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1.
Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product. 相似文献
2.
针对软件缺陷预测时缺陷数据集中存在的类别分布不平衡问题,结合上采样算法SMOTE与Edited Nearest Neighbor (ENN) 数据清洗策略,提出了一种基于启发式BP神经网络算法的软件缺陷预测模型。模型中采用上采样算法SMOTE增加少数类样本以改善项目中的数据不平衡状况,并针对采样后数据噪声问题进行ENN数据清洗,结合基于启发式学习的模拟退火算法改进四层BP神经网络后建立分类预测模型,在AEEEM数据库上使用交叉验证对提出的方案进行性能评估,结果表明所提出的算法能够有效提高模型在预测类不平衡数据时的分类准确度。 相似文献
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ContextEnterprise software systems (e.g., enterprise resource planning software) are often deployed in different contexts (e.g., different organizations or different business units or branches of one organization). However, even though organizations, business units or branches have the same or similar business goals, they may differ in how they achieve these goals. Thus, many enterprise software systems are subject to variability and adapted depending on the context in which they are used.ObjectiveOur goal is to provide a snapshot of variability in large scale enterprise software systems. We aim at understanding the types of variability that occur in large industrial enterprise software systems. Furthermore, we aim at identifying how variability is handled in such systems.MethodWe performed an exploratory case study in two large software organizations, involving two large enterprise software systems. Data were collected through interviews and document analysis. Data were analyzed following a grounded theory approach.ResultsWe identified seven types of variability (e.g., functionality, infrastructure) and eight mechanisms to handle variability (e.g., add-ons, code switches).ConclusionsWe provide generic types for classifying variability in enterprise software systems, and reusable mechanisms for handling such variability. Some variability types and handling mechanisms for enterprise software systems found in the real world extend existing concepts and theories. Others confirm findings from previous research literature on variability in software in general and are therefore not specific to enterprise software systems. Our findings also offer a theoretical foundation for describing variability handling in practice. Future work needs to provide more evaluations of the theoretical foundations, and refine variability handling mechanisms into more detailed practices. 相似文献
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性能效率是APP软件的重要质量属性,但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征,基于ISO/IEC 25010标准提出了APP软件的性能效率模型,定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型,通过实验对APP软件的性能效率进行了度量及相关分析。 相似文献
6.
Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach. 相似文献
7.
从硬件和软件两个角度出发,介绍基于DSP的多元数据同步采集与存储系统的组成、工作模式以及功能的测试。系统主要由上位机和数字采集与存储单元组成,其中数字采集与存储单元的硬件部分包括电源模块,值班电路模块,数据采集模块,数据存储模块,时钟同步模块。系统采用DSP作为中央处理芯片,利用经过同步后的秒脉冲作为触发信号,实现同步数据采集。以CF卡作为存储介质,实现数据自容式存储。软件部分实现自检、同步、数据采集存储功能。经过测试,系统工作稳定,功能正常,同步精度在100ns以内。 相似文献
8.
实时操作系统DSP/BIOS在DSP开发中的应用 总被引:2,自引:0,他引:2
本文介绍了RTOS(实时操作系统)DSP/BIOS在DSP的开发设计中的应用。在简述了DSP的一般模型后,论述了RTOS在DSP/BIOS外设管理,实时性能分析以及程序流程控制中的应用。 相似文献
9.
图形点阵式液晶显示器MSP-G320240在高速处理器DSP中的应用 总被引:1,自引:1,他引:0
介绍了内置SD1335控制器的图形液晶显示器MSP-G320240的工作原理及应用方法,给出了MSP-G320240液晶显示器同DSP的简单接口电路,同时给出了相应的液晶显示器的初始化和清显示区的具体程序。 相似文献
10.