TrEKer: Tracing error propagation in operating system kernels

Coppik, Nicolas; Schwahn, Oliver; Winter, Stefan; Suri, Neeraj

doi:10.1109/ase.2017.8115650

Cited by 6 publications

(7 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our work makes use of TrEKer [10], a technique for tracing error propagation in OS kernels using execution traces at the granularity of individual memory accesses.…”

Section: Error Propagation Analysismentioning

confidence: 99%

“…Prior work has attempted to tackle this issue by introducing additional instrumentation to the faulty module for tracing the modifications made by the faulty module either to the system state or to externally visible parts of its own state [10]. These modifications can then be compared to those made by the non-faulty version of the same module, with the assumption that instances in which the behavior of the faulty version diverges from the non-faulty version constitute potential error propagation.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Fast Kernel Error Propagation Analysis in Virtualized Environments

Coppik

Schwahn

Suri

2021

2021 14th IEEE Conference on Software Testing, Verification and Validation (ICST)

Self Cite

View full text Add to dashboard Cite

Assessing operating system dependability remains a challenging problem, particularly in monolithic systems. Component interfaces are not well-defined and boundaries are not enforced at runtime. This allows faults in individual components to arbitrarily affect other parts of the system. Software fault injection (SFI) can be used to experimentally assess the resilience of such systems in the presence of faulty components. However, applying SFI to complex, monolithic operating systems poses challenges due to long test latencies and the difficulty of detecting corruptions in the internal state of the operating system.In this paper, we present a novel approach that leverages static and dynamic analysis alongside modern operating system and virtual machine features to reduce SFI test latencies for operating system kernel components while enabling efficient and accurate detection of internal state corruptions.We demonstrate the feasibility of our approach by applying it to multiple widely used Linux file systems.

show abstract

“…Our work makes use of TrEKer [10], a technique for tracing error propagation in OS kernels using execution traces at the granularity of individual memory accesses.…”

Section: Error Propagation Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Fast Kernel Error Propagation Analysis in Virtualized Environments

Coppik

Schwahn

Suri

2021

2021 14th IEEE Conference on Software Testing, Verification and Validation (ICST)

Self Cite

View full text Add to dashboard Cite

show abstract

“…6. Reversibility formula build time in seconds (log scale) for blackscholes traces with different input sizes and numbers of threads pose, we generated execution traces of the benchmark with inputs of varying size (2,4,8,16,32 inputs) and varying numbers of threads (1,2,4,6,8,12,16) handling these inputs. We have repeated the reversibility check four times for each input/thread count combination to account for execution time variations.…”

Section: F Rq 4: Tracesanitizer Overheadmentioning

confidence: 99%

“…EPA analyzes how software faults affect program control and data flow at run time. It has many uses such as error detector placement [1], [2] and robustness testing [3]. EPA is typically performed by injecting faults into the program, and comparing the fault-affected (faulty run) against the fault-free (golden run) execution traces, i.e., records of which program instructions have been executed in which order.…”

Section: Introductionmentioning

confidence: 99%

“…The main insight in our work is that EPA in the presence of non-determinism, while being very challenging in the general case, becomes solvable for a specific but important class of programs that satisfy two conditions: (1) exhibit identical externally observable behavior across repeated executions, and (2) are not affected by non-deterministic external functions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

TraceSanitizer - Eliminating the Effects of Non-Determinism on Error Propagation Analysis

Saissi

Winter

Schwahn

et al. 2020

2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

Self Cite

View full text Add to dashboard Cite

Modern computing systems typically relax execution determinism, for instance by allowing the CPU scheduler to interleave the execution of several threads. While beneficial for performance, execution non-determinism affects programs' execution traces and hampers the comparability of repeated executions. We present TraceSanitizer, a novel approach for execution trace comparison in Error Propagation Analyses (EPA) of multi-threaded programs. TraceSanitizer can identify and compensate for nondeterminisms caused either by dynamic memory allocation or by non-deterministic scheduling. We formulate a condition under which TraceSanitizer is guaranteed to achieve a 0% false positive rate and automate its verification using Satisfiability Modulo Theory (SMT) solving techniques. TraceSanitizer is comprehensively evaluated using execution traces from the PARSEC and Phoenix benchmarks. In contrast with other approaches, Trace-Sanitizer eliminates false positives without increasing the false negative rate (for a specific class of programs), with reasonable performance overheads.

show abstract

SqSelect: Automatic assessment of Failed Error Propagation in state-based systems

Ibias

Núñez

2021

Expert Systems with Applications

View full text Add to dashboard Cite

TrEKer: Tracing error propagation in operating system kernels

Cited by 6 publications

References 41 publications

Fast Kernel Error Propagation Analysis in Virtualized Environments

Fast Kernel Error Propagation Analysis in Virtualized Environments

TraceSanitizer - Eliminating the Effects of Non-Determinism on Error Propagation Analysis

SqSelect: Automatic assessment of Failed Error Propagation in state-based systems

Contact Info

Product

Resources

About