aiplan4eu/unified-planning
Mar 2026 – Mar 2026
1 Month active
Languages Used
Python
Technical Skills
Domain ModelingPDDLParser DevelopmentPythonUnit Testingdomain-specific languages
Joan Espasa Arxer
PROFILE
Joan Espasa Arxer
Worked on the aiplan4eu/unified-planning repository to enhance the expressiveness of planning models by implementing support for object-specific fluents in PDDL parsing and domain/problem definitions. Leveraged Python and domain modeling expertise to extend the parser, enabling more nuanced planning scenarios. Focused on parser development and unit testing to ensure robust integration of new features. Improved the maintainability and readability of the PDDL I/O test suite by consolidating assertions and refining code formatting. The work addressed both functional and quality aspects, laying a foundation for broader planning algorithm support and facilitating future development in domain-specific languages and software testing.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
323
Activity Months1
Your Network
17 peopleShared Repositories
17
Arthur Bit-MonnotMember
AlelafarMember
Alessandro ValentiniMember
Andrea MicheliMember
Enrico ScalaMember
Enrico ScalaMember
Enrico ScalaMember
Luca FrambaMember
Gabi RoegerMember
Work History
March 2026
3 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary for the aiplan4eu/unified-planning project, focusing on delivering expressiveness in planning models and improving test quality. The month centered on enabling object-specific fluents in PDDL parsing and domain/problem definitions, plus targeted test code formatting improvements to boost maintainability and readability.
3 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary for the aiplan4eu/unified-planning project, focusing on delivering expressiveness in planning models and improving test quality. The month centered on enabling object-specific fluents in PDDL parsing and domain/problem definitions, plus targeted test code formatting improvements to boost maintainability and readability.
March 2026
Activity
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Quality Metrics
Correctness93.4%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage26.6%
Skills & Technologies
Programming Languages
Python
Technical Skills
Domain ModelingPDDLParser DevelopmentPythonUnit Testingdomain-specific languagesparser developmentplanning algorithmssoftware testingunit testing
Repositories Contributed To
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