We present the first profiler for a compiled, non-strict, higher-order, purely functional language capable of measuring time as well as space usage. Our profiler is implemented in a production-quality optimising compiler for Haskell, has low overheads, and can successfully profile large applications. A unique feature of our approach is that we give a formal specification of the attribution of execution costs to cost centres. This specification enables us to discuss our design decisions in a precise framework. Since it is not obvious how to map this specification onto a particular implementation, we also present an implementation-oriented operational semantics, and prove it equivalent to the specification. 1 Motivation and overview Everyone knows the importance of profiling tools: the best way to improve a program's performance is to concentrate on the parts of the program which are eating the lion's share of the total space and time resources. One would expect profiling tools to be ...

Profiling tools, which measure and display the dynamic space and time behaviour of programs, are essential for identifying execution bottlenecks. A variety of such tools exist for conventional languages, but almost none for non-strict functional languages. There is a good reason for this: lazy evaluation means that the program is executed in an order which is not immediately apparent from the source code, so it is difficult to relate dynamically-gathered statistics back to the original source. This thesis examines the difficulties of profiling lazy higher-order functional languages and develops a profiling tool which overcomes them. It relates information about both the time and space requirements of the program back to the original source expressions identified by the programmer. Considerable attention is paid to the cost semantics with two abstract cost semantics, lexical scoping and evaluation scoping, being investigated. Experience gained from the two profiling schemes led to the d...

Profiling tools, which measure and display the dynamic space and time behaviour of programs, are essential for identifying execution bottlenecks. A variety of such tools exist for conventional languages, but almost none for non-strict functional languages. There is a good reason for this: lazy evaluation means that the program is executed in an order which is not immediately apparent from the source code, so it is difficult to relate dynamically-gathered statistics back to the original source. This thesis examines the difficulties of profiling lazy higher-order functional languages and develops a profiling tool which overcomes them. It relates information about both the time and space requirements of the program back to the original source expressions identified by the programmer. Considerable attention is paid to the cost semantics with two abstract cost semantics, lexical scoping and evaluation scoping, being investigated. Experience gained from the two profiling schemes led to the d...