基于機(jī)會(huì)發(fā)現(xiàn)的軟件項(xiàng)目風(fēng)險(xiǎn)識(shí)別研究.pdf

1、Nearly half a million project managers execute about a millionsoftware projects every year all around the world, turning out softwareworth more than $600 billion. A considerable part of the softwareprojects, as one of th

2、e studies, Standish Group report shows nearlythree - quarter of over all as challenged or cancelled, goes in vain dueto unhandled damaging project risks associated with them. Most of them are unidentified until too

3、 late to manage them and theresults of these project have been nothing but desperate cancellation.Henceforth, it goes without saying the need of risk identification whichis a core process of risk management, the most cru

4、cial management inany project management. Software risk is a measure of the chance and loss of an unacceptableresult disturbing the software project, software process, or softwareproduct. Each software system

5、 is distinctive with its own particular set ofrisks. There are many software risks but fewer consequences that wecare to avoid. Mostly, it is hard to avoid all kinds of risks in a project.This is why we often care about

6、a few highly impacting risks likepotential cost, schedule, technical consequences in any project. Thesesoftware risks could avert a software project from meeting its cost,schedule, and technical objectives. Software risk

7、 is hazardous becauseit can prevent software project success. Software risk identification is the initial process in the riskassessment which is a part of risk management. Without proper riskidentification, it is t

8、ough to control and manage the risk that isassociated with the software project.So far, a number of research papers are contributed to this effortand a vast majority of techniques have been applied for the concernedprobl

9、em to solve the issue but still most of them are basically, dependon rigorous textual procedures to identify risks. The current work is an innovative attempt to solve the softwareproject risks identification proble

10、m with KeyGraph, a graphical tool ofchance discovery. This procedure, in turn, simplifies the software risksidentification and consolidates attempts to identify software risks morevivid and robust fashion. Further,

11、 the procedure enhances human ability and endeavour toidentify software risks by analytic capabilities. At the same time, it isimportant to bear in mind that the procedure consists an analyticalapproach that's what we ca

12、ll human initiative, the human process ofexternalizing the tacit experiences, rather than, an autonomous ormachine-dependent one. The software risk identification process begins with the creation ofsoftware project

13、 risk scenarios. These scenarios are at first, made bycollecting essential set of data or nodes as input to the formation ofKeyGraph. Further, co-occurrence network is created by links between thesefrequent co-occu

14、rring item-pairs or node-pairs of the data-set. Thefundamental islands are obtained by deleting links that separates thegraphs and deleting the links of highest contribution. This situation isregarded as generation of hu

15、bs, candidates of rare event or chance,indeed, risks which are significant items, touching many node-clusterbridges of frequent co-occurrence. A deliberate analysis is done beforethe nomination of these risks. Finally, t