We describe the design, implementation and use of a new kind of profiling tool that yields valuable information about the memory use of lazy functional programs. The tool has two parts: a modified functional language implementation which generates profiling information during the execution of programs, and a separate program which converts this information to graphical form. With the aid of profile graphs, one can make alterations to a functional program which dramatically reduce its space consumption. We demonstrate this in the case of a genuine example --- the first to which the tool was applied --- for which the results are strikingly successful.

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...