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Software engineering practices have been steadily moving towards higher-level programming languages and away from lower-level ones. High-level languages tend to greatly improve safety, productivity, and code maintainability because they handle various implementation details automatically, allowing programmers to focus on their problem domains. However, the gains offered by high-level languages are usually made at the cost of reduced performance: higher-level languages usually consume more memory, run more slowly and require expensive garbage-collecting runtime systems. This trend has been worsening with the increasing adoption of the functional programming paradigm by the industry. Modern programmers are thus faced with a dilemma: should they favor productivity and lower maintenance costs at the expense of performance, or should they focus on performance, to the detriments of almost everything else? The main idea behind this thesis is that we can help solve this dilemma by making advances in type systems, metaprogramming, and compilers technology. In particular, we study how metaprogramming via statically-typed quasiquotation can let programmers define their own domain-specific optimizations in a safe way, while leveraging the latest advances in intermediate program representations. We present the design and implementation of the Squid metaprogramming framework, which extends the Scala programming language with multi-staged programming capabilities and more. We also present different application examples for Squid, including a polymorphic yet efficient library for linear algebra, a stream fusion engine improving on the state of the art, a demonstration of query compilation by rewriting, a staged SQL database system prototype, and a new embedded domain-specific language for expressing queries over collections of data. |
