The increasing availability of astonishing volumes of heterogeneous data when developing and using current IT systems is opening the way to advanced techniques in many fields of system engineering. Quality assurance is not an exception to this rule. The exploitation of this data may provide to all type of stakeholders (from developers to CEOs) evidence about the current behavior of the system, and empower them as to make informed decisions in their daily work.
However, data-driven quality assurance is not for free. Data is often incomplete, unreliable and available in highly heterogeneous forms. Aggregating the data into meaningful quality factors is not always evident, and may highly depend on a particular context, making generalization hard. Big data technologies are required, with the inherent problems of managing such demanding infrastructure. All in all, data-driven system quality assurance is today a challenge.
The DSQA workshop has the goal of exploring the potential of data-driven system quality assurance while understanding and pointing out possible (or proved) solutions to these challenges. Last advancements in research and current state of the practice will be put together in order to better comprehend the potential of this emerging field.
The list of topics includes, but is not limited to:
Authors are invited to submit original, unpublished papers. Simultaneous submissions to other publications and conferences are not permitted. Detailed instructions for electronic paper submission, panel proposals and review process can be found at https://qrs19.techconf.org/submission
Types of submissions are:
The above lengths include the title of the paper, the name and affiliation of each author, a 150-word abstract, and up to 6 keywords.Submission
To be announced