A computational process being performed by a memory analysis tool residing in a memory of a memory analysis computer system which is configured with a memory analysis aid for assisting detection of memory leaks in a software program which has a processing load and which uses the memory, wherein some of the memory is in form of heap memory, the process comprising: (a) obtaining, by a memory analysis tool residing in the memory, memory usage data which includes memory usage samples which collectively specify a plurality of data types, each memory usage sample specifying a value of at least one usage statistic for at least one of the data types at a specified sample time, wherein the memory usage samples of the memory heap are collected periodically on a production agent by a sampling agent executing at said memory analysis computer system; (b) computationally identifying, by the memory analysis tool, respective memory usage trends over time for a plurality of the data types, by processing at least part of the memory usage data with a processor, wherein the computationally identifying includes performing simple linear regression using least squares to fit usage statistics to a linear trend; (c) computationally searching, by the memory analysis tool, for correlations between data type memory usage trends, wherein the searching is accomplished by computing statistical measures of distances between pairs or other tuples of the data type memory usage trends, and then comparing results with a predetermined threshold, wherein different statistical measures define different trend correlation criteria; (d) computationally grouping, by the memory analysis tool, data types into memory-usage-trend-correlated groups based on the computed statistical measures of the distances between pairs or other tuples of the data type memory usage trends, wherein all data types in a given memory-usage-trend-correlated group have memory usage trends that satisfy a predetermined trend correlation criterion, and wherein data types whose trends do not satisfy the predetermined trend correlation criterion are not in the given memory-usage-trend-correlated group; and (e) utilizing, by the memory analysis tool, a result of the grouping step and displaying, by the memory analysis tool, memory usage analysis information about the data type groupings, wherein the memory usage analysis information comprises names of the data type names, leak rates, leak sizes indicating memory space lost, and/or leak counts indicating the number of data items in lost memory space, the data type names being of data types which are in a group of the memory-usage-trend-correlated groups being identified to a user as having the most memory leakage, the memory analysis aid statistically analyzing the data type memory usage trends to calculate leak metrics. (a) obtaining, by a memory analysis tool residing in the memory, memory usage data which includes memory usage samples which collectively specify a plurality of data types, each memory usage sample specifying a value of at least one usage statistic for at least one of the data types at a specified sample time, wherein the memory usage samples of the memory heap are collected periodically on a production agent by a sampling agent executing at said memory analysis computer system; (b) computationally identifying, by the memory analysis tool, respective memory usage trends over time for a plurality of the data types, by processing at least part of the memory usage data with a processor, wherein the computationally identifying includes performing simple linear regression using least squares to fit usage statistics to a linear trend; (c) computationally searching, by the memory analysis tool, for correlations between data type memory usage trends, wherein the searching is accomplished by computing statistical measures of distances between pairs or other tuples of the data type memory usage trends, and then comparing results with a predetermined threshold, wherein different statistical measures define different trend correlation criteria; (d) computationally grouping, by the memory analysis tool, data types into memory-usage-trend-correlated groups based on the computed statistical measures of the distances between pairs or other tuples of the data type memory usage trends, wherein all data types in a given memory-usage-trend-correlated group have memory usage trends that satisfy a predetermined trend correlation criterion, and wherein data types whose trends do not satisfy the predetermined trend correlation criterion are not in the given memory-usage-trend-correlated group; and (e) utilizing, by the memory analysis tool, a result of the grouping step and displaying, by the memory analysis tool, memory usage analysis information about the data type groupings, wherein the memory usage analysis information comprises names of the data type names, leak rates, leak sizes indicating memory space lost, and/or leak counts indicating the number of data items in lost memory space, the data type names being of data types which are in a group of the memory-usage-trend-correlated groups being identified to a user as having the most memory leakage, the memory analysis aid statistically analyzing the data type memory usage trends to calculate leak metrics.