A computer-implemented method for memory suspect detection, the method comprising: systematically executing a plurality of transactions of an application to generate metrics, the plurality of transactions associated with suspected memory allocations, the suspected memory allocations associated with one or more of classes known for common memory issues, classes associated with memory issues from previous executions, and classes associated with user interest; periodically capturing the metrics generated while systematically executing the plurality of transactions, the metrics generated on execution of one of the plurality of transactions comprises at least a memory allocation information associated with the one of the plurality of transactions, wherein the memory allocation information comprises a memory allocation type, a timestamp, a size, and an origin of memory allocation, wherein the metrics are referred to as memory snapshots that are captured at the beginning and at the end of a memory monitoring session termed as a baseline snapshots and during the memory monitoring session termed as intermediate snapshots; performing analytics on the periodically captured metrics of each of the plurality of transactions to determine a change in count and size of each type or class of memory allocations by parsing the metrics across the memory screenshots to generate a memory suspect list, wherein for each of the memory allocation information, a comparison is made between multiple memory snapshots to determine change in count, size of each type or class of objects; and identifying, a set of transactions from amongst the plurality of transactions impacted due to the suspected memory allocations based on the change in count and size of each type or class of memory allocations, and a graphical pattern is generated for all object types which have a net increase in overall memory size or count in comparison with a baseline start snapshot and a baseline end snapshot, wherein a slope is computed for the graphical pattern by considering multiple point along the graphical pattern in which the object types with highest average positive slope values and no negative slopes are listed in descending order, wherein if the slope is zero or negative or a combination of positive and negative with a net trend of negative, then the object types are not categorized as memory suspects, wherein if the slope is linear and positive or the net combined average slope is positive, then the object types are candidates for memory suspects. systematically executing a plurality of transactions of an application to generate metrics, the plurality of transactions associated with suspected memory allocations, the suspected memory allocations associated with one or more of classes known for common memory issues, classes associated with memory issues from previous executions, and classes associated with user interest; periodically capturing the metrics generated while systematically executing the plurality of transactions, the metrics generated on execution of one of the plurality of transactions comprises at least a memory allocation information associated with the one of the plurality of transactions, wherein the memory allocation information comprises a memory allocation type, a timestamp, a size, and an origin of memory allocation, wherein the metrics are referred to as memory snapshots that are captured at the beginning and at the end of a memory monitoring session termed as a baseline snapshots and during the memory monitoring session termed as intermediate snapshots; performing analytics on the periodically captured metrics of each of the plurality of transactions to determine a change in count and size of each type or class of memory allocations by parsing the metrics across the memory screenshots to generate a memory suspect list, wherein for each of the memory allocation information, a comparison is made between multiple memory snapshots to determine change in count, size of each type or class of objects; and identifying, a set of transactions from amongst the plurality of transactions impacted due to the suspected memory allocations based on the change in count and size of each type or class of memory allocations, and a graphical pattern is generated for all object types which have a net increase in overall memory size or count in comparison with a baseline start snapshot and a baseline end snapshot, wherein a slope is computed for the graphical pattern by considering multiple point along the graphical pattern in which the object types with highest average positive slope values and no negative slopes are listed in descending order, wherein if the slope is zero or negative or a combination of positive and negative with a net trend of negative, then the object types are not categorized as memory suspects, wherein if the slope is linear and positive or the net combined average slope is positive, then the object types are candidates for memory suspects.