In this paper, we propose the first verification method for attention robustness, i.e., the local robustness of the changes in the saliency-map against combinations of semantic perturbations. Specmcally, our method determines the range of the perturbation parameters (e.g., the amount of brightness change) that maintains the difference between the actual saliencymap change and the expected saliency-map change below a given threshold value. Our method is based on linear activation region traversals, focusing on the outermost boundary of attention robustness for scalability on larger deep neural networks.

We have improved an approach for listing API sequences using API specification documents to make combinatorial testing for remote services to which requests are sent using APIs such as REST, gRPC, and WSDL. The proposed approach performs a depth-first, backward, all-at-once search rather than a breadth-first, forward, one-by-one search which was the strategy of previous studies. Our proposed approach parses an API specification document and creates a directed tree that represents a partial order of calls of APIs to collect values demanded by each target API. The approach calculates the leading-following relations of APIs by manipulating a matrix that represents the relations of APIs and named values that mediate the relations. We applied our proposed approach to a practical service, GitLab. We obtained the result that the approach lists the longer executable API sequences that can visit more methods in service implementation than the approaches of existing work without listing a large number of sequences.

This paper proposes multi-query unification, a technique for generating unified components from a DFD aimed at reducing the total cost of data transmission between components that are deployed to a computing fabric that includes processing nodes and interconnection services. The method focuses on generating components of the two primary data processing methodologies: cumulative data processing (CDP) and data stream processing (DSP). The method utilizes multi-query unification and generates a unified query by applying two methods depending on the order sensitivity of processes in a DFD. Nesting unification composes a unified query by embedding the query of a process into the query of the next process as a subquery. Clause assembly unification composes a query using templates for each clause of the original query. For clause assembly is applicable only to processes that is executable simultaneously, we define the criteria called order sensitivity for applying clause assembly and propose two-stage unification in which nesting unification is always applied after clause assembly. The performance evaluation based on a virtual DFD shows that applying two-stage unification reduces the execution time of components by 60 percent in DSP, however, execution time is reduced by only 10 percent in CDP. On the other hand, nesting unification alone reduces the execution time by 30 percent. Based on those results, we conclude that clause assembly should be applied to DSP using Esper but should not be applied to CDP using Hive.

Network traffic keeps increasing like as the demand of video streaming. Routers and switches in wire-line networks require guaranteed line rate as high as 20Gbp/s as well as advanced quality of service (QoS). Hybrid SRAM and DRAM architecture previously presented with the benefit of high-speed and high-density requires complex memory management. As a result it, it has hardly supported large numbers of queue, which is an effective solution in QoS. This paper proposes an intelligent memory management unit (MMU) in the bases of hybrid architecture, wherever 16k multi queues are integrated. The performance examined by the system board is zero-packet loss under the seamless traffic with 60-1.5k Byte packet-length. (deterministic manner) Noticeable feature in this paper's architecture is eliminating any premium memories but uses only low-cost commodity SRAMs and DRAMs. The intelligent MMU involves head buffer architecture, which is suitable to support a large numbers of FIFO queues. The experimental board based on this architecture is embedded into a Router system to evaluate the performance. Using 16k queues at 20Gbps, zero-packet loss is examined with 64-Byte to 1, 500-Byte packet-length.

In these days, there are a lot of massive event data appeared every day because networked devices such as smartphones and kind of sensors become very common. Every service provider intends to analyze the event data and discovers a new business rule for real time event processing service. We proposed a methodology which integrates such kind of data analysis and service development using DFD (Data Flow Diagram) which is independent from implementations, and we developed its prototype for evaluations. The methodology and the tool separate the concern of a developer and an analyst, moreover, we succeeded to confirm that the prototype tool reduced actual analysis and service development costs dramatically.

Sharing know-how regarding business process modeling activities and best practices can save time in the early phases of business system development. To help developers share know-how and best practices, we have developed a methodology and a tool for business process modeling and have applied it to a system development project. Furthermore, we have developed process-template development techniques to realize granularity-unification of business processes so that business process models can be reused, and have clarified the practical divisions of process models and the design issues concerning each division. These techniques enable the preparation of reuse-oriented business process templates before the business process modeling activity. In this paper, we describe the methodology and tool, including a meta-model and notations we have constructed for business modeling. We then consider the effectiveness of the methodology and tool: in an actual development project, the tool and business process templates decreased development time by 46% or more.