16,670 research outputs found

    Opaque Service Virtualisation: A Practical Tool for Emulating Endpoint Systems

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    Large enterprise software systems make many complex interactions with other services in their environment. Developing and testing for production-like conditions is therefore a very challenging task. Current approaches include emulation of dependent services using either explicit modelling or record-and-replay approaches. Models require deep knowledge of the target services while record-and-replay is limited in accuracy. Both face developmental and scaling issues. We present a new technique that improves the accuracy of record-and-replay approaches, without requiring prior knowledge of the service protocols. The approach uses Multiple Sequence Alignment to derive message prototypes from recorded system interactions and a scheme to match incoming request messages against prototypes to generate response messages. We use a modified Needleman-Wunsch algorithm for distance calculation during message matching. Our approach has shown greater than 99% accuracy for four evaluated enterprise system messaging protocols. The approach has been successfully integrated into the CA Service Virtualization commercial product to complement its existing techniques.Comment: In Proceedings of the 38th International Conference on Software Engineering Companion (pp. 202-211). arXiv admin note: text overlap with arXiv:1510.0142

    Logs and Models in Engineering Complex Embedded Production Software Systems

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    Emotional Regulation in Synchronous Online Collaborative Learning: A Facial Expression Recognition Study

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    Emotional regulation in learning has been recognised as a critical factor for collaborative learning success. However, the “unobservable” processes of emotion and motivation at the core of learning regulation have challenged the methodological progress to examine and support learners’ regulation. Artificial intelligence (AI) and learning analytics have recently brought novel opportunities for investigating the learning processes. This multidisciplinary study proposes a novel fine-grained approach to provide empirical evidence on the application of these advanced technologies in assessing emotional regulation in synchronous computer-support collaborative learning (CSCL). The study involved eighteen university students (N=18) working collaboratively in groups of three. The process mining analysis was adopted to explore the patterns of emotional regulation in synchronous CSCL, while AI facial expression recognition was used for examining learners’ associated emotions and emotional synchrony in regulatory activities. Our findings establish a foundation for further design of human-centred AI-enhanced support for collaborative learning regulation

    Computational Approaches for Analyzing Latent Social Structures in Open Source Organizing

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    Open source software represents a novel form of organizing that leaves digital trace data for organizational researchers to analyze using computational methods. Computational social science has emerged as an important approach to understanding patterns that represent latent social structures in sociological, organizational, and technical phenomena. Within the context of open and digitalized collaboration the clearest manifestation of computational social science has been social network analysis. While social network analysis is a powerful approach for understanding social phenomena in terms of their latent relational social structure, the network lens does not capture the entirety of social structures. Procedural social structures undergirding recurrent patterns of action form another important element of latent social structure. Analyzing such structures requires alternative methods able to deal with history-dependent patterning of activities. Therefore, we investigate the concepts of latent relational and procedural structures, and discuss computational approaches for analyzing patterns and interdependencies among such structures

    On the Potential of Business Process Management for Digital Entrepreneurship: Findings from a Literature Review

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    Digital ventures face significant organizational challenges when scaling, including increasing sales and employee numbers, that withdraw resources from working on their market offerings. While digital entrepreneurship literature stresses the importance of creating processes that balance structure and flexibility to deal with these challenges, business process management (BPM) literature focuses on improving pre-designed business processes. We reconcile these perspectives in a structured literature review to explore how BPM can support digital venturing. We identify synergies and tensions between BPM and digital entrepreneurship and propose three avenues for future research. These include exploring ambidextrous BPM in digital ventures, treating digital venturing as a business process, and developing capabilities for balancing flexibility and structure. We contribute to information systems research by critically reviewing the literature on BPM and digital entrepreneurship and providing potential areas for future investigation
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