The Human Side of Agile Software Development
关于软件的英语作文加翻译
English Composition:In the modern era, software plays an integral role in our daily lives. It is the backbone of the digital world, powering everything from the simplest calculator applications to the most complex artificial intelligence systems. The development of software has revolutionized industries, improved communication, and enhanced our ability to solve problems.The process of creating software is known as software development. It involves several stages, including requirement analysis, design, implementation, testing, and maintenance. Each stage is crucial to ensure that the final product meets the users needs and is free from bugs and errors. Software developers must possess a deep understanding of programming languages and algorithms to write efficient and effective code.One of the most significant benefits of software is its flexibility. It can be easily updated and customized to meet changing requirements. This adaptability has allowed businesses to stay agile and responsive to market demands. Furthermore, software has democratized access to information and services, making it possible for individuals to perform tasks that were once reserved for specialized professionals.However, the proliferation of software also brings challenges. Cybersecurity is a growing concern as malicious software can compromise sensitive data and systems. Developers must prioritize security in their designs to protect users and their information. Additionally, the rapid pace of technological advancement means that software must be continuously updated to remain relevant and secure.In conclusion, software is an essential component of our digital infrastructure. It has the power to transform industries and improve our lives in countless ways. As we continue to rely on software, it is imperative that we invest in its development, security, and ongoing maintenance.Translation to Chinese:在现代时代，软件在我们的日常生活中扮演着不可或缺的角色。
Introduction of SE
is concerned with all aspects of software production. Software engineers should adopt a systematic and organised approach to their work and use appropriate tools and techniques depending on the problem to be solved, the development constraints and the resources available.
Generic - developed to be sold to a range of different
customers e.g. PC software such as Excel or Word. Bespoke (custom) - developed for a single customer according to their specification.
An Introduction to Software Engineering
Objectives
To introduce software engineering and to
explain its importance To set out the answers to key questions about software engineering
Topics covered
Introduction of software engineering FAQs about software engineering Trends in software engineering
(完整word版)软件工程MiddleTermExam-2015-11(带答案)
评阅教师得分“软件工程导论”课程半期考试题一、单项选择题（本大题共20小题，每小题2分，共40分)提示：在每小题列出的四个备选项中只有一个是符合题目要求的，请将其代码填写在下表中。
错选、多选或未选均无分。
1. Which design model elements are used to depict a model of informationrepresented from the user’s view？a. Architectural design elementsb. Component—level design elementsc. Data design elementsd. Interface design elementsAnswer：c (Section 8。
4.1)2. Which of the following are not areas of concern（考虑）in the design model?a. architectureb. datac. interfacesd. project scopeAnswer: d (Section 8.1)3. The importance of software design can be summarized in a single worda. accuracyb. complexityc. efficiencyd. qualityAnswer: d (Section 8。
1）4. Which of the following is not a characteristic common to all design methods？a. configuration managementb. functional component representationc. quality assessment guidelinesd. refinement heuristicsAnswer: a （Section 8.2.2）5. What types of abstraction are not used in software design？a. controlb. datac. environmentald. proceduralAnswer：c (Section 8。
八年级科技前沿英语阅读理解25题
八年级科技前沿英语阅读理解25题1<背景文章>Artificial intelligence (AI) has been making remarkable strides in the medical field in recent years. AI - powered systems are being increasingly utilized in various aspects of healthcare, bringing about significant improvements and new possibilities.One of the most prominent applications of AI in medicine is in disease diagnosis. AI algorithms can analyze vast amounts of medical data, such as patient symptoms, medical histories, and test results. For example, deep - learning algorithms can scan X - rays, CT scans, and MRIs to detect early signs of diseases like cancer, pneumonia, or heart diseases. These algorithms can often spot minute details that might be overlooked by human doctors, thus enabling earlier and more accurate diagnoses.In the realm of drug development, AI also plays a crucial role. It can accelerate the process by predicting how different molecules will interact with the human body. AI - based models can sift through thousands of potential drug candidates in a short time, identifying those with the highest probability of success. This not only saves time but also reduces the cost associated with traditional trial - and - error methods in drug research.Medical robots are another area where AI is making an impact.Surgical robots, for instance, can be guided by AI systems to perform complex surgeries with greater precision. These robots can filter out the natural tremors of a surgeon's hand, allowing for more delicate and accurate incisions. Additionally, there are robots designed to assist in patient care, such as those that can help patients with limited mobility to move around or perform simple tasks.However, the application of AI in medicine also faces some challenges. Issues like data privacy, algorithmic bias, and the need for regulatory approval are important considerations. But overall, the potential of AI to transform the medical field is vast and holds great promise for the future of healthcare.1. What is one of the main applications of AI in the medical field according to the article?A. Designing hospital buildings.B. Disease diagnosis.C. Training medical students.D. Managing hospital finances.答案：B。
炸掉你的人力资源部
《Fortune》January 15, 1996, p.105. (Thomas A. Stewart《哈佛商业评论》总编托马斯•斯图沃特)《炸掉你的人力资源部》意译Taking On the Last BureaucracyPeople Need People---But Do They Need Personnel? It's Time for Human Resources Departments to Put Up or Shut Up.Nestling warm and sleepy in your company, like the asp in Cleopatra's bosom, is a d epartment whose employees spend 80% of their time on routineadministrative tasks. Nea rly every function of this department can be performed more expertly for less by others. C hances are its leaders are unable todescribe their contribution to value added except in tr endy, unquantifiable, and wannabe terms--yet, like a serpent unaffected by its own veno m, thedepartment frequently dispenses to others advice on how to eliminate work that do es not add value. It is also an organization where the averageadvertised salary for profes sional staffers increased 30% last year.I am describing, of course, your human resources department, and have a modest pr oposal: Why not blow the sucker up?【在你的公司中存在着一个暖洋洋的、昏昏欲睡的，就像是科洛巴特拉〔古埃及艳后，用毒蛇自杀〕胸脯上的毒蛇一样的东西，这个东西就是你公司中的一个部门。
A survey study of critical success factors in agile software projects
A survey study of critical success factors in agile software projectsTsun Chow,Dac-Buu Cao*School of Business and Technology,Capella University,Minneapolis,MN 55402,USA Received 20February 2007;received in revised form 12August 2007;accepted 17August 2007Available online 26August 2007AbstractWhile software is so important for all facets of the modern world,software development itself is not a perfect process.Agile software engineering methods have recently emerged as a new and different way of developing software as compared to the traditional method-ologies.However,their success has mostly been anecdotal,and research in this subject is still scant in the academic circles.This research study was a survey study on the critical success factors of Agile software development projects using quantitative approach.Based on existing literature,a preliminary list of potential critical success factors of Agile projects were identified and compiled.Sub-sequently,reliability analysis and factor analysis were conducted to consolidate this preliminary list into a final set of 12possible critical success factors for each of the four project success categories –Quality,Scope,Time,and Cost.A survey was conducted among Agile professionals,gathering survey data from 109Agile projects from 25countries across the world.Multiple regression techniques were used,both at the full regression model and at the optimized regression model via the stepwise screen-ing procedure.The results revealed that only 10out of 48hypotheses were supported,identifying three critical success factors for Agile software development projects:(a)Delivery Strategy,(b)Agile Software Engineering Techniques,and (c)Team Capability.Limitations of the study are discussed together with interpretations for practitioners.To ensure success of their projects,managers are urged to focus on choosing a high-caliber team,practicing Agile engineering techniques and following Agile-style delivery strategy.Ó2007Elsevier Inc.All rights reserved.Keywords:Software development;Agile methods;Critical success factors1.IntroductionWhile software is so important for the all facets of the modern world,software development itself is not a perfect process.Despite the efforts to employ software engineering methodologies,software development has not been consis-tently successful,thus often resulting in delayed,failed,abandoned,rejected software projects.Even those software projects already implemented may need expensive on-going maintenance and corrective releases or service packs.The above shortcomings have affected the bottom line for information technology (IT)and software development organizations in a big way.The challenge here is how soft-ware development management can be improved to avoid the above problems of waste and inefficiency?There hasbeen a recent emergence of a new class of software develop-ment process called Agile methods,which operate rather differently from traditional methods.The present research seeks to identify and provide insight into the critical success factors (CSF’s)that help software development projects using agile methods to suc-ceed.The study compiled the success factors reported in the agile literature,performed reliability analysis and factor analysis on those factors and consolidated them into a final 12possible success factors for Agile projects in five differ-ent categories:Organizational,People,Process,Technical,and Project.A web-based survey was conducted to gather feedback from 109agile software projects from 25coun-tries around the world,and the collected data were ana-lyzed using the multiple regression method.The analysis addresses the following questions:(a)Are these 12factors truly the critical success factors of Agile software develop-ment projects?;(b)If so,what is the relative importance of0164-1212/$-see front matter Ó2007Elsevier Inc.All rights reserved.doi:10.1016/j.jss.2007.08.020*Corresponding author.Tel.:+17149525590.E-mail address:dac-buu.cao@ (D.-B.Cao)./locate/jssAvailable online at The Journal of Systems and Software 81(2008)961–971each factor when compared to other factors?;and(c)Is there a difference among thosefive factor categories in terms of their impact on the success of an Agile software development project?2.BackgroundThis section reviews briefly two key concepts,Agile method and Critical Success Factor(CSF).It is followed by a discussion of failure and success research on Agile projects.Finally,the research model is presented covering the research hypotheses.2.1.Agile methodsThe word‘‘agile’’by itself means that something isflex-ible and responsive,so agile methods implies its‘‘[ability] to survive in an atmosphere of constant change and emerge with success’’(Anderson,2004,p.xxviii).This‘‘maneuver-ability’’in software business is a characteristic that is more important than ever these days since‘‘deploying software to the Web has intensified software competition further than before’’and‘‘staying in business involves not only getting software out and reducing defects but tracking con-tinually moving user and marketplace demands’’(Cock-burn,2002,p.xxii).The official definition of Agile Software Development was contained in a form of‘‘mani-festo’’in February2001by a group of17noted software process methodologists,who attended a summit meeting to advocate for a better way of developing software and then formed the Agile Alliance.The‘‘Manifesto for Agile Software Development’’posted on the Agile Alliance web-site(<>)reads as follows: We are uncovering better ways of developing software by doing it and helping others do it.Through this work we have come to value:Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiationResponding to change over following a planThat is,while there is value in the items on the right,we value the items on the left more.There are many software development methods that can be called‘‘agile’’,and the list varies depending on different viewpoints,but in general the list in the literature includes Extreme Programming(XP),Scrum,Feature-Driven Development(FDD),Dynamic System Development Method(DSDM),Adaptive Software Development (ASD),Crystal,and Lean Software Development(LD).2.2.The critical success factor approachThe Critical Success Factor(CSF)approach to identify-ing and measuring an organization’s performance wasfirst developed by Rockhart(1979)and later on refined and became well-established(Bullen and Rockhart,1981; Rockhart and Crescenzi,1984).CSF is defined by Bullen and Rockhart(1981)as‘‘the limited number of areas in which satisfactory results will ensure successful competitive performance for the individual,department,or organiza-tion.CSF’s are the few key areas where‘things must go right’for the business toflourish and for the managers goal to be attained’’(p.385).As for software development project area,the CSF method has also been considered in recent studies.CSF’s in software projects are found to relate to fundamental pro-ject management techniques(Reel,1999),or to relate to the combination of software engineering and business strategy (Bytheway,1999).Another case studyfinds that CSF’s in software projects consists of various dimensions,from the development life cycle and estimation and validation to executive management,project management,and resource-and strategic-level planning(Bosghossian,2002).In the context of the present study,the CSF’s can be defined as the factors that must be present for the Agile project to be successful.2.3.Success factors in agile software development projectsThere has not been any formal study on CSF’s in the Agile software development project per se,based on recent searches in peer reviewed academic literature or practi-tioner literature related to this topic.However,there are case studies and research theories on successes or fail-ures/problems in agile implementation and agile software development projects.The review of both failures and suc-cesses in the literature will be beneficial in identifying the possible success factors in agile software development pro-jects,as failures can contribute to the understanding of how to avoid certain serious pitfalls that are critical to the success of a project.2.3.1.Failure researchFailure or Problem research is typically based on‘‘les-sons learned’’from certain types of projects,but they are mostly similar enough to be generalized.Reel(1999) focuses more on generic software development projects and compiles10signs of software development project fail-ure,at least seven of which are determined even before a design is developed or a line of code is written.Cohn and Ford(2003)study problems in transitioning organizations to agile processes,while Larman(2004)discusses in detail mistakes and misunderstandings occurred in agile projects.A research by Boehm and Turner(2005)emphasizes on management challenges in implementing agile projects, whereas a study by Nerur et al.(2005)covers problems not only in management aspect but also in people,process, and technology dimensions of migrating to agile projects.Based on the above-mentioned literature,failures/ problems can be classified into four categories:organiza-tional,people,process,and technical,summarized in Table1.962T.Chow,D.-B.Cao/The Journal of Systems and Software81(2008)961–9712.3.2.Success researchSuccess research cited in the literature is mostly based on case studies or meta-data or compilations and observations of agile projects and practices.Specifically,Highsmith (2002)reports from direct experience with agile implemen-tations,while Schatz and Abdelshafi(2005)provide results from the Primavera case study,and Karlstrom and Rune-son(2005)give insight from the Star-Gate case study.Other success researches which have a comparativeflavor between traditional and agile methods include Boehm and Turner (2003),Augustine et al.(2005),and Ceschi et al.(2005). Some studies focus on agile implementation on large orga-nizations or scaling of agile methods to large projects,such as Reifer et al.(2003),Lindvall et al.(2004),and Ambler (2006).Finally,Koch(2005)makes research compilation of a wide range of success factors of agile implementations.Based on the above-mentioned literature,agile project success factors can be classified intofive categories:organi-zational,people,process,technical,and project,summa-rized in Table2.2.3.3.Success attributesIn terms of attributes of success,which depict the overall perception of success of a particular project,Cohn and Ford(2003)and Lindvall et al.(2004)suggest Quality (i.e.delivering a good working product),Scope(meeting all requirements by the customer),Timeliness(delivering on time),and Cost(within estimated cost and effort).These attributes can be summarized in Table3below.2.3.4.Factor consolidationFrom the two lists of possible factors(Tables1and2) which may affect the success or failure of an agile software development project,a number of factors that share similar characteristics were consolidated into a reduced list of fac-tors which cover39attributes.Table1Failure FactorsDimension FactorOrganizational ck of executive sponsorshipck of management commitmentanizational culture too traditionalanizational culture too politicalanizational size too largeck of agile logistical arrangementsck of necessary skill-setck of project management competenceck of team work10.Resistance from groups or individuals11.Bad customer relationshipProcess12.Ill-defined project scope13.Ill-defined project requirements14.Ill-defined project planningck of agile progress tracking mechanismck of customer presence17.Ill-defined customer roleck of complete set of correct agile practices19.Inappropriateness of technology and tools Table2Success FactorsDimension FactorOrganizational 1.Strong executive supportmitted sponsor or manager3.Cooperative organizational culture instead ofhierarchal4.Oral culture placing high value on face-to-facecommunicationanizations where agile methodology is universallyaccepted6.Collocation of the whole team7.Facility with proper agile-style work environment8.Reward system appropriate for agilePeople9.Team members with high competence and expertise10.Team members with great motivation11.Managers knowledgeable in agile process12.Managers who have light-touch or adaptivemanagement style13.Coherent,self-organizing teamwork14.Good customer relationshipProcess15.Following agile-oriented requirement managementprocess16.Following agile-oriented project managementprocess17.Following agile-oriented configuration managementprocess18.Strong communication focus with daily face-to-facemeetings19.Honoring regular working schedule–no overtime20.Strong customer commitment and presence21.Customer having full authorityTechnical22.Well-defined coding standards up front23.Pursuing simple design24.Rigorous refactoring activities25.Right amount of documentation26.Regular delivery of software27.Delivering most important featuresfirst28.Correct integration testing29.Appropriate technical training to teamProject30.Project nature being non-life-critical31.Project type being of variable scope with emergentrequirement32.Projects with dynamic,accelerated schedule33.Projects with small team34.Projects with no multiple independent teams35.Projects with up-front cost evaluation done36.Projects with up-front risk analysis doneTable3Success attributesDimension AttributeOverall perceived level ofsuccess1.Quality(delivering good product orproject outcome)2.Scope(meeting all requirements andobjectives)3.Time(delivering on time)4.Cost(delivering within estimated cost andeffort)T.Chow,D.-B.Cao/The Journal of Systems and Software81(2008)961–971963Since this research is of exploratory nature,a reliability analysis is necessary so that each and every factor is ensured of a high level of ing reliability anal-ysis,the researcher can determine the extent to which the items in each factor are related to each other.This can pro-vide an overall index of internal consistency of the vari-ables,and also can help single out problematic items that should be excluded from the variable and/or included in another variable.According to Rubin and Babbie(1997),‘‘the most common and powerful method used today for calculating internal consistency reliability is coefficient alpha.’’Cronbach a is a coefficient alpha which is a direct function of both the number of items and their magnitude of inter-correlation,and is the lower bound to the test var-iance attributable to common factors among the items within each variable(Cronbach,1951).For exploratory studies,it is agreed that a coefficient alpha level of0.5could be deemed acceptable(Nunally,1967).A reliability analysis was performed on all multi-item factors using the Cronbach’s alpha method.After two rounds of reliability analysis,the number of factors that had Cronbach’s alpha value below the acceptable level was reduced from5to1.One way to see if this factor could be reduced any fur-ther is to perform factor analysis on it(Williams and Monge,2001).A principal component factor analysis with Varimax rotation was performed on this factor.Thefinal results revealed12factors were identified, which were translated into12main hypotheses,each link-ing its existence as a critical success factor to the success of the Agile software development project in terms of four success dimensions:Quality,Scope,Time,and Cost.964T.Chow,D.-B.Cao/The Journal of Systems and Software81(2008)961–971The success factors used in the hypotheses included:(a) Strong management commitment,(b)Agile-friendly orga-nizational environment,(c)Agile-friendly project team environment,(d)High-caliber team capability,(e)Strong customer involvement,(f)Agile-style project management process,(g)Methodical project definition process,(h) Agile-style software engineering techniques,(i)Correct delivery strategy,(j)Non-life-critical project nature,(k) Variable-scope project type,and(l)Dynamic,accelerated project schedule.The hypotheses were numbered1to12,and since there were four success dimensions for each factor,the corre-sponding success dimensions were identified by the letters a,b,c,d.As a result,there were a total of48hypotheses, starting at1a and ending at12d(see Appendix A).Thefinal list of12factors is depicted by the research model in Fig.1.3.Data collectionThis study employed the web survey method to gather data.The target population was members of the Agile Alli-ance and its user groups.A web survey with Likert scale questionnaires and demographic information collection was distributed to the target population.There were four sections in the survey.Thefirst section was on demographic data,which included both the respondent’s demographic information as well as the agile project information.The second section was on success factors.To measure impor-tance of success factors,a7-point Likert scale was used to reflect the level of perception of the question by the respon-dent.The third section was on perception of success,and again,to measure perception of success of agile projects,a 7-point Likert scale was used to reflect the level of percep-tion of the question by the respondent.In order to avoid ambiguity in terms of perception of success on the part of the respondent,the questions focused on one particular project of the respondent’s choice in case he/she had been involved in multiple agile projects.The last section was for additional comments,where respondents were invited to enter any feedback or thoughts on a free-form text area, which might be used for follow-up for clarification if necessary.As part of the pilot process to test content validity and readability,five members of the Agile Alliance supplied feedback on improving the survey.The feedback was incor-porated into the survey before the survey invitation was emailed to the group coordinators of all83Agile Alliance user groups(42in the Americas,28in Europe,12in Asia/ Pacific,and one in Africa),as well as to the contact persons of all60corporate members of the Agile Alliance(29from the Americas,30from Europe,and one from Asia/Pacific).In all,after a six-week survey period,a total of408peo-ple responded by accessing the online survey and109pro-jects were submitted with complete data.Table4displays the breakdown of agile methods used in the109projects submitted,while Tables5–7display the size,length,and location of the projects,respectively.4.Data analysis and results4.1.Multiple regression modelsSince this research is an exploratory study tofind out which factors can positively impact the success of an agile project,it is appropriate for a multiple regression analysis, where the relationship between multiple independent vari-ables(success factors)and the dependent variable(agile project success)is determined,and where the relative pre-dictive importance of the independent variables is estab-lished(Williams and Monge,2001).Table4Project profile–Agile methods usedMethod Frequency Percent Extreme programming5853.2 Scrum2321.1 Other2119.3 Feature driven development5 4.6 Crystal2 1.8 Total109100.0Table5Project profile–Number of team membersTeam members Frequency Percent Less than106458.7 10–192321.1 20–291110.1 30–393 2.8 40–492 1.8 50–1006 5.5 Total109100.0Table6Project profile–Length of project in monthsMonths Frequency Percent 1–387.3 4–62321.1 7–91311.9 10–121715.6 13–241513.8 Over243330.3 Total109100.0Table7Project profile–Project location(zone)Location Frequency Percent Europe6156.0 America3633.0 Asia/Pacific109.2 Africa2 1.8 Total109100.0T.Chow,D.-B.Cao/The Journal of Systems and Software81(2008)961–971965According to McClave and Benson(1988),the general multiple regression model,assuming that there are k inde-pendent variables,can be written as follows:y¼bþb1x1þb2x2þ...:þb k x kþewhere y is the dependent variable and x1,x2,...,x k are the independent variables,and b i is the regression coefficient, and e is the random error component.The value of the coefficient b i determines the contribution of the indepen-dent variable x i,given that the other x variables are held constant and b0is the y-intercept.In the case of this study,the above translates to the fol-lowing general equation:YðQ;S;T;CÞ¼b1SF1þb2SF2þb3SF3þb4SF4þ...þb12SF12where Y is Agile Project Success dependent variable,Q is the Quality dimension,S is the Scope dimension,T is the Time dimension,C is the Cost dimension,B i is the Partial regression coefficient for the i th Success Factor(SF).The multiple regression analysis was done on both levels –the full model and the optimized model.First,at the full model level,all12independent variables were entered into a regression model at the same time,with the expectation that the calculation of the coefficients would take into account the interaction of all other variables being present. In this case,the relative importance of each and every inde-pendent variable would be accounted for,and those vari-ables that got top scores would be considered to be a critical success factor.Second,at the optimized model level,a stepwise regression screening procedure was carried out in order to come up with as few variables as possible while still predicting well the results of Agile projects.In this case,those variables that made it to the model would be considered to be a critical success factor,as they alone could account for the outcome of the dependent variables.At each level described above,the multiple correlation coefficient(R)and the coefficient of determination(R2)of the model were calculated,and for each independent vari-able,the coefficients B and b as well as the t-value were computed.Additionally,the significance level of each inde-pendent variable and the distribution normality of the dependent variable were checked.Those variables with top coefficient values that reached certain thresholds(i.e. significance level p60.10for the full model and p60.06 for the optimized model)would be recognized as candi-dates for being critical success factors.Finally,the list of candidates from the two model approaches were compared and analyzed for inclusion in the list of critical success factors.4.2.Summary of hypothesis testing resultsFrom the above analyses,wefinally arrived at the list of the most significant independent variables as shown in Table8.The results show that for Time and Cost,both model approaches arrived at the same conclusions,namely in each case,Team Capability and Delivery Strategy were selected as the most significant factors.For Scope,factors Agile Software Engineering Techniques and Delivery Strategy showed up in both approaches,but the stepwise optimized model approach yielded another factor,namely Customer Involvement.Finally,for Quality,each approach yielded one similar factor,which was Agile Software Engineering Techniques,while the second factor was different for each: Team Environment in the Full model case and Project Management Process in the Optimized model case.With the above observations,the results of the hypoth-esis testing can befinalized as follows:out of48research hypotheses,a total of10hypotheses were supported,while the remaining38hypotheses were rejected.Those hypoth-eses were rejected due to their low coefficient values and high probability level for their corresponding null hypoth-eses,meaning the presence of those factors did not make a significant difference to the value of the success dimensions.Table9summarizes the results of the hypothesis testing. The10supported hypotheses are labeled with a check mark (U).Those without the check mark are rejected hypotheses.Table8Summary of outcome from the two modeling approachesQuality Scope Time CostSelected variable bvalue Selected variable bvalueSelectedvariablebvalueSelectedvariablebvalueFull model Agile SW engineeringtechniques 0.39Agile SW engineeringtechniques0.24Teamcapability0.30Deliverystrategy0.37Team environment0.20Delivery strategy0.19Deliverystrategy 0.24Teamcapability0.23Optimizedmodel Agile SW engineeringtechniques0.46Agile SW engineeringtechniques0.27Teamcapability0.32Deliverystrategy0.36 Project management process0.24Delivery strategy0.20Deliverystrategy0.31Teamcapability0.17Customer involvement0.20966T.Chow,D.-B.Cao/The Journal of Systems and Software81(2008)961–9714.3.Answers to research questionsBased on the outcome of the regression analysis and the hypothesis testing results above,we now are in a position to answer the research questions posed at the beginning of the study.Although the success level was calculated for each of the four success attributes as opposed to the overall project success level,with each attribute carrying a distinct aspect to the perception of success,we can use the frequency of supported hypotheses to generalize the overall perception of success.Each of the research ques-tions is answered in each sub-section below.4.3.1.Research question1Thefirst research question was,‘‘Are these12factors truly the critical success factors of Agile software develop-ment projects?’’From thefindings discussed above,the answer is clearly No.Indeed,out of those12factors,only half of them were represented in the list of supported hypotheses.The factors that were candidates to be consid-ered as critical success factors were:1.Team Environment(in terms of Quality).2.Team Capability(in terms of Timeliness and Cost).3.Customer Involvement(in terms of Scope).4.Project Management Process(in terms of Quality).5.Agile Software Engineering Techniques(in terms ofQuality and Scope).6.Delivery Strategy(in terms of Scope,Timeliness,andCost).4.3.2.Research question2The second research question was,‘‘What is the relative importance of each factor when compared to other fac-tors?’’Based on the hypothesis testing result,we can see that Delivery Strategy had the most hypotheses supported (three),followed by Agile Software Engineering Tech-niques and Team Capability(two each),andfinally fol-lowed by Team Environment,Customer Involvement, and Project Management Process(one each).However, between Agile Software Engineering Techniques and Team Capability,the former was more important than the latter on the account of its higher Beta value.Likewise,among the last three factors,Project Management Process was more important than Team Environment and Customer Involvement by virtue of its higher Beta value.Table10 provides the details below(for a list of attributes of these 6success factors,please see Appendix B).4.3.3.Research question3The third research question was,‘‘Is there a difference among thosefive factor categories in terms of their impact on the success of an Agile software development project?’’Again,based on the regression analysis and the hypothesis testing results,it was found that there was a marked differ-ence among thosefive factor categories,namely Organiza-tional,People,Process,Technical,and Project.It was evident the Technical dimension,which included Agile Software Engineering Techniques and Delivery Strategy, was the most critical in impacting the success of Agile pro-jects,as it covered all four success dimensions.It was fol-lowed by the People dimension,which included Team Capability and Customer Involvement,as this dimension covered three success dimensions.The Organizational dimension and the Process dimension each touched one success dimension(Quality,in both cases).The only dimen-sion which failed to make any impact at all was the Project dimension.Table9Summary of hypothesis testing resultsQuality Scope Timeliness Cost1.Management commitment H1a H1b H1c H1danizational environment H2a H2b H2c H2d3.Team environment H3a U H3b H3c H3d4.Team capability H4a H4b H4c U H4d U5.Customer involvement H5a H5b U H5c H5d6.Project management process H6a U H6b H6c H6d7.Project definition process H7a H7b H7c H7d8.Agile software engineeringtechniquesH8a U H8b U H8c H8d9.Delivery strategy H9a H9b U H9c U H9d U10.Project nature H10a H10b H10c H10d11.Project type H11a H11b H11c H11d12.Project schedule H12a H12b H12c H12dTable10Ranking of critical success factorsRank Factor Hypotheses supported Selection in the full model Selection in the optimized modelFrequency b value Frequency b value1Delivery strategy H9b,H9c,H9d30.3730.360.240.310.190.202Agile software engineering techniques H8a,H8b20.3920.460.240.273Team capability H4c,H4d20.3020.320.230.174Project management process H6a0–10.245Team environment H3a10.200–6Customer involvement H5b0–10.20T.Chow,D.-B.Cao/The Journal of Systems and Software81(2008)961–971967。
Polarion ALM软件商品说明说明书
SummaryIn legacy software development environments, different point solutions are often used to manage application lifecycles. As a result, disparate silos of devel-opment information can adversely affect collaboration, transparency, data integrity and your company’s ability to drive innovation.Polarion ALM software can help you consolidate your real-time management information and drive project transparency. By using Polarion ALM, you can synchronize information exchange and testing while giving your development teams the ability to more quickly and accurately respond to new business oppor-tunities and customer demands.Unifying dataPolarion ALM allows you to unify data on a secure platform that uses the latest web technologies. You can deploy the software on a physical and/or virtual single server or cluster of servers. The software allows you to start small with the option to easily and affordably scale the solution to meet your needs.Benefits• Enhances collaboration for greater transparency• Supports traceability and versioning requirements for regulatory compliance • Helps significantly cut cost of ownership • Reduces risks through audits and quality monitoring• Leverages open APIs for custom extensions• Reduces overall costs and increases qualityDIGITAL INDUSTRIES SOFTWAREPolarion ALM unified solutionUnifying application lifecycle management functions to enhance collaboration, transparency and traceability/polarionManaging requirementsRequirements management includes documenting, analyzing, tracing and prioritizing requirements with a process to control and communicate changes to your stakeholders. By using Polarion ALM, your document-oriented domain experts and project team members can collaborate using familiar Microsoft® Word and Excel® spreadsheet software to create and edit requirements. After importing the information into Polarion ALM, you can use Polarion LiveDoc™Features• Unified data repository• Browser-based with 24/7 portal or cloud-based network access• Extensive requirements management options• Extensive support for various workflow methodologies• Built-in ReqIF functionality and online authoring/editing• Supports test management for quality assuranceComplete availability ALM-enhancing functionality Upgrade optionALMOnline authoring with LiveDocs™.Round-trip for Word and/or Excel to collaborate with participants who use those formats. The software also includes built-in Requirements Interchange Format™ (ReqIF) functionality that allows you to provide lossless require-ments exchange with your customers and suppliers.Testing for quality assuranceQuality assurance includes the process of testing for preventing errors and faults. By using Polarion ALM, you can create quality assurance test cases and map them back to your requirements. After establishing the test cases, you can plan manual and automated test runs, using third-party test automation tools as needed, and report the results to your project members. Quality assurance and testing processes can help you reduce costs and improve overall quality.Addressing risk managementPolarion ALM software includes built-in project templates with capabilities that help you manage potential risks following the standard failure modes and effects analysis (FMEA) approach. The software also gives you the flexibility to create and adapt custom work-flows to meet your specific needs.Customizing project planningWith Polarion ALM, you have access to a number of preconfigured and fully customiz-able project templates including options for project and iteration scheduling. The software helps you provide automatic project updates, showing potential delays and workload scenar-ios in real time.Implementing workflow-driven change managementEfficient workflow-driven change manage-ment can help you ensure that no critical steps are missed or bypassed in your application development process. Polarion ALM gives you out-of-the-box project templates with precon-figured workflows to help you automate yourprocesses and use a central repository for all Live project planning.relevant data. The software supports standard environments, such as Agile/Lean, traditional and hybrid, and custom environments includ-ing: Feature Driven Development (FDD), extreme programming (XP), Rational Unified Process (RUP), Scrum and Kanban frameworks and/or methodologies for process management.Accelerating collaborationPolarion ALM uses a browser-based platform that allows 24/7 project access for geographi-cally distributed teams. Members can access the portal over your network or through cloud-based networks anywhere/anytime using a web browser and plugins for selected third-party software or mobile applications. Live dashboards, reports and activity streams allow you to provide real-time delivery of key information and metrics, as required. Access-controlled, threaded commenting and email change alerts help you speed up collaboration while protecting data integrity. The Polarion LiveDoc solution provides the functionality you need to support collaboration with external teams.Extending ALM capabilitiesAn open architecture with application programming interfaces (APIs) lets you extend the Polarion ALM solution to meet your needs.A 10,000+ Polarion member community has contributed nearly 200 extensions for Polarion products. Ready-made plug-ins for popular third-party tools such as Hewlett Packard Enterprise Quality Center, Jira, Simulink and more make it easy to set up an integration for internal and external teams using those options while removing adoption obstacles and ensuring a smooth transition.Polarion ALM is built on top of Apache Subversion, a leading software configuration management (SCM) system. Beyond source code management, Polarion ALM providesfunctionality for managing all of your Workflow driven collaboration on Wiki.application lifecycle elements: system require-ments and specifications, verification proce-dures, project plans and tasks. You can store relevant data in version-controlled repositories and track each process change. Optional support for electronic signatures ensures compliance with the United States Food and Drug Administration (FDA) 21 code of federal regulations (CFR) Part 11 and other standards.Responding faster to changesDevOps is a methodology that combines development and operations as a practice to emphasize collaboration and communication to help facilitate process automation. The DevOps-oriented capabilities in Polarion ALM can help you increase collaboration, reduce production risks and release your products or services in less time. Sharing information, plans and requirements helps your project teams respond faster to frequent changes, automate repeated cross-team tasks andreduce deployment errors.Achieving traceabilityCross-project semantic linking and workflow controls can help ensure comprehensive traceability for your company. The robust reporting capabilities of Polarion ALM can make it easy for your company to certify compliance with regulatory governing bodies including: Capability Maturity Model Integration (CMMI); Communications and Power industries (CPI); Federal Aviation Administration (FAA); FDA; International Electrotechnical Commission (IEC); International Organization of Standards (ISO); Software Process Improvement and Capability Determination (SPICE). Polarion ALM includes a certified ISO 26262 project template.Software re-use and branching Branching, in revision control and software configuration management, is the duplication of an object under revision control so that modifications can happen in parallel alongboth branches. Polarion LiveBranch™ anddocument re-use provide easy yet robust waysto manage commonalities in your productvariants without the use of copy/paste.Propagate changes in “master” specs tobranched specs instantly or on demand.AdvantagesApplication lifecycle management can helpyour company achieve a number of advan-tages. By using Polarion ALM, you can increaseoverall efficiencies by creating process stan-dards and facilitating proper resource alloca-tion. Through enhanced collaboration,Polarion ALM can help you provide completeand timely insight into all elements of theproject lifecycle. It can also help you automateand streamline processes to achieve a fastertime-to-market with higher quality productsthat meet your requirements andspecifications.© 2016 Siemens. A list of relevant Siemenstrademarks can be found here. Othertrademarks belong to their respectiveowners.56100-D11 7/16 HSiemens DigitalIndustries Software/softwareAmericas180****5351Europe00 800 70002222Full traceability from requirements to source code.。
英语十种职业名词作文
As a high school student, Ive always been fascinated by the diversity of careers available in the world. Each profession has its unique charm and challenges, and Ive often daydreamed about what it would be like to be in each of these roles. Heres a glimpse into ten different careers that have caught my attention, and the reasons why they intrigue me.1. Astronaut: The idea of floating in space, looking back at our blue planet, is nothing short of magical. Astronauts are the modernday explorers, pushing the boundaries of human knowledge and experience. They undergo rigorous training, and their courage and dedication are truly inspiring.2. Archaeologist: Unearthing the past and piecing together the stories of civilizations long gone is an adventure in itself. Archaeologists are detectives of history, and their work can rewrite our understanding of the human story.3. Chef: The art of transforming ingredients into culinary masterpieces is a skill I deeply admire. Chefs are not just cooks they are artists who create experiences through taste, texture, and presentation.4. Software Developer: In the digital age, software developers are the architects of our virtual world. They create the applications and systems that we rely on daily, and their creativity and problemsolving skills are essential in this everevolving field.5. Environmental Scientist: With climate change and environmentaldegradation being pressing issues, environmental scientists play a crucial role in finding solutions. Their work in conservation and sustainability is vital for the health of our planet.6. Nurse: The compassion and care that nurses provide to patients is unmatched. They are the backbone of healthcare systems, working tirelessly to ensure the wellbeing of others.7. Journalist: Journalists are the watchdogs of society, uncovering the truth and informing the public. Their commitment to accurate reporting and their pursuit of stories that matter are cornerstones of a free press.8. Architect: Designing structures that stand the test of time is an incredible feat. Architects combine aesthetics with functionality, creating spaces that shape our daily lives and the skylines of our cities.9. Teacher: Educators are the unsung heroes who shape the minds of future generations. Their impact extends far beyond the classroom, influencing the way we think, learn, and grow.10. Entrepreneur: Starting a business from scratch and turning an idea intoa successful venture is a testament to an entrepreneurs vision and tenacity. They take risks and innovate, driving economic growth and creating jobs.Each of these professions requires a unique set of skills and a passion for what they do. Whether its the thrill of discovery in archaeology, the precision of coding in software development, or the lifechanging impact ofteaching, each career path offers its own rewards and challenges.For me, the most appealing aspect of these careers is the opportunity to make a difference. Whether its through scientific research, artistic expression, or social advocacy, these roles allow individuals to contribute positively to society and leave a lasting legacy.In conclusion, the world of work is vast and varied, offering a multitude of opportunities for those willing to explore and dedicate themselves to their chosen field. As I consider my own future, these ten careers serve as a reminder that there is no limit to what one can achieve with passion, hard work, and a commitment to excellence.。
The software industry and India’s economic development
Information Economics and Policy14(2002)253–273/locate/econbaseThe software industry and India’s economic developmenta b,*Ashish Arora,Suma Athreyea Heinz School of Public Policy and Management,Carnegie Mellon University,5000Forbes Avenue,Pittsburgh,PA15213,USAb Faculty of Social Sciences,The Open University,Walton Hall,Milton Keynes MK76AA,UK AbstractThis paper assesses the contribution of software to India’s economic development,paying particular attention to the role of software in the absorption of labour and the development of human capital in the economy.The success of the software industry has increased the relative value of professional workers,not only programmers,but also managers and analysts.The growing importance of human capital,in turn,has led to innovative models of entrepreneurship and organization,pioneered by the software sector,and these are slowly taking root and spreading to other sectors of India’s industry.A potentially important and under-appreciated contribution of the software industry is thus its exemplar of good entrepreneurship and corporate governance to the rest of India.Though less visible than the macro contributions to employment and foreign exchange,this role is a source of productivity improvement for all industries,and can have powerful long-term benefits for India’s industrialization and growth.©2002Elsevier Science B.V.All rights reserved. Keywords:Indian software;Software exports;Software and growth;Human capital and development JEL Classification:F1;I2;L8;J5;O01.IntroductionIn little over a decade,India has emerged as a major exporter of software in the international economy.This remarkable feat has been accomplished through the extraordinary growth of Indian software which,in the last5years,expanded at a compound annual rate of56%.More than two-thirds of this was due to exports,*Corresponding author.Tel.:144-1908-65-45-56;fax:144-1908-65-44-88.E-mail addresses:ashish@(A.Arora),s.s.athreye@(S.Athreye). 0167-6245/02/$–see front matter©2002Elsevier Science B.V.All rights reserved.PII:S0167-6245(01)00069-5254A.Arora,S.Athreye/Information Economics and Policy14(2002)253–273 making the industry a major export earner for the country.The proportion of software exports to merchandise exports grew from a negligible amount in1990to over6%in1998–1999.Remarkably,these software exports are largely due to the efforts of domestic rather than foreignfirms.Of the top20exporters in1998–1999,only sixfirms were foreign subsidiaries.The software industry contributes1%of India’s GNP,but has accounted for over7%of the growth of its GNP(Kumar,2000a,b).In1997,the software industry employed160,000of the total employed workforce of28.245million. Employment in the industry,although constituting only a small fraction of the total,has grown quickly and estimates for the year2000suggest that there will be over410,000IT professionals employed in India.Can the software sector continue to contribute significantly to economic growth, and what forms are these contributions likely to take?To answer this question,we begin by examining in Section2the factors that have contributed to India’s emerging specialization in software exports.We argue that software services are intensive in human capital and the abundant supply of engineers in the country provides not only an absolute wage advantage,but also a comparative advantage. In Section3we review the factors that constrain the current growth of the software industry on the supply side,in particular the role of underinvestment in literacy and in telecommunications infrastructure.Section4analyses the contribution of software growth to human capital formation.High earnings in software have resulted in considerable private investment in training,and the subsequent emergence of a successful self-financing model of tertiary education in some parts of the country.Section5analyses the impact of software on productivity improvements through the linkage effects of software in the domestic economy. We conclude that this mechanism of productivity improvement is of limited importance in the Indian context.Section5emphasizes the role of high software salaries versus the rest of India’s industry in creating productivity-inducing organizational improvements in software.We also analyse the role of software firms as organizational exemplars.Section6summarizes our main conclusions.2.Factors favouring the growth of software revenues in India:the role of comparative and absolute advantagesSoftware is not just another industry.The number of companies that produce software or employ software developers is much greater than the set offirms commonly thought of as softwarefirms,such as Microsoft or Oracle.Indeed,large banks,insurance companies,finance companies,and virtually every organization above a certain size all develop a great deal of software.Much of this software is either developed for a particular user,or consists of a standard‘platform’such as a SAP ERP system or an Oracle accounting system,and is customized to the needs of the user organization.Once in place,these systems have to be maintained andA.Arora,S.Athreye/Information Economics and Policy14(2002)253–273255 enhanced.Some observers claim that over two-thirds of all software development efforts are spent in maintaining and enhancing existing software codes,rather than producing new software(Raymond,1999).Despite the steady growth of software technology and tools,software develop-ment is still labour intensive and requires relatively little capital.Estimates by Lakha(1994)suggest that labour costs accounted for about70%of all software1costs in the early1990s.With the information technology revolution taking hold in the1990s,the demand for IT workers in the developed world has steadily surpassed supply.However,a fairly substantial fraction of these activities can be outsourced and are increasingly conducted away from the user organization.This outsourcing demand has formed the basis of the initial growth of the software industry in India.The needs of software production seem particularly suited to the resource endowments of the Indian economy.Moreover,scale economies are not a significant barrier to entry.Afirm can—and many do—start off as little more than one software development team.Others have started as temporary employment agencies,requiring a few rooms in which to set up a handful of PCs and a telephone.Further,the production of software is not heavily dependent on physical infrastructure such as roads and ports,although a steady supply of electrical power is critical,as is ready access to PCs,workstations and communication,airports, phones,faxes and increasingly,the Internet.The initial growth of the software service industry was facilitated by the enlightened‘hands off’policies of the government of India.By the late1980s and early1990s,PC prices had fallen steadily,as had the prices of other equipment. The government allowed liberal imports of both hardware and software tools,and firms were able to provide their own electrical power through a variety of sources, including self-generation.As Table1shows,this growth of software revenue came2disproportionately from exports,and thus it is worth exploring the nature of India’s advantage in software exports.Tables2and3show the extent of the absolute(labour)cost advantage.1With the decrease in hardware prices and the increase in the wages of software professionals,this estimate is likely to be on the low side for the late1990s.Furthermore,the cost of software is the dominant budgetary item in setting up computerized systems in the west.As the process of computerization accelerates in the world economy,the demand for software will continue to increase. 2As many early observers(Heeks,1996;D’Costa,1998)have noted,this initial growth was markedly dependent on export demand,was based on relatively unsophisticated services,and often was little more than the provision of temporary workers to overseas customers.Arora et al.(2000a)also found that for the most part,Indian softwarefirms were generalists,specializing in terms of neither technology nor vertical industry domains,but competing largely on cost with relatively little to differentiate one from the other.One implication of this is that thefirms surrender the lion’s share of the rents to customers so the net benefits of the mushrooming software industry and its growing productivity are largely passed on to customers,prominently the US which accounts for over60%of India’s total exports of software.256A.Arora,S.Athreye/Information Economics and Policy14(2002)253–273Table1Growth of software revenues($million)Year Export revenues Domestic revenues198422–198526–198638–198754–1989/90105–1994/954853501995/967344901996/9710856701997/9817509501998/9926501250Source:Lakha(1994)forfigures up to1989/90;Kumar(2000a,b)for all other years. Amongst developed countries,only Greece shows similar levels in the salaries of software professionals.If one concentrates on the availability of scientists and engineers(Table3),India has one of the largest reserves of these professionals in the world,almost all of whom speak English.Table3also highlights two other factors.Firstly,India has the potential of expanding this reserve with appropriate investments in primary and secondary education.Secondly,countries such as China and Russia have an even greater supply of trained scientists and engineers.If they were to train a proportion of their scientists in English,these countries could participate more fully in the internation-Table2International differences in salaries paid to software professionals,1995(US$)Switzerland USA Canada UK Ireland Greece India Project leader74,00054,00039,00039,00043,00024,00023,000 Business analyst74,00038,00036,00037,00036,00028,00021,000 Systems analyst74,00048,00032,00034,00036,00015,00014,000 Systems designer67,00055,00036,00034,00031,00015,00011,000 Development programmer56,00041,00029,00029,00021,00013,0008000 Support programmer56,00037,00026,00025,00021,00015,0008000 Network analyst/designer67,00049,00032,00031,00026,00015,00014,000 Quality assurance specialist71,00050,00028,00033,00029,00015,00014,000 Database data analyst67,00050,00032,00022,00029,00024,00017,000 Metrics/process specialist74,00048,00029,00031,000–15,00017,000 Documentation/training staff59,00036,00026,00021,000–15,0008000 Test engineer59,00047,00025,00024,000–13,0008000 Source:/idpm/isicost.htm.A.Arora,S.Athreye/Information Economics and Policy14(2002)253–273257 Table3Reserve of technically trained personnel,selected countries,1995Country Adult illiteracy Scientists/engineers in Population,Reserve ofrates(%)R&D per million of millions scientists/engineerspopulation19951995Males Females1981–1995USA––3732263981,516Japan––5677125709,625Russian Fed.––4358148644,984China10275371200644,400 Germany––301682247,312France––253758147,146UK––241759142,603India3562151929140,279Israel––4826628,956Vietnam493347324,382Turkey8282096112,749Hungary––11571011,570Greece––774107740Ireland––187147484 Source:World Bank,World Development Reports(1997)and(1999).al software industry.But the dynamics of the software industry comes into play as well.As we argue below,the head start enjoyed by the Indian software industry will hurt the prospects of the late comers.The explanation of the growth of software exports from a country like India because of lower labour costs is well known.It also underlies a somewhat pessimistic outlook for the future of these exports and the software industry.Once the surplus of trained labour is depleted,the cost advantage erodes,making India less attractive in comparison to China and Russia,for instance,as the source for lower value-added services(Heeks,1996).The absence of a sizeable domestic market will compound the problem by depriving the country’s software exporters of the experience needed to ultimately enable them to produce higher value-added services and products(D’Costa,1998).In this respect,the only option is for India to develop a sizeable domestic market and reduce its export dependence. This,however,introduces a dilemma.Perhaps the main reason for the absence of a large and sophisticated domestic market is a relatively unsophisticated economy,which has,until recently,grown at3.5%per year.Thus,the develop-ment of a sizeable domestic software market is likely to be a consequence as much as it is a cause of the growth of this particular industry.Indeed,Arora et al. (2000a)find that conditions between the domestic market and exports market are so diverse that knowledge and experience gained from domestic projects are either258A.Arora,S.Athreye/Information Economics and Policy14(2002)253–273not applicable,or too costly for overseas customers.Arora et al.conclude that3,4 domestic market experience is not particularly valuable for the export market. Another way of looking at the growth of software exports is to determine whether India enjoys an underlying comparative advantage in software production `vis-a-vis the rest of the world.If such a comparative advantage does exist,both the absolute cost advantage and favourable circumstances such as the demand caused by the millennium scare could provide the experience and scale of output needed for dynamic learning processes to kick in and positively influence the growth of the sector’s productivity.In this scenario,the future of Indian software exports is not entirely bleak and increasing productivity could compensate for the erosion of the labour cost advantage.Productivity levels measured as revenue per employee are lower in India than in other parts of the world(notably Ireland and especially Israel).More importantly, however,compared to other countries,software in India is far more productive than other sectors—the essence of a comparative advantage argument.This is clear when we compare the ratio of labour productivity in software.It is twice that of5India’s manufacturing and1.3times that of the US(Table4).The picture is similar for Israel,another country with a fast growing software industry.In an open economy,both India and its trading partners benefit from the country’s specialization in software,and implicitly its imports in less productive economic sectors such as manufacturing.The distribution of these gains is a moot point,of course.Given the country’s heavy reliance on the US for software exports and their undifferentiated nature,it seems likely that productivity improvements in Indian software produce greater benefits for the US rather than India. Although the share of software production in India’s industrial output,exports and employment is increasing,its share in the world market remains low.The picture changes somewhat when we look at only the share of the country’s customized software in the global market:this is estimated to have gone up from 11.9%in1991to18.5%in1999(Kumar,2000b).Limited infrastructure continues to constrain the industry.The most important of3This conclusion,however,is conditioned by the types of export projects:simple,small and not very sophisticated.In short,there may be the‘chicken and egg’problem.Given the nature of export projects,sophisticated domestic projects may be of little value,but overseas customers appear unwilling to outsource projects that would enable Indianfirms to acquire the necessary experience. 4A more compelling argument is that the domestic market could be the source for particular types of differentiation,for example,software for multiple languages and using multiple scripts,and for mutual translation.This could be a source of competitive advantage in countries with more than one language where forms,and government and corporate publications have to be in multiple languages.Alter-natively,growth in the level and sophistication of domestic demand mayfinally provide companies with an easy way to‘break’into foreign markets by demonstrating their capabilities.These may yet happen,as the industry matures into more differentiated and distinct segments.5We use value-added as the index of labour productivity in manufacturing and revenue per employee as the index of labour productivity in software where few material inputs are needed for production.A.Arora,S.Athreye/Information Economics and Policy14(2002)253–273259 Table4Comparative advantage in software production across selected countries,1995All manufacturing Software Comparative advantageRevenue perOutput per Value added per Index1Index2employee(3)employee(1)employee(2)(3)/(1)(3)/(2)($’000)($’000)($’000)Israel112.2038.30100.000.89 2.61 Ireland242.20117.10142.240.59 1.22India20.80 4.108.930.43 2.18 France205.1377.143161.320.79 2.09 Finland231.9276.1683.460.36 1.10USA206.0098.20126.020.61 1.28 Sources:authors’computations from the following data sources:data in columns(1)and(2)are taken from the UN Industrial Statistics(1998and1999)published by UNCTAD.Exchange rates used to convert local currencies into dollars are taken from line rf of the International Financial Statistics published by the International Monetary Fund.Data in column(3)are derived from the following national and international sources:India from NASSCOM();Israel from Israeli Association of Software Houses(.il);Ireland from National Software Directorate (http://www.nsd.ie),Ireland,and France,Finland and USA from The Software Sector:A Statistical Profile for Selected OECD Countries(OECD /dsti/sti/it/infosoc/index.htm). Figures for Israel are obtained by dividing Israeli software revenues by estimated employment.Figures for Ireland are obtained by excluding multinationals from the calculation,which may therefore, underestimate revenue per employee in software.these are the availability of power and the quality of the telecommunications infrastructure(bandwidth and,increasingly,limited telephone penetration).In 1996,India had15main telephone lines per1000people,compared with395per 1000for Ireland and446per1000for Israel.The situation is more serious when we consider the penetration of PCs in the total population:1.5computers per1000 people versus145for Ireland and117.6for Israel(WDR1998/99).It is difficult to estimate accurately the extent to which infrastructure constraints have affected productivity.Some indirect evidence,however,is available.Costs for power are the second highest expenditure and many softwarefirms generate their own 6power.Low bandwidths are also a problem.While current bandwidths are adequate for simple tasks,they could become an obstacle to more complex,higher value-added projects being awarded to the samefirms.For the newly emerging area of e-commerce,the lack of telephone penetration will emerge as an important problem.Here,too,the solutions point to the nature of the problem.Mobile phone penetration(which does not require land lines)experienced the most rapid growth in smaller towns.In this context,the development of mobile telephony and Internet products presents a window of opportunity and growth inasmuch as6A manager of a leading softwarefirm noted that spending on diesel power generators was the second largest item of thefirm’s capital expenditure budget.Thisfirm claims to have generated4MW in1997,the year in which the interview took place.260A.Arora,S.Athreye/Information Economics and Policy14(2002)253–273 demand for these is not constrained by telephone lines,or by literacy on the part of mobile phones.3.Can the Indian success be replicated?Implications for other developing countriesMany researchers have predicted competition from other labour-abundant countries such as China,or even Russia and Ukraine,where economic woes have resulted in large reserves of underemployed engineers and scientists.Countries, including China,are reportedly investing heavily to introduce English language skills to their engineers.Undoubtedly,the current market shares of these countries could be increased—and increased substantially—if abundant skilled labour were the sole determinant of success.But the success of the software industry also reflects a certain level of entrepreneurial and managerial capabilities,as well as the importance of strong links with major markets.In the case of India,these are expatriates working in high-level technical and managerial positions in the west, primarily in the US.Such links helped Indian entrepreneurs to respond quickly to the growing demand for software services.At a minimum,this meant the ability to recruit programmers,and arrange for and manage outsourcing contracts.As thefirms grew,so did the challenges.Successful enterprises developed capabilities that became the source of India’s competitive advantage.Interviews with US managers reported in Arora et al.(2000a)highlight the importance placed by American companies on the ability of the Indianfirms to mobilize large teams of developers at short notice.This,in turn,places demands on thefirms to develop substantial expertise in recruiting,screening,training and,as discussed earlier,retaining software professionals.As discovered in Russia,this is no trivial matter.Russian firms reportedly complain that getting foreign companies to overcome their hesitation of doing business with the country is a major obstacle to offshore programming.Paucity of quality control and proper management are also handicaps,despite a substantial cost advantage in wages.Russia trails behind India in the number of companies with the ISO9000certification(Santana,2001). Furthermore,Indianfirms are increasing productivity by improving their software development processes,by moving up the value chain,and by developing proprietary development tools(Table5).More recent entrants in the industry have also had some success at developing products.Arora et al.(2000a)find that larger firms(with more than250employees)earn$8000–10,000per employee more than smaller ones.The number of such largefirms has increased over time.Similarly, Arora et al.(2000a)report that Indianfirms rated at CMM level3or higher earn about$6000–10,000per employee more thanfirms without this qualification.AsA.Arora,S.Athreye/Information Economics and Policy14(2002)253–273261 Table5India’s manpower and revenues/man-yearYear Manpower Revenue per employee($)1993–199490,0006198.51994–1995118,00069981995–1996140,0008924.51996–1997160,00011,0361997–1998180,00015,0001998–1999250,00015,600Source:Arora et al.(2000a,Table1b).7many as32Indian softwarefirms have received the SEI-CMM certification and more than half the companies with the CMM4and5ratings are in India. These ratings demonstrate the significant organizational capability in software development that has been built up over the last decade,making it difficult for8other global companies to compete.More importantly,competitors have to contend with higher market visibility and the business connections Indianfirms have been able to establish.Out of Fortune’s500companies,185now outsource their software production to India.Indeed,onsite services have given way to more profitable offshore services with dedicated software centres,an indication of the trust US and Europeanfirms have in the quality of Indian software services. Although not insurmountable,these are formidable barriers for others to overcome, including the country’s own late entrants to the industry.Thus,we are likely to see established Indianfirms leverage their reputation and capability by outsourcing to China and elsewhere,as TCS,Wipro and Infosys are reported to be considering (Sengupta,2001).Similarly,a large Chinese telecomfirm,Huawei Technologies, has set up an R&D centre in Bangalore where180Chinese programmers work alongside the locals.In other words,rather than a zero sum game,China and other nations may be able to participate in the international division of software labour through collaboration with India.7CMM(Capability Maturity Model)is a structured process for software development associated with the Software Engineering Institute at Carnegie Mellon University.It consists offive‘maturity’panies or units assessed at level four andfive are capable of controlling,managing and improving software development practices.Though initially developed as a means of providing improved software systems for the Department of Defence in the US,the CMM is becoming popular among Indian software servicefirms as a means of signalling their capability to overseas clients, particularly in the US.8Arora et al.(2000a)do not,however,find any difference in the productivity of younger and older firms.262A.Arora,S.Athreye/Information Economics and Policy14(2002)253–2734.The growth of software and human capital formation:public and private investments in training and the rewards to an engineering9educationAlthough India has a large number of scientists and engineers,it also has one of the lowest literacy rates in the world;52%of the total working population are illiterate.As Table3shows,despite the vast reserve of engineers,their number per million is smaller than in several other countries.There is a corresponding over-reliance on the current reserve of trained but underemployed engineers,for whom the slowly growing and protected economy cannot generate adequate demand.A large proportion of the employees in softwarefirms are college graduates,as highlighted by a sample survey of nearly60softwarefirms who reported that over 80%of their employees had engineering degrees.Only13%were non-engineers10trained in software development.This preference for engineers was unremarkable and of little consequence at the start of the industry,when demand versus annual supply was small.Currently, over160,000engineers from all disciplines graduate every year.The sharp and sustained growth of the software industry had increased its workforce to nearly 250,000by1998–1999,and estimates suggest that this may reach400,000in the years2000–2001.If the software industry continues to grow at50%per year,then there will be a shortage of engineers,regardless of productivity improvements(see11Arora et al.(2001)for more details).These projections are consistent with other evidence.Wages in the software industry have risen over20%per annum and attrition rates are high.In1998–1999 in a sample of over100enterprises,more than half of thefirms,irrespective of age,size or market orientation,reported the shortage of manpower and employee attrition(Arora et al.,2000a)to be among the three main problems.Virtually all firmsfind it difficult to attract and retain talented software developers despite wages that are substantially above Indian standard.Public policy has responded with increased investments in engineering colleges, placing greater emphasis on information technology in engineering curricula and on the creation of institutes of information technology(IIIT)similar to the better9This section draws heavily upon Arora et al.(2001).10An earlier study(NASSCOM,1999)reported that only2%of all software developers trained in private training institutes join software developmentfirms.11Recognizing the importance of this fact,many Indian policymakers have called for an‘educational emergency’declaration to ensure that the supply of skilled software developers is increased.Several CEOs of the smaller software developmentfirms and NASSCOM(the professional association representing the views of thesefirms)have begun to argue that the shortage of skilled labour is constraining their ability to grow.(See also Basic Background Report(BR-3)for the National Task Force on Information Technology(IT)and Software Development(SD)submitted to the Prime Minister of India,18th March1999.)。
软件测试的价值观
外文资料名称：Value-Based Management ofSoftware Testing外文资料出处：Institute of SoftwareTechnology & Interactive System/research/valuebased-management-software-testing/ 附件： 1.外文资料翻译译文2.外文原文基于价值的软件测试管理作者：鲁道夫,斯蒂芬,保罗译：荣子健摘要:根据研究表明测试已经成为软件开发过程中一个很重要的环节，它占据了整个软件开发成本的百分之三十到五十。
然而测试往往没有重视到商业价值，也可能与预期的目标不一致。
路径测试、分支测试、功能测试、异常测试、场景测试以及需求测试等对于软件来说都是同等重要的。
然而在实践中百分之八十的价值往往来自百分之二十的软件。
为了从软件测试中得到最大的投资回报，我们通过测试管理最大化软件的价值。
在本章，我们将详细解释对基于价值的软件测试，阐述支持基于价值的测试实施，建立基于价值的测试管理的框架，并举例说明该框架。
关键词: 基于价值的软件测试,基于价值的测试,测试成本,测试收益,测试管理11.1 前言测试是软件质量保证过程中最重要和最广泛使用的方法。
校验和验证旨在通过需求分析, 测试软件来确保其正确运行功能，保证软件的质量和软件的可靠性。
在IEEE610.12(1990)中,测试被定义为“在规定条件下运行系统对组件进行观察和记录,并对系统或者组件进行评价的活动”。
测试在实践过程中被广泛的使用，质量保证策略在诸多组织中扮演着重要的角色。
软件影响着成千上万人的日常生活，担负着巨大的任务。
因此软件在不久的将来将显得尤为重要。
研究表明，测试通常消耗软件开发成本的30%至50%。
对于安全危急系统，甚至更高的比例也不足为奇。
因此软件测试面临的挑战就是为了进行高效的测试而寻找更多的合理途径。
软件测试管理的价值在于努力减少测试成本和满足用户需求。
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Classic Mistakes Steven C.McConnell
• •
• • • •
- Undermined motivation. Has a larger effect on productivity and quality that any other factor (Boehm 1981) - Weak personnel (Boehm 1981, Lakhanpal 1993) - Uncontrolled problem employees. Failure to take action to deal with a problem employee (Weinberg "Phychology of a Computer Programming", 1971) - Heroics. It can be beneficial. (Bach 1995), but "can-do attitudes escalate minor setback into true disasters" (De Marco 1995) - Developers-Customer friction: poor communication, conflicts (Jones 1994) - Lack of user input. (Standish Group 1994) - More ...
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Motivational Factors (1)
Achievement: getting work done; building something that works; Advancement: getting more responsibility Company policy and admin: being in line with written company direction; Job security: a quaint 20th century notion; Personal life: the opportunity to spend time with family and friends and to pursue hobbies and interests unconnected with work; Possibility for growth: learn new skills; improve the use of current skills; become more knowledgeable; unique for each person; Recognition: identification by organization, customers, whatever of an individual’s contribution,
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Im portance
10 50 60 70 80 90
20Biblioteka 30401000
A ch ie ve m en R t ec og ni tio n W or k Its R el es f po ns ib ili A ty dv an ce m en t In te rr ea lti on s S al ar y G r su ow bo th rd in at es
Do courage, honesty, helpfulness or ... improve an overall work process? Manager dilemmas: How to measure it? How to control it? How to motivate people?
Treat people as best as you can, so they have a minimum of dissatisfaction Use people so they get achievement, interest and they can grow and advance in their work
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Motivation & Movement
Frederick Herzberg: Motivation or Movement? Motivation – function of growth from getting intrinsic rewards out of interesting work. Movement – function of fear of punishment or failure to get intrinsic rewards. Motivating factors: simulate honest growth and performance
Motivators by Job Level
Importance of Motivational Factors by Job Level
Motivator
In te rr el at Sta io t ns us In su te pe rr rio el at r S io up ns er C pe om vi er si pa on s ny te ch P ol ni ic ca y l an d A dm W or in k co nd iti on s P er so na ll ife Jo b se cu rit y
9. 10. 11. 12. 13. 14. 15.
Relations subordinate Salary Personal life Relations superior Job security Status Company policy and administration 16. Working conditions
The Human Side of Agile Software Development
Stephen Ford Alex Grabelkovsky Guy Davis
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Agenda
Observations on people Traditional System Development Environmental Issues Team considerations Agile methods and people factors
Software development - human and an intellectual activity Intellect - is it enough to develop a successful project?
More dimensions?
Physical? Emotional? Spiritual?
9. 10. 11. 12. 13.
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Motivation: Software People
1. 2. 3. 4. 5. 6. 7. 8.
Achievement Possibility for growth Work itself Recognition Advancement Supervision technical Responsibility Relations peers
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Harmony of Objectives
The Principle of Harmony of Objectives (Koontz-O’Donnell, 1972)
The more that people perceive that their personal goals are in harmony with organizational goals, the greater will be their contribution to organizational goals.
Manager
Project Leader
Programmer Analyst
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Growth Needs vs. Social Needs
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Vote
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Motivation: General Population
1. 2. 3. 4. 5. 6. 7. 8.
Achievement Recognition Work itself Responsibility Advancement Salary Possibility for growth Relations subordinate
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Motivational Factors (2)
Relations peers: how you get on with your day-to-day colleagues; Relations superior: access to the boss and decision makers; Relations with subordinates: Responsibility: ability to make / influence decisions. Salary: Status: how your peers value you Supervision technical: the ability to provide leadership and oversight in technical activities Work itself: do the job well; Working conditions: physical comfort, style and grace;
Status Relations superior Relations peers Supervision technical Company policy and administration 14. Working conditions 15. Personal life 16. Job security