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Mining Timed Regular Specifications from System Traces

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-15579-1_2openalex-snapshot
Automated Program Verification
inferredcites →https://doi.org/10.1007/s100090050010openalex-snapshot
Uppaal in a nutshell
inferredcites →https://doi.org/10.1007/s11241-007-9012-7openalex-snapshot
Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised
inferredcites →https://doi.org/10.1016/0304-3975(94)90010-8openalex-snapshot
A theory of timed automata
inferredcites →https://doi.org/10.1016/j.scico.2007.01.015openalex-snapshot
The Daikon system for dynamic detection of likely invariants
inferredcites →https://doi.org/10.1016/s0019-9958(78)90562-4openalex-snapshot
Complexity of automaton identification from given data
inferredcites →https://doi.org/10.1109/32.908957openalex-snapshot
Dynamically discovering likely program invariants to support program evolution
inferredcites →https://doi.org/10.1109/ase.2015.71openalex-snapshot
General LTL Specification Mining (T)
inferredcites →https://doi.org/10.1109/icse.2003.1201290openalex-snapshot
ICSE workshop on dynamic analysis (WODA 2003)
inferredcites →https://doi.org/10.1109/issre.2004.11openalex-snapshot
Automatically Inferring Temporal Properties for Program Evolution
inferredcites →https://doi.org/10.1109/tse.2011.105openalex-snapshot
Automatically Generating Test Cases for Specification Mining
inferredcites →https://doi.org/10.1145/1029894.1029901openalex-snapshot
Efficient incremental algorithms for dynamic detection of likely invariants
inferredcites →https://doi.org/10.1145/1040305.1040314openalex-snapshot
Synthesis of interface specifications for Java classes
inferredcites →https://doi.org/10.1145/1047659.1040314openalex-snapshot
Synthesis of interface specifications for Java classes
inferredcites →https://doi.org/10.1145/1065579.1065786openalex-snapshot
IODINE
inferredcites →https://doi.org/10.1145/1134285.1134325openalex-snapshot
Perracotta
inferredcites →https://doi.org/10.1145/1146238.1146258openalex-snapshot
From daikon to agitator
inferredcites →https://doi.org/10.1145/1342211.1342215openalex-snapshot
Mining specifications of malicious behavior
inferredcites →https://doi.org/10.1145/1368088.1368157openalex-snapshot
Automatic generation of software behavioral models
inferredcites →https://doi.org/10.1145/1806799.1806806openalex-snapshot
Online inference and enforcement of temporal properties
inferredcites →https://doi.org/10.1145/1831708.1831719openalex-snapshot
Generating test cases for specification mining
inferredcites →https://doi.org/10.1145/1837274.1837466openalex-snapshot
Scalable specification mining for verification and diagnosis
inferredcites →https://doi.org/10.1145/2380445.2380479openalex-snapshot
Dynamic property mining for embedded software
inferredcites →https://doi.org/10.1145/265924.265927openalex-snapshot
Eraser
inferredcites →https://doi.org/10.1145/2975961.2975962openalex-snapshot
Mining timed regular expressions from system traces
inferredcites →https://doi.org/10.1145/302405.302672openalex-snapshot
Patterns in property specifications for finite-state verification
inferredcites →https://doi.org/10.1145/359545.359563openalex-snapshot
Time, clocks, and the ordering of events in a distributed system
inferredcites →https://doi.org/10.1145/502034.502041openalex-snapshot
Bugs as deviant behavior
inferredcites →https://doi.org/10.1145/502059.502041openalex-snapshot
Bugs as deviant behavior
inferredcites →https://doi.org/10.1145/503272.503275openalex-snapshot
Mining specifications
inferredcites →https://doi.org/10.1145/506147.506151openalex-snapshot
Timed regular expressions
inferredcites →https://doi.org/10.1145/565816.503275openalex-snapshot
Mining specifications
inferredcites →https://doi.org/10.1145/581339.581377openalex-snapshot
Tracking down software bugs using automatic anomaly detection
inferredcites →https://doi.org/10.1145/581376.581377openalex-snapshot
Tracking down software bugs using automatic anomaly detection
inferredcites →https://doi.org/10.1145/996821.996832openalex-snapshot
Dynamically inferring temporal properties

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-030-15538-4_15openalex-snapshot
Supporting the Selection of Constraints for Requirements Monitoring from Automatically Mined Constraint Candidates
inferred← citeshttps://doi.org/10.1007/978-3-030-21290-2_41openalex-snapshot
A Constraint Mining Approach to Support Monitoring Cyber-Physical Systems
inferred← citeshttps://doi.org/10.1007/978-3-030-64843-5_20openalex-snapshot
Propositional Projection Temporal Logic Specification Mining
inferred← citeshttps://doi.org/10.1007/978-3-030-85037-1_2openalex-snapshot
On the Complexity of Timed Pattern Matching
inferred← citeshttps://doi.org/10.1007/978-3-031-33170-1_7openalex-snapshot
Learning Symbolic Timed Models from Concrete Timed Data
inferred← citeshttps://doi.org/10.1016/j.compchemeng.2026.109722openalex-snapshot
From differential equations to finite state machines: A new approach for formal verification of chemical processes models
inferred← citeshttps://doi.org/10.1016/j.future.2024.107670openalex-snapshot
Regularity-driven pattern extraction and analysis approach by the pre-pruning technique without pattern loss
inferred← citeshttps://doi.org/10.1016/j.ic.2022.104957openalex-snapshot
Survey on mining signal temporal logic specifications
inferred← citeshttps://doi.org/10.1016/j.sysarc.2020.101876openalex-snapshot
Palisade: A framework for anomaly detection in embedded systems
inferred← citeshttps://doi.org/10.1016/j.tcs.2020.12.032openalex-snapshot
Temporal logic specification mining of programs
inferred← citeshttps://doi.org/10.1109/ijcnn.2019.8852116openalex-snapshot
Deep Learning for System Trace Restoration
inferred← citeshttps://doi.org/10.1109/qrs-c51114.2020.00070openalex-snapshot
QMine: A Framework for Mining Quantitative Regular Expressions from System Traces
inferred← citeshttps://doi.org/10.1109/qrs54544.2021.00093openalex-snapshot
MINTS: Unsupervised Temporal Specifications Miner
inferred← citeshttps://doi.org/10.1109/rtss66672.2025.00033openalex-snapshot
On Synthesis of Timed Regular Expressions
inferred← citeshttps://doi.org/10.1109/smc.2019.8914322openalex-snapshot
A Neural Word Embedding Approach to System Trace Reconstruction
inferred← citeshttps://doi.org/10.1109/smc42975.2020.9282846openalex-snapshot
MA2DF: A Multi-Agent Anomaly Detection Framework
inferred← citeshttps://doi.org/10.1109/smc42975.2020.9282938openalex-snapshot
GWAD: Greedy Workflow Graph Anomaly Detection Framework for System Traces
inferred← citeshttps://doi.org/10.1109/smc52423.2021.9658712openalex-snapshot
Is Timing Critical to Trace Reconstruction?
inferred← citeshttps://doi.org/10.1109/tii.2020.3009985openalex-snapshot
Operational Data-Driven Feedback for Safety Evaluation of Agent-Based Cyber–Physical Systems
inferred← citeshttps://doi.org/10.1145/3387909openalex-snapshot
Monotone Precision and Recall Measures for Comparing Executions and Specifications of Dynamic Systems
inferred← citeshttps://doi.org/10.1145/3433994openalex-snapshot
Offline and Online Learning of Signal Temporal Logic Formulae Using Decision Trees
inferred← citeshttps://doi.org/10.1145/3517194openalex-snapshot
Parametric Timed Pattern Matching
inferred← citeshttps://doi.org/10.1145/3645114openalex-snapshot
Elements of Timed Pattern Matching
inferred← citeshttps://doi.org/10.7287/peerj-cs.210v0.1/reviews/1openalex-snapshot
Peer Review #1 of "Pay attention and you won’t lose it: a deep learning approach to sequence imputation (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.210v0.1/reviews/2openalex-snapshot
Peer Review #2 of "Pay attention and you won’t lose it: a deep learning approach to sequence imputation (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.210v0.1/reviews/3openalex-snapshot
Peer Review #3 of "Pay attention and you won’t lose it: a deep learning approach to sequence imputation (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.210v0.2/reviews/1openalex-snapshot
Peer Review #1 of "Pay attention and you won’t lose it: a deep learning approach to sequence imputation (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj-cs.210openalex-snapshot
Pay attention and you won’t lose it: a deep learning approach to sequence imputation
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