nagini
asmoses
nagini | asmoses | |
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1 | 3 | |
215 | 38 | |
- | - | |
8.4 | 7.8 | |
6 days ago | 8 months ago | |
Python | C++ | |
Mozilla Public License 2.0 | GNU General Public License v3.0 or later |
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nagini
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Show HN: Codemodder – A new codemod library for Java and Python
https://en.wikipedia.org/wiki/Semgrep links to OWASP Source Code Analysis Tools: https://owasp.org/www-community/Source_Code_Analysis_Tools
But what's static analysis or dynamic analysis source code analysis without Formal Verification?
"Nagini: A Static Verifier for Python": https://pm.inf.ethz.ch/publications/EilersMueller18.pdf https://github.com/marcoeilers/nagini :
> However, there is currently virtually no tool support for reasoning about Python programs beyond type safety.
> We present Nagini, a sound verifier for statically-typed, concurrent Python
asmoses
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Show HN: Codemodder – A new codemod library for Java and Python
Thanks for your reply!
I think they called it an FST "Full Syntax Tree", which is probably very similar to a CST "Concrete Syntax Tree". At the time that moses was written, Python's internal AST hadn't sufficient code to mutate sufficiently for moses' designs.
MOSES: Meta-Optimizing Semantic Evolutionary Search :
https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutio... :
> All program evolution algorithms tend to produce bloated, convoluted, redundant programs ("spaghetti code"). To avoid this, MOSES performs reduction at each stage, to bring the program into normal form. The specific normalization used is based on Holman's "elegant normal form", which mixes alternate layers of linear and non-linear operators. The resulting form is far more compact than, say, for example, boolean disjunctive normal form. Normalization eliminates redundant terms, and tends to make the resulting code both more human-readable, and faster to execute.
> The above two techniques, optimization and normalization, allow MOSES to outperform standard genetic programming systems.
https://github.com/opencog/asmoses
MOSES outputs Combo (a LISP), Python as an output transform IIUC, and now Atomese with asmoses, which links to a demo notebook: https://robert-haas.github.io/mevis-docs/code/examples/moses...
Evolutionary algorithm > Convergence: https://en.wikipedia.org/wiki/Evolutionary_algorithm#Converg...
/? mujoco learning to walk [with evolutionary selection / RL Reinforcement Learning]
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Knowledge Graph Reasoning Based on Attention GCN
https://news.ycombinator.com/item?id=38744177 :
> - Indicate degree of confidence in annotation (note that AGI hypergraph systems have TruthValue and also AttentionValue, like attention networks
From " https://news.ycombinator.com/item?id=23787359 :
> How does this compare to MOSES (OpenCog/asmoses) or PLN? https://github.com/opencog/asmoses https://scholar.google.com/scholar?hl=en&as_sdt=0%2C43&q=%22... (2007)
From https://news.ycombinator.com/item?id=35810320 :
> Is there a better way to publish Linked Data with existing tools like LaTeX, PDF, or Word? Which support CSVW? Which support RDF/RDFa/JSON-LD?
What are some alternatives?
Ecosystem - You play God