6 projects tagged "BSD Original"
The Glasgow Haskell Compiler is a robust, fully-featured, optimising compiler for the functional programming language Haskell. GHC compiles Haskell to either native code or C. It implements numerous experimental language extensions to Haskell for example concurrency, a foreign language interface, several type-system extensions, exceptions, and so on. GHC comes with a generational garbage collector, a space and time profiler, and a comprehensive set of libraries.
Knit is a new component definition and linking language that can be used with C and assembly code. Knit supports component definitions that require little or no modification to existing code. It automatically schedules component initializers and finalizers and provides an extensible constraint system to detect subtle errors in component composition. Knit provides cross-module inlining that largely eliminates the overheads of componentization, supports component hierarchies, and supports cyclic component dependencies. Knit can be used for any C program, but is especially well suited for use in systems that have many separate components, multiple implementations of the same component, intricate initialization requirements, complex component interdependencies, low-level code and embedded systems, or code that is used in radically different configurations.
DrIFT is a type sensitive preprocessor for Haskell. It extracts type declarations and directives from modules and applies rules to them which generate code. It is intended that the user can add new rules as required. DrIFT automates instance derivation for classes that aren't supported by the standard compilers. In addition, instances can be produced in separate modules to that containing the type declaration. This allows instances to be derived for a type after the original module has been compiled. Simple utility functions can also be produced from a type.
timeplotters is a collection of command line tools for visualizing temporal data. It is especially useful for visualizing data from ad-hoc program logs, helping you to spot patterns and anomalies that you would not otherwise see by just watching how the program works or by looking at the logs with the naked eye. Its input format is tailored to event types typically seen in program logs, and the visualization methods are tailored to the questions typically asked about program performance (e.g. distribution of activity durations).