Fuzzing is a widely adopted and pragmatic methodology for bug hunting as a means of software hardening. Research reveals that increasing fuzzing throughput directly increases bug discovery rate. The highest performance fuzzing strategy is persistent fuzzing, which reuses a single process for all test cases by looping back to the start upon completion, instead of exiting. This eliminates all process creation, initialization, and tear-down costs---which are on-par with execution cost. Unfortunately, persistent fuzzing leads to semantically inconsistent program states because process state changes from one test case remain for subsequent test cases. This semantic inconsistency results in missed crashes, false crashes, and overall incorrectness that undermines fuzzer effectiveness.

Few Shot or Single Shot Segmentation of an object part is a challenging problem owing to various factors involving scarcity of part segmentation labels and varying scale and pose of the labeled object part (support-part) in relation to query object whole segment (query-whole). Prior attempts have been made to segment the query object part using additional language guidance with object part labels. Owing to lack of proper definition of an object part or lack of part label descriptions in many scenarios (e.g. an engine part), many real-world situations demand segmenting object parts with guidance from only a visual prompt. We propose to solve the problem of few shot part segmentation using only visual prompt by modeling it as a graph labeling problem. To this end, we introduce a novel super-pixel guided DiNOv2 feature based graph modeling for the whole and part of the support object (visual prompt) and the whole of the query object. We rely on an iterative graph partitioning strategy based on reverse guidance from query to support and converge to the most optimal query part segmentation. We showcase the efficacy of our proposed method in the most exhaustive part segmentation database, ADE20K-Part-234.

We describe the design and implementation of a generic architecture to provide a collective solution for power-aware routing to a wide range of problems in wireless sensor network environments. Power aware-routing is integral to the solutions proposed for a variety of wireless sensor network problems. This can lead to challenging technical problems and deployment barriers when attempting to integrate the proposed solutions. We have identified coupling between sources and sinks as the main factor for different design choices for a range of problems. We developed a core-based hierarchical routing framework and protocol for efficient power-aware routing that is used to decouple the sources from sinks. We show the efficiency of our approach via simulation.