Kasper Søe Luckow

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Probabilistic software analysis seeks to quantify the likelihood of reaching a target event under uncertain environments. Recent approaches compute probabilities of execution paths using symbolic execution, but do not support nondeterminism. Nondeterminism arises naturally when no suitable probabilistic model can capture a program behavior, e.g., for(More)
We present a novel tool for statically determining the Worst Case Execution Time (WCET) of Java Bytecode-based programs called <i>Tool for Execution Time Analysis of Java bytecode</i> (TetaJ). This tool differentiates itself from existing tools by separating the individual constituents of the execution environment into independent components. The prime(More)
We present HVMTP, a time predictable and portable Java Virtual Machine (JVM) implementation with applications in resource-constrained, hard real-time embedded systems, which implements the Safety Critical Java (SCJ) Level 1 specification. Time predictability is achieved by a combination of time predictable algorithms, exploiting the programming model of(More)
We present a rationale for a selection of tools that assist developers of hard real-time applications to verify that programs conform to a Java real-time profile and that platform-specific resource constraints are satisfied. These tools are specialised instances of more generic static analysis and model checking frameworks. The concepts are illustrated by(More)
We describe Symbolic PathFinder v7 in terms of its updated design addressing the changes of Java PathFinder v7 and of its new optimization when computing path conditions. Furthermore, we describe the Symbolic Execution Tree Extension; a newly added feature that allows for outputting the symbolic execution tree that characterizes the execution paths covered(More)
We describe the design and the capabilities of the static timing analysis tool TetaSARTS that assists in temporal verification of Safety Critical Java (SCJ) systems. The primary functionality of TetaSARTS is schedulability analysis, which takes into account the scheduling policy and task interactions. TetaSARTS also facilitates analysing processor(More)