1st Workshop on Big Software In-Vivo Analytics (SoVivA'17)


Software systems have grown increasingly large and complex in today's highly interconnected world. Communication, production, healthcare, transportation and education all increasingly rely on “Big Software”. This increasing dependence makes reliable software systems a major concern and stresses the need for effective prediction of software failures. Since software is evolving and operates in a highly dynamic and changing environment, it becomes difficult if not impossible to anticipate all problems at design-time. Because trends like Devops blur the lines between development and deployment, system validation shifts from testing and verification at design time to monitoring at run time: only at run time do we know the application context which is necessary for certain analyses and - if needed - interventions. The mission of this workshop is to advance and provide a scientific basis for in-vivo software analytics, and to bring together researchers interested in big data analytics for big software. The workshop seeks contributions from researchers and practitioners interested in all aspects of generating, collecting, and analysing event data produced by running systems.


Software forms an integral part of the most complex artifacts built by humans. Modern operating systems, such as Windows or Linux, contain hundreds of millions of program statements, written by thousands of different programmers. Their complexity surpasses the comprehensive abilities of any one individual human being. Moreover, software is increasingly like a living organism, evolving constantly and autonomously. Through continuous delivery, continuous deployment and their successor Devops, software is changing all the time. The software that puts a book in your basket at a web store may have been altered by the time you reach the checkout screen. The key questions here are: How do you tame the complexity of such ever-evolving software and how do you consistently ensure their quality?

The aim of this workshop is to focus on the in vivo analysis of large software systems. By monitoring running systems and logging the stream of events, it becomes possible to check system correctness, to detect security and privacy threats, to diagnose system faults automatically, and to synthesize recommended actions: which components need to be debugged, which components need replacing, which components require more testing with what inputs? And when the system needs to be reconfigured, which components and subsystems should we reconfigure?

This full-day workshop will provide an interactive forum for researchers and participants to exchange ideas and experiences, streamline research on software analytics, identify common grounds of their work, and share lessons and challenges, thereby articulating a vision for the future of in-vivo software analytics.


The workshop seeks interesting and innovative contributions and surveys on methods and tools covering all aspects of generating, collecting, and analysing event data produced by running systems. The workshop also encourages new initiatives of building bridges between design- and run-time analytics of software systems. Whenever possible, authors are strongly encouraged to make their code and data available to be used by other researchers. Topics of interest include, but are not limited to:

  • Run-time monitoring and verification of big software
  • Data stream analytics for big software
  • Scalable process mining algorithms for big software
  • Scalable and interactive visualization techniques of run-time event data
  • Data analytics for detecting and predicting software performance issues
  • Scalable algorithms for detecting defects, predicting violations and supporting online recommendations
  • Privacy-enhanced approaches and techniques for software monitoring and run-time event data analysis
  • Run-time analytics for improving and automating software testing and design
  • Hybrid approaches combining design-time and run-time analytics for big software


  • Submission deadline: May 12, 2017
  • Notification: June 16, 2017
  • Camera ready copy due: July 3, 2017


Authors are invited to submit original, previously unpublished research papers (full papers of 10 pages including references and appendices, and short or position papers of 5 pages) following ESEC guidelines. All papers must be prepared using ACM Proceedings Template and be submitted electronically in PDF using the EasyChair submission system .

Each paper will be reviewed by at least 3 PC members. The selection of papers will be made based on the suitability of the topic for the workshop, the originality of the research and the technical quality and soundness of the approach. We intend to publish the workshop proceedings in the ACM Digital Library.

At least one author of an accepted paper must register and participate in the workshop. Registration is subject to the terms, conditions and procedure of the main ESEC/FSE conference to be found on their website: http://esec-fse17.uni-paderborn.de/


Workshop Organizers

  • Marieke Huisman: University of Twente, the Netherlands
  • Nour Assy: Eindhoven University of Technology, the Netherlands
  • Annibale Panichella: University of Lxembourg, Luxembourg

Program Committee

  • Zekeriya Erkin, Delft University of Technology, the Netherlands
  • Walid Gaaloul, Telecom SudParis, France
  • Joel Greenyer, Leibniz Universität Hannover, Germany
  • Imen Grida Ben Yahia, Orange Labs/France Telecom, France
  • Arnd Hartmanns, University of Twente, the Netherlands
  • Tiziana Margaria, University of Limerick, Republic of Ireland
  • Gordon Pace, University of Malta, Malta
  • Dietmar Pfahl, University of Tartu, Estonia
  • Ji Qi, Eindhoven University of Technology, the Netherlands
  • Ina Schaefer, Technische Universität Braunschweig, Germany
  • Sicco Verwer, Delft University of Technology, the Netherlands
  • Aiko Yamashita, Centrum Wiskunde & Informatica, the Netherlands


Prof. Dr. Marieke Huisman
University of Twente, POBox 217, 7500 AE Enschede, the Netherlands.
Email: m.huisman@utwente.nl