"Large language models are achieving state-of-the-art results across a wide variety of domains, eclipsing past work in well-studied areas like auto-completion. I argue that they also presage a "Cambrian explosion"—a wave of radically new AI-powered software development tools that will make all our lives easier. I propose a paradigm for how we can best rethink existing tools to leverage a combination of LLMs and PL technologies like static and dynamic analysis. This approach promises to evolve our software tools far beyond their current capacities, including profilers that suggest optimizations, debuggers that identify and propose fixes using real-world knowledge, coverage analyzers that synthesize new tests, compilers that propose fixes for compile-time errors, and data analysis frameworks that analyze your data."
from the youtube description:
"Large language models are achieving state-of-the-art results across a wide variety of domains, eclipsing past work in well-studied areas like auto-completion. I argue that they also presage a "Cambrian explosion"—a wave of radically new AI-powered software development tools that will make all our lives easier. I propose a paradigm for how we can best rethink existing tools to leverage a combination of LLMs and PL technologies like static and dynamic analysis. This approach promises to evolve our software tools far beyond their current capacities, including profilers that suggest optimizations, debuggers that identify and propose fixes using real-world knowledge, coverage analyzers that synthesize new tests, compilers that propose fixes for compile-time errors, and data analysis frameworks that analyze your data."
Some links from the presentation
- https://github.com/plasma-umass#plasma-projects
- https://github.com/stephenfreund/flowco
Plasma - projects:
- RightTyper: Automatically annotates your Python code with high-quality types - https://github.com/righttyper/righttyper
- Scalene: A state-of-the-art CPU+GPU+memory profiler for Python, with AI-powered optimization suggestions GitHub stars - https://github.com/plasma-umass/scalene
- Coz: A causal profiler that tells you where to optimize your code (C/C++/Rust/Swift/Java) - https://github.com/plasma-umass/coz
- CSrankings: Ranks the world's CS departments - https://csrankings.org/
- CoverUp: Automatically generates high-coverage tests - https://github.com/plasma-umass/coverup
- Slipcover: Nearly zero-overhead code coverage analysis for Python - https://github.com/plasma-umass/slipcover
- ChatDBG: AI-assisted debugging in lldb, gdb, and pdb. Uses AI to answer 'why' - https://github.com/plasma-umass/ChatDBG
- CWhy: ("See why") Explains and suggests fixes for C/C++/Rust compiler error messages. - https://github.com/plasma-umass/CWhy
- Commentator: Automatically comments Python code, adding docstrings and type annotations - https://github.com/plasma-umass/commentator
- SQLwrite: SQLite3 with natural language to SQL, recommends indexes to optimize queries - https://github.com/plasma-umass/sqlwrite