Advanced Computer Graphics
Advanced Computer Graphics CSCI 780
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This 8 page Class Notes was uploaded by Aliza Ruecker on Thursday October 29, 2015. The Class Notes belongs to CSCI 780 at College of William and Mary taught by Staff in Fall. Since its upload, it has received 20 views. For similar materials see /class/231167/csci-780-college-of-william-and-mary in ComputerScienence at College of William and Mary.
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Date Created: 10/29/15
39 Conclusion 39 Discussion I HZ 1mman I HZ 1mman I HZ 1mman I HZ 4 v u w puma 1mman 9 a I HZ gname pname excu 1mman I HZ 1mman I HZ 1mman I HZ 1mman I HZ CSci 780 Advanced Software Engineering Automated Assistance for Program Restructuring by William D Griswold and David Notkin 1 naznna 1 Outline 0 Problem 0 Proposed Solution 0 Example 0 Transformations 0 Implementation 0 Evaluation 0 Discussion 0 Summary 1 naznna Problem 0 Maintenance degrades systems over time 0 Quick and dirty xes o No restructuring due to fear of breaking something 0 Information hiding doesn t always help 0 Can39t anticipate all changes 0 Can39t always afford to implement exibility 0 Must choose a possibly suboptimal modularization o Crossmodule changes are necessary and the cause of degradation 1 naznna 3 Belady and Lehman 1977 OS360 A system that is used undergoes continuing change until it becomes more economical to replace it by a new or restructured system 1 naznna Proposed Solution 0 Ease maintenance by breaking it into restructuring followed by change 0 But manual figtltes ol cen introduce bugs 0 Study 53 of bugs introduced with new feature 0 Use a tool to help with the restructuring 0 Automatically transform the code using highlevel operations 0 But only when the meaning will not be changed 1 naznna 5 Example sub push xtamk s smke ms sr 191 stack hssu return stack sub popstack amp 1 val stackh a stackremovehead return val pushmysmyakscn pushpv uvhaphmmnmam 1 naznna Transformations 12 createvariable add a new variable Can39t collide Winn exrsung names renamevariable rename all occurrences Can39t collide Winn exrsung names I moveexpr move an expression intervening expressoi39is can39t depend on moved one vartoexpr replace a var use with its definition Can39t have sideerrecs Must sauer movenexpr mam 7 Transformations 22 exh39actfunction move the selected lines into a function and replace the lines with a call Need to identity aii nonnlocal variables and pass tnem as parameters with a function ca infeasible ll l generall But heuristics are workable scopesubstimtecall find places where code can be replaced ll Also bindingtoexpr exprtobinding inline function inrmnm x Implementation 1 I2 Three representations Syntacucai parse code into an abstract syntax tree Program dependence grapn PDG snows data reiauonsnips between statemeriB Control ow grapn CFG shows ordenng of statemeriB Need to manage relationships between reps orrect Ef cient mam v Program Dependence Graph imam in M anagement Strategies p N c 5 quotu a w r a mam n Implementation 22 Performing meaningpreserving transformations procedure deitape for d ll i usese do cornpensau ontrarisu iocaitranse Map compensationitrans to PDGCFG do graph manipulation then map hack to AST imam i2 CSci 780 Advanced Software Engineering Peopleware Productive Projects and Teams Tom DeMarco and Timothy Lister lznznna 1 Outline 0 Managing the Human Resource o Coding War Games 0 The Work Environment 0 The Right People 0 Jelled Teams o Teamicide 0 Conclusion 0 Discussion lznznna 2 Problem 0 The software industry has a notorious reputation for being out of control in terms of schedule accuracy cost accuracy amp quality control A majority of large systems run late egtltceed budgets amp many are cancelled Capers Jones 0 Study of 500 projects DeMarco amp Lister o 15 cancelled aborted or postponed o 25 failure for projects requiring gt25 staffyears lznznna 3 What Is The Cause 0 Hardware 0 Faster computers 0 Bigger displays 0 Newer pagers 0 Software 0 Better compilers o Newer programming languages 0 Code analysis mols lznznna 6 Peopleware o The major problems of our work are not so much technologyrel as socblogZ ain nature 0 Success factors 0 Communication 0 Staf ng 0 Motivation 0 Low turnover 0 We tend to focus on technical issues because they are easy to tac e lznznna 5 Peoplewa re cont 0 Motivation is undoubtedly the single greatest in uence on how well people perform Most productivity studies have found that motivation as a stronger influence on productivity than any other factor Steve McConnell Rapd Development 0 Hire the best people keep them happy so they don t leave and remove obstacles from their way DeMarco amp Lister lznznna a The Production Bias Squeeze out errors Occaslonal mls takes natural and healthy No goo ng on the Job Selfnmouvauorl creatlylty interenangeaple Workers Need unlquel less Opumlze the steady state Projectalwayscharlglrlg Standardlze procedures Some standardlzauorl Overtime Spanish Theory of Value Value acquisition is a zerosum ame Example unpald oyerurne thaid overtime is a myth Burnout undertlrne turnover Resentment Workll lg faster not better Example Eagle project at Data General No experlrnentauon Selectlye experlmel39ltauol39l Great productlylty 4enure tearn qult afterwards lzlnnm 7 lzlwnm x Quality If Time Permits Coding War Games Quality is not just another product attribute a We can39t afford to do more QampA There39s a market cost for poor quality But developer39s selfesteem is based on it Would you enjoy producng a crappy product7 Quality neeck to be set by the developer not e customer Egtlt HP nasa culture orquallty and low turnover lzwnm v Design code and test mediumsized program Mll llmal urne mll llmal derece 2 person teams compete to complete programming challen es Normal work environment hours tools etc 600 participants 92 companies 19841986 lzlwnm m Results Individuals Bestvs Worst 10 to a Best halfvs Worst half 2 to 1 Nonfactors nghnlevel prograrnrnlng language Years of experlel lce salary weak correlauon Quallty leyel zero defect group outperformed others But there Wasan organizational correlation Bestorganlzauon ys worstorganlzatlon 10 to 1 lzwnm n Workplace Stats PROGRAMMER WORKPLACE AVERAGES FROM THE smug Dmlcmcd rpm 3 squaw rm Encloxurc cubicle all 73 quot Cubwlc tmylu s rut Denimlied terminal 60 rseiir l i Iii m lzlwnm l2 Workplace Stats cont Impact of Workplace FERCENT OF ENVIRONMENTAL FACl OR row 21 lamrem 25 ALL QuEs39noN RESPONDENTS 7x sq as ml s 5an l your workplace accsplahly quiet 58 No 57quotquot 3 W Yquot 239quot Y m yrs um yo 9 yes is um Su sm pmacy39 am No 52 yes um yes 29 yts Do people one mmrup you 7quotquot Y W V 57 quot Y n til 1 1 n u S y 51quot Y you nuulzsxly m yet 76 vs 62 m t u dimem or imposxible to work Docs your workman make u 1y In your workplace lmm 957 41 Yes m reel appmnmd 57 yes wr yes 45quot yns not your workplace make you lccl 13M Santa Teresa Study appreciated 51 No Worklng alone 30 Worklng wmn others 70 is your workplace at work 5 plain as your workplace at homc w No 30 tlme nolsersensmve 70 urne nolse generators mam n mwnm m The Penalty of Interruptions Solutions Fbm condition of deep mental involvement E I acbor uninterrupted time total time Takes about 15 minutes to achieve flow With interruptions every 15 minutes More war games results Workers Wlth qulet Workplaces were 13 rnore llkely rk to dellver zerordefect W0 mam l5 Email instead of phone ug e p one Structure workplace to have meeting rooms with doors Retreat to these rooms for discussions Avoid headphones music hinders creativity Offices with win ows Retreats Dont be a 39aid of personalization lzwnm m The Right People Managers Make sure to look for the right thing Can the person perform7 Can tne person learn7 Not a professlonal drone appearance Jobseekers Hove your capabilities D elo oftwar portfollo ev p a s Do an lntems W k for mam n Keeping Good People Strive to be the best O39eate a binding atmosphere expect to stay Communlty garden basketball court Lethelp people get ner Master s or PhD Widespread retraining and promotion lzwnm o