Alcides Fonseca

Resource-Aware Programming (RAP) is an exploratory research project, funded by FCT.

The RAP project aims to give developers more feedback of the resources (time, memory energy) their programs cost, during the development process. The projects relies on considering cost as a probabilistic function, and relying on Genetic Programming to infer the cost of basic blocks, based on execution traces.

RAP is funded by FCT:

• EXPL/CCI-COM/1306/2021 – Main project (13/01/2022-12/01/2024)
• POR011PRE – Activity Test for Resource-Aware Programming (MN5) (2024)

Team

Software

• GeneticEngine An hybrid of Grammar-Guided and Strongly Typed Genetic Programming in Python.
• Aeon A programming language with liquid types, focused on synthesis
• LiquidJava A library+typechecker + VSCode plugin for Java that adds Liquid Types and TypeState.

Publications

Journal

• Computational prediction of human deep intronic variation (GigaScience)

Conference Proceedings

• Comparing the expressive power of Strongly-Typed and Grammar-Guided Genetic Programming at GECCO 2023
• Ebserver: Automating Resource-Usage Data Collection of Android Applications at MobileSoft 2023
• Domain-Aware Feature Learning with Grammar-Guided Genetic Programming at EuroGP 2023
• Usability-Oriented Design of Liquid Types for Java at ICSE 2023
• Data Types as a More Ergonomic Frontend for Grammar-Guided Genetic Programming at GPCE 2022

Workshop Proceedings

• Comparing Individual Representations in Grammar-Guided Genetic Programming for Glucose Prediction in People with Diabetes at Grammatical Evolution Workshop, GECCO 2023
• Type Systems in Resource-Aware Programming: Opportunities and Challenges at RAW, ICT4S 2022
• An Experience Report on Challenges in Learning the Robot Operating System at ROSE, ICSE 2022
• Figra: evaluating a larger search space for cardumen in automatic program repair at APR, ICSE 2022

Short Papers

• LayeredTypes – Combining dependent and independent type systems at Types 2023
• Benchmarking Representations of Individuals in Grammar-Guided Genetic Programming at Evo* 2022

Demos

• Genetic Engine: Genetic Programming for the Common Programmer at <Programming> 2022
• Dive into LiquidJava ⁠— Extending Java with Liquid Types at <Programming> 2022

Posters

• Genetic Engine: Grammar-Guided Genetic Programming without the Grammar at <Programming> 2022

Master Thesis

• Optimization of feature learning through grammar-guided genetic programming by Leon Ingelse

Funding