JVM-based Techniques for Improving Java Observability

Observability measures the support of computer systems to accurately capture, analyze, and present (collectively observe) the internal information about the systems. Observability frameworks play important roles for program understanding, troubleshooting, performance diagnosis, and optimizations. However, traditional solutions are either expensive or coarse-grained, consequently compromising their utility in accommodating today’s increasingly complex software systems. New solutions are emerging for VM-based languages due to the full control language VMs have over program executions. Existing such solutions, nonetheless, still lack flexibility, have high overhead, or provide limited context information for developing powerful dynamic analyses. In this thesis, we present a VM-based infrastructure, called marker tracing framework (MTF), to address the deficiencies in the existing solutions for providing better observability for VM-based languages. MTF serves as a solid foundation for implementing fine-grained low-overhead program instrumentation. Specifically, MTF allows analysis clients to: 1) define custom events with rich semantics ; 2) specify precisely the program locations where the events should trigger; and 3) adaptively enable/disable the instrumentation at runtime. In addition, MTF-based analysis clients are more powerful by having access to all information available to the VM. To demonstrate the utility and effectiveness of MTF, we present two analysis clients: 1) dynamic typestate analysis with adaptive online program analysis (AOPA); and 2) selective probabilistic calling context analysis (SPCC). In addition, we evaluate the runtime performance of MTF and the typestate client with the DaCapo benchmarks. The results show that: 1) MTF has acceptable runtime overhead when tracing moderate numbers of marker events; and 2) AOPA is highly effective in reducing the event frequency for the dynamic typestate analysis; and 3) language VMs can be exploited to offer greater observability.

Fire Frequency and the Vegetative Mosaic of a Spruce-Fir Forest in Northern Utah

Fire scar and vegetative analysis were used to construct a fire history for the Engelmann spruce/subalpine fir (Picea engelmannii/Abies lasiocarpa) vegetation type of the Utah State University (USU) T. W Daniel Experimental Forest. Three distinct periods of fire frequency were established-presettlement (1700-1855), settlement (1856-1909), and suppression (1910-1990). Mean fire interval (MFI) decreased during the settlement period and greatly increased during the suppression era. The difference was attributed to the influx of ignition sources during the settlement of nearby Cache Valley, located 40 km to the west. Logging and livestock grazing appear to have led to the reduced MFI, which in turn worked as a factor to create the vegetative mosaic now observed on the study area. The increase in MFI during the suppression era permitted the advancement of shade-tolerant species in the understory of the shade-intolerant lodgepole pine (Pinus contorta var. latifolia) and quaking aspen (Populus tremuloides). Continued suppression of disturbance from wildfire will allow the lodgepole pine cover type, which experienced the lowest MFI during the settlement period, to be further invaded by shade-tolerant species, decreasing spatial stand diversity and increasing the risk of more intense fires.