Economic models of quality assurance can be an important tool for decision-makers in software development projects. They enable to base quality assurance planning on economical factors of the product and the used defect-detection techniques. A variety of such models has been proposed but many are too abstract to be used in practice. Furthermore, even the more concrete models lack an integration with existing software development process models to increase their applicability. This paper describes an integration of a thorough stochastic model of the economics of analytical quality assurance with the systems development process model V-Modell XT. The integration is done in a modular way by providing a new process module - a concept directly available in the V-Modell XT for extension purposes - related to analytical quality assurance. In particular, we describe the work products, roles, and activities defined in our new process module and their effects on existing V-Modell XT elements.
Ambler uses process patterns in @cite_10 to describe task-specific self-contained pieces of processes and workflows in a reusable way. Such patterns can be applied to solve complex tasks when needed. St "orrle @cite_20 shows how process patterns can be described in great detail using UML. The idea of process patterns is further refined by @cite_13 in form of a modular and extensible software development process based on collections of independent process components. These process patterns essentially are the basis of the extension mechanism of the V-Modell XT.
@cite_13 @cite_10 @cite_20
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Patterns are widely used for describing software designs, i.e., product structures--but they may also be used to describe process structure, by adapting the well known pattern description schemes to the software process domain. But patterns may also be applied useful to describe process structures. This paper describes, how process patterns may be described using UML. Audit trail patterns generated on behalf of a Unix process canb e used to model the process behavior. Most of the approaches proposed so far use a table of fixed-length patterns to represent the process model. However, variable-length patterns seem to be more naturally suited to model the process behavior, but they are also more difficult to construct. In this paper, we present a novel technique to build a table of variable-length patterns. This technique is based on Teiresias, an algorithm initially developed for discovering rigid patterns in unaligned biological sequences. We evaluate the quality of our technique in a testbed environment, and compare it with the intrusion-detection system proposed by [8], which is based on fixed-length patterns. The results achieved with our novel method are significantly better than those obtained with the original method based on fixed-length patterns. For a system of distributed processes, correctness can be ensured by (statically) checking whether their composition satisfies properties of interest. In contrast, Web services are being designed so that each partner discovers properties of others dynamically, through a published interface. Since the overall system may not be available statically and since each business process is supposed to be relatively simple, we propose to use runtime monitoring of conversations between partners as a means of checking behavioural correctness of the entire web service system. Specifically, we identify a subset of UML 2.0 Sequence Diagrams as a property specification language and show that it is sufficiently expressive for capturing safety and liveness properties. By transforming these diagrams to automata, we enable conformance checking of finite execution traces against the specification. We describe an implementation of our approach as part of an industrial system and report on preliminary experience. Process mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms have problems dealing with such unstructured processes and generate spaghetti-like process models that are hard to comprehend. One reason for such a result can be attributed to constructing process models from raw traces without due pre-processing. In an event log, there can be instances where the system is subjected to similar execution patterns behavior. Discovery of common patterns of invocation of activities in traces (beyond the immediate succession relation) can help in improving the discovery of process models and can assist in defining the conceptual relationship between the tasks activities. In this paper, we characterize and explore the manifestation of commonly used process model constructs in the event log and adopt pattern definitions that capture these manifestations, and propose a means to form abstractions over these patterns. We also propose an iterative method of transformation of traces which can be applied as a pre-processing step for most of today's process mining techniques . The proposed approaches are shown to identify promising patterns and conceptually-valid abstractions on a real-life log. The patterns discussed in this paper have multiple applications such as trace clustering, fault diagnosis anomaly detection besides being an enabler for hierarchical process discovery.