Automated Author Profile

Bianculli, Domenico

University of Luxembourg

Current S-Index

1.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.4

Average Dataset Index per dataset

Total Datasets

4

Total datasets for this author

Average FAIR Score

76.0%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Stress Testing CPS - Crazyflie dataset (Version: 0.1)

This dataset contains the test traces generated for the Crazyflie case study of the paper "Stress Testing Control Loops in Cyber Physical Systems". Simply copy the content of the unpacked folder in the code repository and instead of re-executing the tests, the code will use the pre-generated traces.

Authors

  • Mandrioli, Claudio ;
  • Shin, Seung Yeob ;
  • Maggio, Martina ;
  • Bianculli, Domenico ;
  • Briand, Lionel
0 Citations0 Mentions79% FAIR0.4 Dataset Index
10.5281/zenodo.80427752023

Stress Testing CPS - Lightweight Aircraft dataset

This dataset contains the test traces generated for the Lightweight Aircraft case study of the paper "Stress Testing Control Loops in Cyber Physical Systems". Simply copy the unpacked folder in the code repository of the testing approach matlab implementation and instead of re-executing the tests, the code will use the pre-generated traces.

Authors

  • Mandrioli, Claudio ;
  • Shin, Seung Yeob ;
  • Maggio, Martina ;
  • Bianculli, Domenico ;
  • Briand, Lionel
0 Citations0 Mentions79% FAIR0.4 Dataset Index
10.5281/zenodo.80428692023

Stress Testing CPS - DCservo dataset

This dataset contains the test traces generated for the DC servo case study of the paper "Stress Testing Control Loops in Cyber Physical Systems". Simply copy the unpacked folder in the code repository of the testing approach matlab implementation and instead of re-executing the tests, the code will use the pre-generated traces.

Authors

  • Mandrioli, Claudio ;
  • Shin, Seung Yeob ;
  • Maggio, Martina ;
  • Bianculli, Domenico ;
  • Briand, Lionel
0 Citations0 Mentions73% FAIR0.4 Dataset Index
10.5281/zenodo.80429302023

Efficient Large-Scale Trace Checking Using Mapreduce

The problem of checking a logged event trace against a temporal logic specification arises in many practical cases. Unfortunately, known algorithms for an expressive logic like MTL (Metric Temporal Logic) do not scale with respect to two crucial dimensions: the length of the trace and the size of the time interval for which logged events must be buffered to check satisfaction of the specification. The former issue can be addressed by distributed and parallel trace checking algorithms that can take advantage of modern cloud computing and programming frameworks like MapReduce. Still, the latter issue remains open with current state-of-the-art approaches. In this paper we address this memory scalability issue by proposing a new semantics for MTL, called lazy semantics. This semantics can evaluate temporal formulae and boolean combinations of temporal-only formulae at any arbitrary time instant. We prove that lazy semantics is more expressive than standard point-based semantics and that it can be used as a basis for a correct parametric decomposition of any MTL formula into an equivalent one with smaller, bounded time intervals. We use lazy semantics to extend our previous distributed trace checking algorithm for MTL. We evaluate the proposed algorithm in terms of memory scalability and time/memory tradeoffs.

Authors

  • Bersani, Marcello M. ;
  • Bianculli, Domenico ;
  • Ghezzi, Carlo ;
  • Srdan Krstic ;
  • Pietro, Pierluigi San
0 Citations0 Mentions73% FAIR0.4 Dataset Index
10.5281/zenodo.586802016