Model-driven performance evaluation for service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised for the empirical performance evaluation of model-driven developed service systems

iObserve: Integrated Observation and Modeling Techniques to Support Adaptation and Evolution of Software Systems

The goal of iObserve is to develop methods and tools to support evolution and adaptation of long-lived software systems. Future long-living software systems will be engineered using third-party software services and infrastructures. Key challenges for such systems will be caused by dynamic changes of deployment options on cloud platforms. Third-party services and infrastructures are neither owned nor controlled by the users and developers of service-based systems. System users and developers are thus only able to observe third-party services and infrastructures via their interface, but are not able to look into the software and infrastructure that provides those services. In this technical report, we summarize our results of four activities to realize a complete tooling around Kieker, Palladio, and MAMBA, supporting performance and cost prediction, and the evaluation of data privacy in context of geo-locations. Furthermore, the report illustrates our efforts to extend Palladio

VulCurator: A Vulnerability-Fixing Commit Detector

Open-source software (OSS) vulnerability management process is important nowadays, as the number of discovered OSS vulnerabilities is increasing over time. Monitoring vulnerability-fixing commits is a part of the standard process to prevent vulnerability exploitation. Manually detecting vulnerability-fixing commits is, however, time consuming due to the possibly large number of commits to review. Recently, many techniques have been proposed to automatically detect vulnerability-fixing commits using machine learning. These solutions either: (1) did not use deep learning, or (2) use deep learning on only limited sources of information. This paper proposes VulCurator, a tool that leverages deep learning on richer sources of information, including commit messages, code changes and issue reports for vulnerability-fixing commit classifica- tion. Our experimental results show that VulCurator outperforms the state-of-the-art baselines up to 16.1% in terms of F1-score. VulCurator tool is publicly available at https://github.com/ntgiang71096/VFDetector and https://zenodo.org/record/7034132#.Yw3MN-xBzDI, with a demo video at https://youtu.be/uMlFmWSJYOE.Comment: accepted to ESEC/FSE 2022, Tool Demos Trac

06121 Abstracts Collection -- Atomicity: A Unifying Concept in Computer Science

From 19.03.06 to 24.03.06, the Dagstuhl Seminar 06121 ``Atomicity: A Unifying Concept in Computer Science\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Open-Source Software as Catalyzer for Technology Transfer: Kieker’s Development and Lessons Learned

The monitoring framework Kieker commenced as a joint diploma thesis of the University of Oldenburg and a telecommunication provider in 2006,and grew toward a high-quality open-source project during the last years. Meanwhile, Kieker has been and is employed in various projects.Several research groups constitute the open-source community to advance the Kieker framework. In this paper, we review Kieker's history,development, and impact as catalyzer for technology transfer

Semantic Annotation and Information Visualization for Blogposts with refer

The growing amount of documents in archives and blogs results in an increasing challenge for curators and authors to tag, present, and recommend their content to the user. refer comprises a set of powerful tools focusing on Named Entity Linking (NEL) which help authors and curators to semi-automatically analyze a platform’s textual content and semantically annotate it based on Linked Open Data. In refer automated NEL is complemented by manual semantic annotation supported by sophisticated autosuggestion of candidate entities, implemented as publicly available Wordpress plugin. In addition, refer visualizes the semantically enriched documents in a novel navigation interface for improved exploration of the entire content across the platform. The efficiency of the presented approach is supported by a qualitative evaluation of the user interfaces