2) We showcase the interpretability and multilingual extension of the proposed systems. (3) Our proposed systems report state-of-the-art performance. (4) Finally, we present a neural toolkit named SanskritShala, a web-based application that provides real-time analysis of input for various NLP tasks. Overall, this thesis contributes to making Sanskrit manuscripts more accessible by developing robust NLP technology and releasing various resources, datasets, and web-based toolkit.Comment: Ph.D. dissertatio

Arrows for knowledge-based circuits

Knowledge-based programs (KBPs) are a formalism for directly relating agents' knowledge and behaviour in a way that has proven useful for specifying distributed systems. Here we present a scheme for compiling KBPs to executable automata in finite environments with a proof of correctness in Isabelle/HOL. We use Arrows, a functional programming abstraction, to structure a prototype domain-specific synchronous language embedded in Haskell. By adapting our compilation scheme to use symbolic representations we can apply it to several examples of reasonable size