Approaches to software process development that are based on the principles and practices of softwareengineering have been advocated by many researchers as a means to produce software processes that meet the needs of...
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ISBN:
(纸本)1601320884
Approaches to software process development that are based on the principles and practices of softwareengineering have been advocated by many researchers as a means to produce software processes that meet the needs of process users. Such approaches require methodical and repeatable verification and validation techniques that enable effective and efficient identification, analysis and correction of software process defects. Defect classification schemes have proven to be effective for characterizing and improving the quality of software products. It is reasonable, therefore, to suggest that a similar scheme for the classification of process defects may provide comparable support to those performing software process engineering activities. This paper proposes a defect typology that can be used to classify software process defects as definition, asset, context or documentation problems. The paper then discusses potential applications of the typology to software process verification and validation and concludes by suggesting areas for further research.
A capacity using covert channel mitigation method (CUCCMM) was proposed. This method uses capacity as metric for channel danger measure according to trusted computer system evaluation criteria (TCSEC) and multiple pro...
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A capacity using covert channel mitigation method (CUCCMM) was proposed. This method uses capacity as metric for channel danger measure according to trusted computer system evaluation criteria (TCSEC) and multiple probabilities based protocol selection policy (MPBPSP) to guide die application of secure concurrency control protocol. The algorithms of channel's capacity measure and policy's parameter computing are also presented. Experimental results show that CUCCMM implements the restriction criterion on channel's capacity effectively and accurately, and the MPBPSP significantly decreases the influence of restriction operation on real-time performance.
Two models have been built on 2 × 1 Si (001) surfaces whose structures are Si-OH and Si-O-Si oxygenic bridge. The system energies and surface structures are comparatively calculated by generalized gradient approx...
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Two models have been built on 2 × 1 Si (001) surfaces whose structures are Si-OH and Si-O-Si oxygenic bridge. The system energies and surface structures are comparatively calculated by generalized gradient approximation (GGA) and local density approximation (LDA), based on density functional theory (DFT) in k-point space with periodic boundary condition. After analysis of the calculation data in comparison with the experiment data, it is concluded that using GGA method is more suitable than LDA to calculate the surface structure of Si compound materials.
When streams rates exceed the system capacity, a data stream management system (DSMS) becomes overloaded and fails to satisfy all kinds of requirements, such as tuple latency and result precision. Especially, in a tim...
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When streams rates exceed the system capacity, a data stream management system (DSMS) becomes overloaded and fails to satisfy all kinds of requirements, such as tuple latency and result precision. Especially, in a time-critical environment, queries should be completed not just timely but within certain deadlines. Semantic load shedding is an effective approach to alleviate workloads. In order to improve the efficiency of load shedding over real-time data streams, we present a semantic and flexible load shedding algorithm based on priority table (SLS-PT) which considers about execution costs and tuples' values together when deciding which tuples are dropped.
This chapter presents our solution to the CoCoME assignment that is based on the SOFA 2.0 (software Appliances) hierarchical component model. The solution involves (i) modeling architecture in SOFA meta-model, (ii) sp...
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In this paper we deal with the problem of learning user preferences from userpsilas scoring of a small sample of objects with labels from a very small linearly ordered set. The main task of this process is to use thes...
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In this paper we deal with the problem of learning user preferences from userpsilas scoring of a small sample of objects with labels from a very small linearly ordered set. The main task of this process is to use these preferences for a top-k query, which delivers the user with an ordered list of k highest ranked objects. We deal with a problem of many ties in the highest score. Two algorithms for learning objective and utility functions are presented. We experiment and compare them to some classical data-mining methods. We use several measures (RMSE and rank correlations ...) to evaluate efficiency of these methods.
This chapter overviews the scope, goals and timeline of the modeling contest CoCoME. It also describes the input the competing teams received and, furthermore, explains how the peer reviewing process went ahead, and h...
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Load shedding is a challengeable issue in data stream management systems (DSMSs). When data stream rates exceed system capacity, the overloaded DSMS fails to process all of its input data and keep up with the rate of ...
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Load shedding is a challengeable issue in data stream management systems (DSMSs). When data stream rates exceed system capacity, the overloaded DSMS fails to process all of its input data and keep up with the rate of data arrival. Especially, in a time-critical environment, queries should be completed not just timely but within certain deadlines. Existing strategies are poor at handling huge fluctuant overload with deadline. In this paper, an Effective Deadline-Aware Random Load Shedding algorithm (named RLS-EDA) is proposed to handle real-time system overload effectively. The RLS-EDA algorithm can make full use of the system idle time by buffering dropped tuples which would have opportunities to be executed when the workload is fade. Experiment results show that our algorithm can reduce average deadline miss ratio and increase system throughput during the period of huge workload fluctuations.
This chapter presents our solution to the CoCoME assignment that is based on the Fractal component model. The solution involves (i) modeling architecture in Fractal ADL, (ii) specification of component behavior via be...
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