Abstract: Techniques for determining an age category for an object and identifying objects for memory leak analysis based on age categories are described. An age category classifier generates a set of age categories, each corresponding to a respective time interval. The age category classifier monitors garbage collection processes on the heap. The age category classifier determines a current age category based on a duration of time that has elapsed between (a) an initiation of a current garbage collection cycle and (b) a reference event. The age category classifier identifies objects transferred from one object group to another object group during the current garbage collection cycle. The age category classifier stores the current age category as the transfer age category in the headers of the transferred objects. The transfer age categories of the objects may be used for reducing the number of objects that are analyzed in a memory leak analysis.

Abstract: Techniques for profiling memory leaks are described. In one or more embodiments, a memory profiling system identifies a set of one or more objects on the heap during application runtime. For each respective object in the subset of objects, the memory profiling system stores a set of sample information including timestamp that identifies a time associated with an allocation on the heap memory was performed for the respective object and a stack trace identifying at least one subroutine that triggered the allocation on the heap memory. Responsive to detecting a memory leak, the memory profiling system generates a memory leak profile for at least one object in the subset of objects that is causing the memory leak. The memory leak profile identifies when the allocation on the memory store for the at least one object was performed and information about object that remained live after the potential memory leak.

Abstract: Techniques for determining an age category for an object and identifying objects for memory leak analysis based on age categories are described. An age category classifier generates a set of age categories, each corresponding to a respective time interval. The age category classifier monitors garbage collection processes on the heap. The age category classifier determines a current age category based on a duration of time that has elapsed between (a) an initiation of a current garbage collection cycle and (b) a reference event. The age category classifier identifies objects transferred from one object group to another object group during the current garbage collection cycle. The age category classifier stores the current age category as the transfer age category in the headers of the transferred objects. The transfer age categories of the objects may be used for reducing the number of objects that are analyzed in a memory leak analysis.

Abstract: Techniques for determining an age category for an object and identifying objects for memory leak analysis based on age categories are described. An age category classifier generates a set of age categories, each corresponding to a respective time interval. The age category classifier monitors garbage collection processes on the heap. The age category classifier determines a current age category based on a duration of time that has elapsed between (a) an initiation of a current garbage collection cycle and (b) a reference event. The age category classifier identifies objects transferred from one object group to another object group during the current garbage collection cycle. The age category classifier stores the current age category as the transfer age category in the headers of the transferred objects. The transfer age categories of the objects may be used for reducing the number of objects that are analyzed in a memory leak analysis.

Abstract: Techniques for tuning a virtual machine (VM) startup parameter are disclosed. A network manager initiates VMs, for executing a program, using an initial set of values for VM startup parameters. A VM analysis engine determines performance characteristics for the execution of the program associated with the initial set of values. Based on the performance characteristics, the VM analysis engine selects a modified set of values for the VM startup parameters. The network manager initiates VMs using the modified set of values for the VM startup parameters. The VM analysis engine determines performance characteristics for the execution of the program associated with the modified set of values. If the performance characteristics are improved, the network manager initiates new VMs using the modified set of values for the VM startup parameters. The network manager redirects traffic to the new VMs and terminates existing VMs associated with the initial set of values.

Abstract: Techniques for profiling memory leaks are described. In one or more embodiments, a memory profiling system identifies a set of one or more objects on the heap during application runtime. For each respective object in the subset of objects, the memory profiling system stores a set of sample information including timestamp that identifies a time associated with an allocation on the heap memory was performed for the respective object and a stack trace identifying at least one subroutine that triggered the allocation on the heap memory. Responsive to detecting a memory leak, the memory profiling system generates a memory leak profile for at least one object in the subset of objects that is causing the memory leak. The memory leak profile identifies when the allocation on the memory store for the at least one object was performed and information about object that remained live after the potential memory leak.

Abstract: Techniques for determining an age category for an object and identifying objects for memory leak analysis based on age categories are described. An age category classifier generates a set of age categories, each corresponding to a respective time interval. The age category classifier monitors garbage collection processes on the heap. The age category classifier determines a current age category based on a duration of time that has elapsed between (a) an initiation of a current garbage collection cycle and (b) a reference event. The age category classifier identifies objects transferred from one object group to another object group during the current garbage collection cycle. The age category classifier stores the current age category as the transfer age category in the headers of the transferred objects. The transfer age categories of the objects may be used for reducing the number of objects that are analyzed in a memory leak analysis.

Abstract: Techniques for tuning a virtual machine (VM) startup parameter are disclosed. A network manager initiates VMs, for executing a program, using an initial set of values for VM startup parameters. A VM analysis engine determines performance characteristics for the execution of the program associated with the initial set of values. Based on the performance characteristics, the VM analysis engine selects a modified set of values for the VM startup parameters. The network manager initiates VMs using the modified set of values for the VM startup parameters. The VM analysis engine determines performance characteristics for the execution of the program associated with the modified set of values. If the performance characteristics are improved, the network manager initiates new VMs using the modified set of values for the VM startup parameters. The network manager redirects traffic to the new VMs and terminates existing VMs associated with the initial set of values.