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Dynaplex: analyzing program complexity using dynamically inferred recurrence relations
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Automated Software Engineering
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Introduction to Algorithms
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A Simple and Scalable Static Analysis for Bound Analysis and Amortized Complexity Analysis
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Polynomial Invariants by Linear Algebra
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Non-polynomial Worst-Case Analysis of Recursive Programs
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Automatic Inference of Upper Bounds for Recurrence Relations in Cost Analysis
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A Numerical Abstract Domain Based on Expression Abstraction and Max Operator with Application in Timing Analysis
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SPEED: Symbolic Complexity Bound Analysis
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Amortized Resource Analysis with Polynomial Potential
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Tools and Algorithms for the Construction and Analysis of Systems
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Complexity and Resource Bound Analysis of Imperative Programs Using Difference Constraints
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An inherently iterative computation of ackermann's function
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Termination and Cost Analysis with COSTA and its User Interfaces
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The Daikon system for dynamic detection of likely invariants
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Array programming with NumPy
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Symlnfer: Inferring program invariants using symbolic states
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Compositional recurrence analysis
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WISE: Automated test generation for worst-case complexity
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Using dynamic analysis to discover polynomial and array invariants
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Measuring empirical computational complexity
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Statistical debugging for real-world performance problems
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Complexity verification using guided theorem enumeration
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TiML: a functional language for practical complexity analysis with invariants
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SLING: using dynamic analysis to infer program invariants in separation logic
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Templates and recurrences: better together
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Denotational recurrence extraction for amortized analysis
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DynamiTe: dynamic termination and non-termination proofs
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Static prediction of heap space usage for first-order functional programs
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Software Artifact for the OOPSLA'21 Paper Titled "Dynaplex: Analyzing Program Complexity using Dynamically Inferred Recurrence Relations"
inferredcites →https://doi.org/10.5555/2337223.2337304openalex-snapshot
Using dynamic analysis to discover polynomial and array invariants
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-74776-2_14openalex-snapshot
An Order Theory Framework of Recurrence Equations for Static Cost Analysis – Dynamic Inference of Non-Linear Inequality Invariants
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Efficient Synthesis of Tight Polynomial Upper-Bounds for Systems of Conditional Polynomial Recurrences
inferred← citeshttps://doi.org/10.1007/978-3-032-22723-2_1openalex-snapshot
Modular Automatic Complexity Analysis of Recursive Integer Programs
inferred← citeshttps://doi.org/10.1007/978-3-032-24839-8_3openalex-snapshot
LLM-Guided Fuzzing for Pathological Input Generation
inferred← citeshttps://doi.org/10.1007/978-3-032-32537-2_3openalex-snapshot
KoAT: Automatic Complexity and Termination Analysis of Integer Programs
inferred← citeshttps://doi.org/10.1007/978-3-032-40374-2_18openalex-snapshot
Inferring Empirical Sound Resource Bounds via Symbolic Execution and Linear Programming
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An Intelligent Scheduling System for Large-Scale Online Judging
inferred← citeshttps://doi.org/10.1017/s1471068424000413openalex-snapshot
A Machine Learning-Based Approach for Solving Recurrence Relations and Its use in Cost Analysis of Logic Programs
inferred← citeshttps://doi.org/10.1109/icse-companion55297.2022.9793811openalex-snapshot
Dynaplex: Inferring Asymptotic Runtime Complexity of Recursive Programs
inferred← citeshttps://doi.org/10.1109/saner64311.2025.00095openalex-snapshot
Towards Developing Effective Oracles to Reduce Patch Overfitting in Automated Program Repair
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Invalidator: Automated Patch Correctness Assessment via Semantic and Syntactic Reasoning
inferred← citeshttps://doi.org/10.1145/3611643.3617853openalex-snapshot
Inferring Complexity Bounds from Recurrence Relations
inferred← citeshttps://doi.org/10.1145/3656380openalex-snapshot
Robust Resource Bounds with Static Analysis and Bayesian Inference
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A Formal Treatment of Performance Bugs
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Bringing Invariant Analysis to modern IDEs: The DIG+ Extension for VS Code
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Integrating Resource Analyses via Resource Decomposition
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