ASKEM_SKEMA_Milestone_8
ASKEM SKEMA Milestone 8 release. This includes:
- Code2FN
- TS2CAST Fortran front-end (tree-sitter based, version 1)
- Supports ingest of TIE-GCM cpktkm.F and cons.F, producing GrometFNModuleCollection
- handling continuation lines: '|' and '&'
- variable declaration and literal value creation
- single and multiple dimension array declaration, get, set and slice
- subroutine and function definition and calls
- primitive operators
- do loop (Fortran idiom similar to Python for-loop)
- if, else, else-if support
- Updates to FN Loop and Conditional representation
- removed explicit Loop/Conditional box wiring
- fixed handling of for-loop iterator loop condition test
- Handling compound conditions
- Improved support for comprehensions
- Support for functions as first-class objects
- bookkeeping of symbol table and variable environment: functions, records (classes) and variables
- CAST updates
- generalization of LiteralValue, removing specific types
- generalization of operator
- porting of cast_to_agraph.py
- Progress on GroMEt FN Execution Engine
- implemented algorithm to walk FN graph in execution order
- developed v1 execution framework primitive operator set
- API and infrastructure improvements
- front-end determines language type based on file extension
- FN diff utility
- General refactoring and name cleanup
- TS2CAST Fortran front-end (tree-sitter based, version 1)
- TextReading
- Version 1 of automated code comment linking
- Added additional grounding mechanisms to TR pipeline
- gazatteer-based grounding and composable grounding pipeline
- delegate grounding to MIRA's web API
- Added support for additional input formats, in addition to COSMOS
- plain text
- grounding through web API
- Created docker file to build a docker image compliant with xDD
- Created (with MIT) library to read and write extractions in canonical JSON format
- Expanded support for initial mention linker to support multi-module GroMEt FN
- Exposed embedding grounding mechanism on TR web service
- METAL
- Added space weather ontology support
- METAL module development
- Data collection
- generate artificial annotated data using gpt-3.5-turbo
- extracted 514 repositories from GitHub, keeping only 115 with more than 2 stars
- Functions and class definition extracted, creating 5,887 code fragments
- Model architecture
- two independent transformer encoder models initialized with CodeBERT
- Evaluation Plan
- token-level and span-level F1-score
- Data collection
- Eqn Reading
- Improvements to Image2MathML pipeline
- improved train/test data generation from arXiv 2014-2018 corpus
- reprocessed eqn dataset
- Image2MathML model retrained, improving BLEU score to 0.95
- Translating Space Weather Equations to DECAPODES Wiring Diagrams
- Improvements to Image2MathML pipeline
- ISA
- Improvements to equation conversion, including translation to canonical form
- Improvements to alignment visualization
- REST API development
- MORAE
- Improvements to FN-to-PetriNet translation
- Prototype support for edge extractions
- MOVIZ
- added optional JSON configuration specification interface to support drawing partially expanded FNs