Visualizing the Evaluation of Functional Programs for Debugging
November 01, 2024 Β· Declared Dead Β· π Slate
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
John Whitington, Tom Ridge
arXiv ID
2411.00618
Category
cs.PL: Programming Languages
Citations
4
Venue
Slate
Last Checked
4 months ago
Abstract
In this position paper, we present a prototype of a visualizer for functional programs. Such programs, whose evaluation model is the reduction of an expression to a value through repeated application of rewriting rules, and which tend to make little or no use of mutable state, are amenable to visualization in the same fashion as simple mathematical expressions, with which every schoolchild is familiar. We show how such visualizations may be produced for the strict functional language OCaml, by direct interpretation of the abstract syntax tree and appropriate pretty-printing. We describe (and begin to address) the challenges of presenting such program traces in limited space and of identifying their essential elements, so that our methods will one day be practical for more than toy programs. We consider the problems posed by the parts of modern functional programming which are not purely functional such as mutable state, input/output and exceptions. We describe initial work on the use of such visualizations to address the problem of program debugging, which is our ultimate aim.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Programming Languages
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
R.I.P.
π»
Ghosted
Glow: Graph Lowering Compiler Techniques for Neural Networks
R.I.P.
π»
Ghosted
Learnable Programming: Blocks and Beyond
R.I.P.
π»
Ghosted
Scenic: A Language for Scenario Specification and Scene Generation
R.I.P.
π»
Ghosted
Vandal: A Scalable Security Analysis Framework for Smart Contracts
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted