大数据科学与工程专业设置探索

针对贵州大数据产业发展的实际需情况,分析大数据的关键技术及特点,结合贵州发展和打造大数据产业的三大机遇和五大优势,对贵州大学设置大数据科学与工程专业的优势进行了分析和展望,利用更好的培养大数据产业人才。     

大数据科学与工程专业设置探索

针对贵州大数据产业发展的实际需情况,分析大数据的关键技术及特点,结合贵州发展和打造大数据产业的三大机遇和五大优势,对贵州大学设置大数据科学与工程专业的优势进行了分析和展望,利用更好的培养大数据产业人才。     

大数据环境下的电子数据审计:机遇、挑战与方法

电子数据审计的研究与应用是近年来审计领域的热点问题。大数据时代的到来给电子数据审计带来了机遇与挑战。首先阐述了研究大数据环境下电子数据审计的重要性;然后分析了电子数据审计的内涵及原理;在此基础上,重点研究了大数据环境下电子数据审计面临的机遇与挑战,并结合大数据的特点以及目前已有的大数据分析技术与工具,探讨了大数据环境下开展电子数据审计的方法;最后给出了大数据环境下开展电子数据审计的相关建议。研究结果为今后大数据环境下开展电子数据审计提供了理论基础。     

工程教育专业认证背景下数据科学与大数据技术专业人才和课程培养体系研究

数据科学与大数据技术专业作为一门新兴专业,对我国信息技术发展及综合实力的提高有举足轻重的意义.文章首先指出数据科学与大数据技术专业在师资、科研、教学方面存在的主要问题,其次围绕"新工科","工程认证"等理念,从数据科学与大数据技术专业的人才培养模式以及课程教学模式创新两方面作出了实践,制定了数据科学与大数据技术专业的课程体系,给出了针对数据科学与大数据技术专业学生的能力培养矩阵方案.     

数据科学与工程特色的计算机科学与技术人才培养模式构建

针对数据人才培养的时代需求,以培养数据科学与工程特色的计算机科学与技术人才为目标,提出优化传统的计算机科学与技术专业课程体系,以特色研究型课程为抓手,建设"数据分析与挖掘课程群",具体阐述改革思路目标,并结合山西大学的学科平台建设说明实施办法。     

数据科学与大数据技术专业建设研究与实践

在调研国内外数据科学与大数据技术专业建设情况的基础上,提出培养具有行业特色和可持续竞争力的大数据卓越人才的建设目标,阐述如何构建贯通式能力培养的课程体系,构建校企融合协同育人体系,构建多层次一体化的实验环境,培养师资队伍以及构建教学质量持续改进体系,从而形成多层次、多类型、健全的卓越人才培养体系。     

国家科学数据中心联合专刊总序

在数字经济成为重塑全球经济结构、改变全球竞争格局的关键力量的当下,数据正在成为关键生产要素。大数据时代,科技创新越来越依赖于对科学数据的分析挖掘和综合利用,以海量科学数据分析应用为代表的数据密集型科研范式应运而生,成为支撑科技创新和推动国家进步的重要力量。党和国家始终高度重视科学数据建设发展。     

大数据背景下软件测试的挑战与展望

随着移动互联网、物联网、云计算的快速发展,大数据引发了新一轮技术发展的新浪潮,同时也给软件测试带来了新的挑战。分析在大数据背景下软件测试遇到的几个挑战,包括软件测试ORACLE问题、数据处理框架、测试平台性能等,并在分析软件杀虫剂效应的基础上给出了软件测试的初步展望。     

面向大数据的信息与计算科学专业实验课程体系研究

本文从大数据时代的背景出发,结合信息与计算科学专业的实际,从面向未来挑战、丰富实验课程内容、培养应用型人才等方面,阐述了专业实验课程建设的思路和对策。     

Data-Intensive Cloud Computing: Requirements, Expectations, Challenges, and Solutions

Data-intensive systems encompass terabytes to petabytes of data. Such systems require massive storage and intensive computational power in order to execute complex queries and generate timely results. Further, the rate at which this data is being generated induces extensive challenges of data storage, linking, and processing. A data-intensive cloud provides an abstraction of high availability, usability, and efficiency to users. However, underlying this abstraction, there are stringent requirements and challenges to facilitate scalable and resourceful services through effective physical infrastructure, smart networking solutions, intelligent software tools, and useful software approaches. This paper analyzes the extensive requirements which exist in data-intensive clouds, describes various challenges related to the paradigm, and assess numerous solutions in meeting these requirements and challenges. It provides a detailed study of the solutions and analyzes their capabilities in meeting emerging needs of widespread applications.     

Overcoming Requirements Engineering Challenges: Lessons from Offshore Outsourcing

Requirements engineering practices have changed significantly to address the needs of global software development characterized by teams working across geographies, time zones, and organizational boundaries. By sharing real-life case studies based on experience of an Indian IT services outsourcing firm, the authors provide insights into the root causes of RE phase conflicts within client-vendor offshore relationships. On the basis of this analysis, they propose a set of strategic success factors that potentially address a variety of RE challenges in the multiparty global software development context. They also propose a holistic framework of best practices across people-process-technology dimensions to achieve the success factors. This article is part of a special issue on Global Software Development.     

Crowdsourced Requirements Engineering Challenges and Solutions: A Software Industry Perspective

Software crowdsourcing (SW CS) is an evolving software development paradigm, in which crowds of people are asked to solve various problems through an open call (with the encouragement of prizes for the top solutions). Because of its dynamic nature, SW CS has been progressively accepted and adopted in the software industry. However, issues pertinent to the understanding of requirements among crowds of people and requirements engineers are yet to be clarified and explained. If the requirements are not clear to the development team, it has a significant effect on the quality of the software product. This study aims to identify the potential challenges faced by requirements engineers when conducting the SW–CS based requirements engineering (RE) process. Moreover, solutions to overcome these challenges are also identified. Qualitative data analysis is performed on the interview data collected from software industry professionals. Consequently, 20 SW–CS based RE challenges and their subsequent proposed solutions are devised, which are further grouped under seven categories. This study is beneficial for academicians, researchers and practitioners by providing detailed SW–CS based RE challenges and subsequent solutions that could eventually guide them to understand and effectively implement RE in SW CS.     

Science in the Cloud: Allocation and Execution of Data-Intensive Scientific Workflows

An important challenge for the adoption of cloud computing in the scientific community remains the efficient allocation and execution of data-intensive scientific workflows to reduce execution time and the size of transferred data. The transferred data overhead is becoming significant with emerging scientific workflows that have input/output files and intermediate data products ranging in the hundreds of gigabytes. The allocation of scientific workflows on public clouds can be described through a variety of perspectives and parameters, and has been proved to be NP-complete. This paper proposes an evolutionary approach for task allocation on public clouds considering data transfer and execution time. In our framework, a solution is represented using an allocation chromosome that encodes the allocation of tasks to nodes, and an ordering chromosome that defines the execution order according to the scientific workflow representation. We propose a multi-objective optimization that relies on a cloud cost model and employs tailored evolution operators. Starting from a population of possible solutions, we employ crossover and mutation operators on both chromosomes aiming at optimizing the data transferred between nodes as well as the total workflow runtime. The crossover operators combine parts of solutions to reduce data overhead, whereas the mutation operators swamp between parts of the same chromosome according to pre-defined rules. Our experimental study compares between the proposed approach and current state-of-the art approaches using synthetic and real-life workflows. Our algorithm performs similarly to existing heuristics for small workflows and shows up to 80 % improvements for larger synthetic workflows. To further validate our approach we compare between the allocation and scheduling obtained by our approach with that obtained by popular scientific workflow managers, when real workflows with hundreds of tasks are executed on a public cloud. The results show a 10 % improvement in runtime over existing schedulers, caused by a 80 % reduction in transferred data and optimized allocation and ordering of tasks. This improved data locality has greater impact as it can be employed to improve and study data provenance and facilitate data persistence for scientific workflows.     

Software and House Requirements Engineering: Lessons Learned in Combating Requirements Creep

Anyone who has built or remodelled a house and has developed or enhanced software must have noticed the similarity of these activities. This paper examines these two processes from the points of view of budgeting, scheduling, and requirements creep. It is admitted from the start that some of the argument and conclusions are based on popular perceptions and personal observation over small populations, that is, the houses the author and some close friends have remodelled and built and software projects in which the author has participated as an analyst, designer, programmer, or consultant.     

面向Agent的软件工程:现状与挑战

面向Agent软件工程是近年来软件工程领域出现的一个重要的前沿研究方向,它试图将Agent理论和技术与软件工程的思想、原理和原则相结合,从而为基于Agent系统的开发提供工程化手段．近年来,随着Internet上的web应用以及软件开发社会化的发展,面向Agent软件工程受到了学术界和工业界的高度关注和重视,研究活跃,发展迅速．从应用需求和技术发展两个方面阐述了面向Agent软件工程的产生和发展背景;从技术、管理和工具3个视点综述了现阶段面向Agent软件工程的研究内容;分析了面向Agent软件工程的研究现状;最后讨论了它存在的问题和面临的挑战以指导进一步研究．