Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

Modern video players employ complex algorithms to adapt the bitrate of the video that is shown to the user. Bitrate adaptation requires a tradeoff between reducing the probability that the video freezes and enhancing the quality of the video shown to the user. A bitrate that is too high leads to frequent video freezes (i.e., rebuffering), while a bitrate that is too low leads to poor video quality. Video providers segment the video into short chunks and encode each chunk at multiple bitrates. The video player adaptively chooses the bitrate of each chunk that is downloaded, possibly choosing different bitrates for successive chunks. While bitrate adaptation holds the key to a good quality of experience for the user, current video players use ad-hoc algorithms that are poorly understood. We formulate bitrate adaptation as a utility maximization problem and devise an online control algorithm called BOLA that uses Lyapunov optimization techniques to minimize rebuffering and maximize video quality. We prove that BOLA achieves a time-average utility that is within an additive term O(1/V) of the optimal value, for a control parameter V related to the video buffer size. Further, unlike prior work, our algorithm does not require any prediction of available network bandwidth. We empirically validate our algorithm in a simulated network environment using an extensive collection of network traces. We show that our algorithm achieves near-optimal utility and in many cases significantly higher utility than current state-of-the-art algorithms. Our work has immediate impact on real-world video players and BOLA is part of the reference player implementation for the evolving DASH standard for video transmission.

BOLA: Near-optimal bitrate adaptation for online videos

A Protocol Test Generation Procedure.

We apply a model checker to the problem of test generation using a new application of mutation analysis. We define syntactic operators, each of which produces a slight variation on a given model. The operators define a form of mutation analysis at the level of the model checker specification. A model checker generates countersamples which distinguish the variations from the original specification. The countersamples can easily be turned into complete test cases, that is, with inputs and expected results. We define two classes of operators: those that produce test cases from which a correct implementation must differ, and those that produce test cases with which it must agree. There are substantial advantages to combining a model checker with mutation analysis. First, test case generation is automatic; each countersample is a complete test case. Second, in sharp contrast to program-based mutation analysis, equivalent mutant identification is also automatic. We apply our method to an example specification and evaluate the resulting test sets with coverage metrics on a Java implementation.

Using Model Checking to Generate Tests from Specifications | NIST

As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep Neural Networks (DNNs) have quickly attracted widespread attention. However, it is challenging to run computation-intensive DNN-based tasks on mobile devices due to the limited computation resources. What’s worse, traditional cloud-assisted DNN inference is heavily hindered by the significant wide-area network latency, leading to poor real-time performance as well as low quality of user experience. To address these challenges, in this paper, we propose Edgent , a framework that leverages edge computing for DNN collaborative inference through device-edge synergy. Edgent exploits two design knobs: (1) DNN partitioning that adaptively partitions computation between device and edge for purpose of coordinating the powerful cloud resource and the proximal edge resource for real-time DNN inference; (2) DNN right-sizing that further reduces computing latency via early exiting inference at an appropriate intermediate DNN layer. In addition, considering the potential network fluctuation in real-world deployment, Edgent is properly design to specialize for both static and dynamic network environment. Specifically, in a static environment where the bandwidth changes slowly, Edgent derives the best configurations with the assist of regression-based prediction models, while in a dynamic environment where the bandwidth varies dramatically, Edgent generates the best execution plan through the online change point detection algorithm that maps the current bandwidth state to the optimal configuration. We implement Edgent prototype based on the Raspberry Pi and the desktop PC and the extensive experimental evaluations demonstrate Edgent ’s effectiveness in enabling on-demand low-latency edge intelligence.

Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing

Most content providers are interested in providing good video delivery QoE for all users, not just on average. State-of-the-art ABR algorithms like BOLA and MPC rely on parameters that are sensitive to network conditions, so may perform poorly for some users and/or videos. In this paper, we propose a technique called Oboe to auto-tune these parameters to different network conditions. Oboe pre-computes, for a given ABR algorithm, the best possible parameters for different network conditions, then dynamically adapts the parameters at run-time for the current network conditions. Using testbed experiments, we show that Oboe significantly improves BOLA, MPC, and a commercially deployed ABR. Oboe also betters a recently proposed reinforcement learning based ABR, Pensieve, by 24% on average on a composite QoE metric, in part because it is able to better specialize ABR behavior across different network states.

https://dl.acm.org/doi/pdf/10.1145/3230543.3230558

Oboe: auto-tuning video ABR algorithms to network conditions

Crawling deep web is the process of collecting data from search interfaces by issuing queries. With wide availability of programmable interface encoded in web services, deep web crawling has received a large variety of applications. One of the major challenges crawling deep web is the selection of the queries so that most of the data can be retrieved at a low cost. We propose a general method in this regard. In order to minimize the duplicates retrieved, we reduced the problem of selecting an optimal set of queries from a sample of the data source into the well-known set-covering problem and adopt a classical algorithm to resolve it. To verify that the queries selected from a sample also produce a good result for the entire data source, we carried out a set of experiments on large corpora including Wikipedia and Reuters. We show that our sampling-based method is effective by empirically proving that 1) The queries selected from samples can harvest most of the data in the original database; 2) The queries with low overlapping rate in samples will also result in a low overlapping rate in the original database; and 3) The size of the sample and the size of the terms from where to select the queries do not need to be very large.

/pdf/an-approach-to-deep-web-crawling-by-sampling-256otaf4lc.pdf

An Approach to Deep Web Crawling by Sampling

Under certain well–defined conditions, determining the correctness of a system under test (SUT) is based on a checking sequence generated from a finite state machine (FSM) specification of the SUT. When there is a distinguishing sequence for the FSM, an efficient checking sequence may be produced from the elements of a set Eα′ of α′-sequences that verify subsets of states and the elements of a set EC of subsequences that test the individual transitions. An optimization algorithm may be used in order to produce a shortest checking sequence by connecting the elements of Eα′ and EC using transitions drawn from an acyclic set. Previous work did not consider whether some transition tests may be omitted from EC. This paper investigates the problem of eliminating subsequences from EC for those transitions that correspond to the last transitions traversed when a distinguishing sequence is applied in an α′–sequence to obtain a further reduction in the length of a checking sequence.

/pdf/eliminating-redundant-tests-in-a-checking-sequence-2kocaa1rhv.pdf

Eliminating redundant tests in a checking sequence

The development of GUI-based applications has raised a lot of new issues, one of them being how to automate effective testing for applications with complicated graphical user interactions. In this paper, we discuss the architectural issues and the implementation concerns of our approach to an automated specification-based testing technique for GUI-based applications. This approach is carried out by enriching existing architecture for automated specification-based testing. An essential part of our work is a visual environment to obtain test specifications. This environment pre-runs the Application Under Test (AUT) under its own control, with two prominent characteristics: First, testers can edit test specifications within the true GUI environment of the AUT. Second, the recorded input and output contain the same references as those in the AUT, so that the test cases generated from the edited specification can be used directly by test oracles during the automated testing procedure.

We present our running prototype of a visual specification editor that allows users to graphically manipulate test specifications when these specifications are given in term of Finite State Machines (FSM) and the implementations of the AUT are GUI-based Java applications.

Specification-based Testing for Gui-based Applications

Controllability and observability problems may manifest themselves during the application of a test or checking sequence in a test architecture where there are multiple remote testers. These problems often require the use of external coordination message exchanges among testers during testing. It is desired to construct a test or checking sequence from the specification of the system under test such that it will be free from these problems without requiring the use of external coordination messages. This paper investigates conditions that allow us to construct such a test or checking sequence. For specifications satisfying these conditions, procedures for constructing subsequences that eliminate the need for using external coordination messages are given.

/pdf/conditions-for-resolving-observability-problems-in-40s0mzeid7.pdf

Jessica Chen

Papers

Oboe: auto-tuning video ABR algorithms to network conditions

An Approach to Deep Web Crawling by Sampling

Eliminating redundant tests in a checking sequence

Specification-based Testing for Gui-based Applications

Conditions for Resolving Observability Problems in Distributed Testing