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  1. Microservice Architecture (MSA) is rapidly taking over modern software engineering and becoming the predominant architecture of new cloud-based applications (apps). There are many advantages to using MSA, but there are many downsides to using a more complex architecture than a typical monolithic enterprise app. Beyond the normal bad coding practices and code-smells of a typical app, MSA specific code-smells are difficult to discover within a distributed app. There are many static code analysis tools for monolithic apps, but no tool exists to offer code-smell detection for MSA-based apps. This paper proposes a new approach to detect code smells in distributedmore »apps based on MSA. We develop an open-source tool, MSANose, which can accurately detect up to eleven different types of MSA specific code smells. We demonstrate our tool through a case study on a benchmark MSA app and verify its accuracy. Our results show that it is possible to detect code-smells within MSA apps using bytecode and or source code analysis throughout the development or before deployment to production.« less
  2. This article, for the first time, demonstrates Cross-device Deep Learning Side-Channel Attack (X-DeepSCA), achieving an accuracy of > 99.9%, even in presence of significantly higher inter-device variations compared to the inter-key variations. Augmenting traces captured from multiple devices for training and with proper choice of hyper-parameters, the proposed 256-class Deep Neural Network (DNN) learns accurately from the power side-channel leakage of an AES-128 target encryption engine, and an N-trace (N ≤ 10) X-DeepSCA attack breaks different target devices within seconds compared to a few minutes for a correlational power analysis (CPA) attack, thereby increasing the threat surface for embedded devicesmore »significantly. Even for low SNR scenarios, the proposed X-DeepSCA attack achieves ~10× lower minimum traces to disclosure (MTD) compared to a traditional CPA.« less
  3. Heterochromatin is mostly composed of long stretches of repeated DNA sequences prone to ectopic recombination during double-strand break (DSB) repair. In Drosophila, “safe” homologous recombination (HR) repair of heterochromatic DSBs relies on a striking relocalization of repair sites to the nuclear periphery. Central to understanding heterochromatin repair is the ability to investigate the 4D dynamics (movement in space and time) of repair sites. A specific challenge of these studies is preventing phototoxicity and photobleaching effects while imaging the sample over long periods of time, and with sufficient time points and Z-stacks to track repair foci over time. Here we describemore »an optimized approach for high-resolution live imaging of heterochromatic DSBs in Drosophila cells, with a specific emphasis on the fluorescent markers and imaging setup used to capture the motion of repair foci over long-time periods. We detail approaches that minimize photobleaching and phototoxicity with a DeltaVision widefield deconvolution microscope, and image processing techniques for signal recovery postimaging using SoftWorX and Imaris software. We present a method to derive mean square displacement curves revealing some of the biophysical properties of the motion. Finally, we describe a method in R to identify tracts of directed motions (DMs) in mixed trajectories. These approaches enable a deeper understanding of the mechanisms of heterochromatin dynamics and genome stability in the three-dimensional context of the nucleus and have broad applicability in the field of nuclear dynamics.« less
  4. Free, publicly-accessible full text available November 1, 2022
  5. Free, publicly-accessible full text available November 1, 2022
  6. Free, publicly-accessible full text available November 1, 2022