Current State and Challenges
- Need for low-level control over data layout remains (see Resource Ownership and Memory Management.md)
- Modern languages providing this control with greater safety (see Type Systems and Rust Programming Language.md)
- Concurrency solutions all have trade-offs; no one-size-fits-all (see Concurrency and Multicore Programming.md)
- Type systems helping model problem domains and check assumptions (see Type Systems and Rust Programming Language.md)
Open Issues
- No consensus on best approaches to concurrent programming (see Concurrency and Multicore Programming.md)
- GPU programming requires different solutions
- Data center and edge computing scale present new challenges
- Operating system abstractions may need rethinking for distributed computing
Promising Directions
- Message-passing operating systems (e.g., BarrelFish, see Concurrency and Multicore Programming.md)
- Innovation in programming languages (Rust, Swift, Go, Erlang; see Type Systems and Rust Programming Language.md)
- Need to match languages to problem domains (see Functional Programming)
- Require new approaches for massively concurrent and distributed systems (see Concurrency and Multicore Programming.md)