Seminar

The D3S Seminar is a regular meeting event of the department members and guest speakers. It is also a regular course Advanced Topics in Distributed and Component-Based Systems I, II (NSWI057, NSWI058). This course is recommended for Ph.D. and advanced graduate students.

Regular meetings take place on Tuesdays at 14:00 in S9 (if not noted otherwise in the schedule below).

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Scheduled seminars

No seminars are currently scheduled.

Passed seminars

In this talk, we will summarize our recent work in the area of using machine learning for self-adaptation of software systems. We focused on the task of providing application-friendly abstractions and tools that would allow the architects to focus on the application business logic rather than on the intricacies of integrating ML into the adaptation loop. We proposed ML-DEECo – an ensemble-based component model with Estimators, which can provide predictions on future and currently unobservable values in the self-adaptive system. The architect only needs to specify the inputs and outputs of the Estimator and the underlying ML model is trained automatically by our ML-DEECo runtime framework.

We will cover recent attempts to automatically detect performance regressions in benchmarking project such as GraalVM. The general aim is to reduce computation costs for benchmarking projects, by reducing number of benchmark runs which are not likely to provide useful information regarding existence of a performance regression.

Reasoning about programs using multiple computational threads is very difficult, because the behaviour of the program might depend on the specific interleaving of operations done by individual threads. Moreover some of the thread interleavings might exhibit a subtle bug in the application. This talk will demonstrate what challenges needs to be tackled when trying to control the thread interleaving of a .NET application in order to force some atomicity violations to manifest.

Test coverage measures what percentage of source code has been executed by a test suite, and it has been used for decades as a metric to assess the quality of tests. Despite its popularity in functional testing, the same quality criteria have seldom been applied to performance testing. Nonetheless, given the considerable costs associated with the design and execution of performance tests, metrics of code coverage could become crucial in the optimization of performance testing activities. In this talk, we will focus on how code coverage can be defined for performance testing, in a way that is compatible with current goals and practices in the field. We will introduce a method to compute code coverage in practice, and we will explore the challenges that arise when compared to functional testing.

The talk will introduce the interpolation-based verification and our contribution to the area.