Memory leak analysis by usage trends correlation

摘要

Tools and techniques assist developers with the detection of memory leaks by using correlation of data type memory usage trends. In particular, investigations of memory leaks can be prioritized without always resorting to the use of bulky and performance-degrading memory dumps, by using these tools and techniques to identify leaky correlated data types. Data about a program's memory usage is processed to identify memory usage trends over time for respective data types, and the trends are searched for significant correlations. Correlated trends (and hence their corresponding data types) are grouped. Memory usage analysis information is displayed for grouped data types, such as the names of the most rapidly leaking data types, the names of correlated data types, leak rates, and leak amounts in terms of memory size and/or data object counts. Memory usage data may also be correlated with processing load requests to indicate which requests have associated memory leaks.

主权项

1. A computational process for improving the functioning of a computer by assisting detection of memory leaks in a software program which has a processing load and which uses memory, the process comprising:
(a) obtaining 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; (b) computationally identifying 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; (c) computationally searching for correlations between data type memory usage trends, wherein the searching comprises computing statistical measures of distances between pairs or other tuples of the data type memory usage trends; (d) computationally grouping data types into memory-usage-trend-correlated groups based on the computed statistical measures of distances between pairs or other tuples of the data type memory usage trends, such that all data types in a given memory-usage-trend-correlated group have memory usage trends that satisfy a predetermined trend correlation criterion, and data types whose trends do not satisfy the predetermined trend correlation criterion are not in the given memory-usage-trend-correlated group; (e) utilizing a result of the grouping step; (f) computationally searching for correlations between data type memory usage trends and one or more processing load request trends; and (g) presenting to a user a report which includes information, based on said searching, about a correlation between data type memory usage and processing load requests.