Extending Automated FLTL Test Oracles with Diagnostic Support

Pill, Ingo; Wotawa, Franz

doi:10.1109/issrew.2019.00096

Cited by 1 publication

(2 citation statements)

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“…In a subsequent work, Pill and Wotawa (2019) address the problem of explaining why an automated FLTL oracle judged a test case to be failing; in a model-based diagnosis perspective, they are focused on deriving the faulty parts in the formula, those that are relevant to the violation. The aim is to support the software designers/programmers by providing information that can be helpful to come up with the desired repair in the debugging process.…”

Section: Diagnosis Of Dess Specified By Temporal Logical Formulaementioning

confidence: 99%

“…The work by Pill and Wotawa (2018) provides an efficient way to check whether a given finite trace complies with the given specification of the system behavior (this specification is the oracle), which is not the task accomplished by our approach. The work by Pill and Wotawa (2019) is aimed at finding out the faulty parts (typically, the faulty operators) in the specification, given a failing trace, where a trace consists in all the recorded observable events, whereas the task of monitoringbased diagnosis addressed in this paper takes as input an observable event at a time.…”

Section: Diagnosis Of Dess Specified By Temporal Logical Formulaementioning

confidence: 99%

See 1 more Smart Citation

Sequence-Oriented Diagnosis of Discrete-Event Systems

Lamperti,

Trerotola,

Zanella

et al. 2023

jair

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Model-based diagnosis has always been conceived as set-oriented, meaning that a candidate is a set of faults, or faulty components, that explains a collection of observations. This perspective applies equally to both static and dynamical systems. Diagnosis of discrete-event systems (DESs) is no exception: a candidate is traditionally a set of faults, or faulty events, occurring in a trajectory of the DES that conforms with a given sequence of observations. As such, a candidate does not embed any temporal relationship among faults, nor does it account for multiple occurrences of the same fault. To improve diagnostic explanation and support decision making, a sequence-oriented perspective to diagnosis of DESs is presented, where a candidate is a sequence of faults occurring in a trajectory of the DES, called a fault sequence. Since a fault sequence is possibly unbounded, as the same fault may occur an unlimited number of times in the trajectory, the set of (output) candidates may be unbounded also, which contrasts with set-oriented diagnosis, where the set of candidates is bounded by the powerset of the domain of faults. Still, a possibly unbounded set of fault sequences is shown to be a regular language, which can be defined by a regular expression over the domain of faults, a property that makes sequence-oriented diagnosis feasible in practice. The task of monitoring-based diagnosis is considered, where a new candidate set is generated at the occurrence of each observation. The approach is based on three different techniques: .1/ blind diagnosis, with no compiled knowledge, .2/ greedy diagnosis, with total knowledge compilation, and .3/ lazy diagnosis, with partial knowledge compilation. By knowledge we mean a data structure slightly similar to a classical DES diagnoser, which can be generated (compiled) either entirely offline (greedy diagnosis) or incrementally online (lazy diagnosis). Experimental evidence suggests that, among these techniques, only lazy diagnosis may be viable in non-trivial application domains.

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Section: Diagnosis Of Dess Specified By Temporal Logical Formulaementioning

confidence: 99%

Section: Diagnosis Of Dess Specified By Temporal Logical Formulaementioning

confidence: 99%