Automated regression tests are essential, especially when practicing continuous software engineering techniques. In the case of process -drivenapplications (PDA), the tests must consider executable process models typ...
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ISBN:
(纸本)9798350333350
Automated regression tests are essential, especially when practicing continuous software engineering techniques. In the case of process -drivenapplications (PDA), the tests must consider executable process models typically using the BPMN notation and external software services as crucial parts of the application. The complexity of processes is constantly increasing and hence also the need for more tests to ensure the correctness of the PDA. Running all implemented tests in an arbitrary order is time-consuming and, causes high costs. It is more promising in terms of early fault detection to start with those tests that are more likely affected by the changes which have been implemented for the upcoming release under test. For this purpose, we have identified the different types of modifications at the control flow and activity level and evaluated their impact for the intended test prioritization. Furthermore, our concept considers the impact of adaptions at the data-flow level. The approach has been implemented prototypically for the Camunda BPM platform. Experimental results through various case studies proved an earlier detection of errors compared to traditional process coverage techniques.
Today's business applications are increasingly processdriven, meaning that the main application logic is executed by a dedicate process engine. In addition, component-oriented software development has been attrac...
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ISBN:
(纸本)9783642114816
Today's business applications are increasingly processdriven, meaning that the main application logic is executed by a dedicate process engine. In addition, component-oriented software development has been attracting attention for building complex distributed applications. In this paper we present the experiences gained from building a process-driven biometric identification application which makes use of Grid infrastructures via the Grid Component Model (GCM). GCM, besides guaranteeing access to Grid resources, supports autonomic management of notable parallel composite components. This feature is exploited within our biometric identification application to ensure real time identification of fingerprints. Therefore, we briefly introduce the GCM framework and the process engine used, and we describe the implementation of the application using autonomic GCM components. Finally, we summarize the results, experiences, and lessons learned focusing on the integration of autonomic GCM components and the process-driven approach.
Decision makers increasingly rely on decision support systems for optimal decision making. Recently, special attention has been paid to process-driven decision support systems (PD-DSS) in which a process model prescri...
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ISBN:
(纸本)9783031207051;9783031207068
Decision makers increasingly rely on decision support systems for optimal decision making. Recently, special attention has been paid to process-driven decision support systems (PD-DSS) in which a process model prescribes the invocation sequence of software-based decision support services and the data exchange between them. Thus, it is possible to quickly combine available decision support services as needed for optimally supporting the decision making process of an individual decision maker. However, process modelers may accidentally create a process model which is technically well-formed and executable, but contains functional and behavioral flaws such as redundant or missing services. These flaws may result in inefficient computations or invalid decision recommendations when the corresponding PD-DSS is utilized by a decision maker. In this paper, we therefore propose an approach to validate functionality and behavior of a process model representing a PD-DSS. Our approach is based on expressing flaws as anti-patterns for which the process model can be automatically checked via graph matching. We prototypically implemented our approach and demonstrate its applicability in the context of decision making for energy network planning.
Decision makers in complex business environments have different goals and constraints and therefore require tailored decision support systems (DSS). Following a low-code approach, a tailored DSS can be created by a de...
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ISBN:
(纸本)9783031115103;9783031115097
Decision makers in complex business environments have different goals and constraints and therefore require tailored decision support systems (DSS). Following a low-code approach, a tailored DSS can be created by a decision maker as a process-based composition of existing, interoperable decision support services. Data incompatibilities may be introduced during the design or execution of such a process-driven DSS, e.g., when a service always generates or a decision maker selects data which violates a data constraint of a subsequent service. These incompatibilities cause interrupted or erroneous decision processes. In this paper, we contribute an approach which enables the detection of data incompatibilities in process-driven DSS during process design and execution. Our approach utilizes the JSON Schema specification to define service interfaces and associated type constraints which data produced by services or decision makers can be validated against. We demonstrate our approach in the context of decision support for energy network planning using a prototypical open-source implementation.
Despite their drawbacks, paper-based questionnaires are still used to collect data in many application domains. In the QuestionSys project, we develop an advanced framework that enables domain experts to transform pap...
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ISBN:
(纸本)9783319595368;9783319595351
Despite their drawbacks, paper-based questionnaires are still used to collect data in many application domains. In the QuestionSys project, we develop an advanced framework that enables domain experts to transform paper-based instruments to mobile data collection applications, which then run on smart mobile devices. The framework empowers domain experts to develop robust mobile data collection applications on their own without the need to involve programmers. To realize this vision, a configurator component applying a model-driven approach is developed. As this component shall relieve domain experts from technical issues, it has to be proven that domain experts are actually able to use the configurator properly. The experiment presented in this paper investigates the mental efforts for creating such data collection applications by comparing novices and experts. Results reveal that even novices are able to model instruments with an acceptable number of errors. Altogether, the QuestionSys framework empowers domain experts to develop sophisticated mobile data collection applications by orders of magnitude faster compared to current mobile application development practices.
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