Fresh Techniques for Memory Profiling of Lazy Functional Programs

Lazy functional languages are known for their semantic elegance. They liberate programmers from many difficult responsibilities, such as the operational details of computations including memory management. However, the productivity and elegant semantics provided by lazy functional languages do not come without a cost. Lazy functional programs often suffer from unpredictable space leaks. For over two decades, various lazy functional implementations have been equipped with memory profiling tools. These tools furnish programmers with valuable information about space demands, but there is still scope for their future development. This dissertation presents two variants of memory profiling tools. The first tool is a hotspot heap profiler which presents information in two forms: profile charts and highlighted hotspots by source occurrence. The profile chart represents a hotspot-construction profile, distributed by hotspot temperatures. Hotspots are also marked in the textual display of source programs with the temperature they represent. Further information about hotspots is given in individual profiles. The second tool is a stack profiler which yields information about producers and construction of stack frames