12. Summary, Trends, Research

© O. Nierstrasz PS — Summary, Trends, Research Roadmap  Summary: —Trends in programming paradigms  Research:... —scg.unibe.ch

© O. Nierstrasz PS — Summary, Trends, Research C and C++ Good for:  systems programming  portability Bad for:  learning (very steep learning curve)  rapid application development  maintenance Trends:  increased standardization  generative programming

© O. Nierstrasz PS — Summary, Trends, Research Functional Languages Good for:  equational reasoning  declarative programming Bad for:  OOP  explicit concurrency  run-time efficiency (although constantly improving) Trends:  standardization: Haskell  extensions (concurrency, objects)

© O. Nierstrasz PS — Summary, Trends, Research Lambda Calculus Good for:  simple, operational foundation for sequential programming languages Bad for:  programming Trends:  object calculi  concurrent, distributed calculi (e.g., pi calculus, “join” calculus...)

© O. Nierstrasz PS — Summary, Trends, Research Type Systems Good for:  catching static errors  documenting interfaces  formalizing and reasoning about domains of functions and objects Bad for:  reflection; self-modifying programs Trends:  reasoning about concurrency and other side effects  “pluggable”, optional types

© O. Nierstrasz PS — Summary, Trends, Research Polymorphism Good for:  parametric good for generic containers  subtyping good for frameworks (generic clients)  overloading syntactic convenience (classes in Haskell, overloading in Java)  coercion convenient, but may obscure meaning Bad for:  local reasoning  optimization Trends:  combining subtyping, polymorphism and overloading  exploring alternatives to subtyping (“matching”)

© O. Nierstrasz PS — Summary, Trends, Research Denotational Semantics Good for:  formally and unambiguously specifying languages  sequential languages Bad for:  modelling concurrency and distribution Trends:  “Natural Semantics” (inference rules vs. equations)  concurrent, distributed calculi

© O. Nierstrasz PS — Summary, Trends, Research Logic Programming Good for:  searching (expert systems, graph & tree searching...)  symbolic interpretation Bad for:  debugging  modularity Trends:  constraints  concurrency  modules

© O. Nierstrasz PS — Summary, Trends, Research Object-Oriented Languages Good for:  domain modelling  developing reusable frameworks Bad for:  learning (steep learning curve)  understanding (hard to keep systems well-structured)  semantics (no agreement) Trends:  aspect-oriented programming  prototype-based programming (renaissance)

© O. Nierstrasz PS — Summary, Trends, Research Scripting Languages Good for:  rapid prototyping  high-level programming  reflection; on-the-fly generation and evaluation of programs  gluing components from different environments Bad for:  type-checking; reasoning about program correctness  performance-critical applications Trends:  replacing programming as main development paradigm  scripting web applications

© O. Nierstrasz PS — Summary, Trends, Research Visual Programming Languages Good for:  Simulation, games  GUI programming Bad for:  Complex algorithms  Scale Trends:  Programming for kids  Model transformation

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