CS 451 Software Engineering This Course Student Software vs. Industrial SoftwareSoftwareSoftware …Software…Software…Software…The Real ProblemsSoftware is Expensive…Late & UnreliableUnreliable…Maintenance is More ExpansiveSoftware Engineering ChallengesBasic ProblemScaleScale…Scale…Scale: ExamplesChangeHardware-CharacteristicsSoftware - CharacteristicsSoftware - CharacteristicsMore Questions to Think AboutSummarySummarySoftware – MythsDrexel University CS 451 Software Engineering Yuanfang Cai Room 104, University Crossings 215.895.0298 [email protected] University This Course  SE is unlike other CS topics  OS , DBMS , Compilers etc talk about specific types of software product  SW Engg. focuses on general software  Software Engineering is the systematic approach to development, operation, maintenance, and retirement of sw.  Basic Q. of SW Engg.: How to develop industrial-strength software?Drexel University Student Software vs. Industrial SoftwareDrexel University Software  Q : If you have to write a 10,000 line program in C to solve a problem, how long will it take?  Answers: generally range from 2-4 months  Let us analyze the productivity  Productivity = output/input resources  In SW output is considered as LOC  Input resources is effort - person months; overhead cost modeled in rate for person month  Though not perfect, some productivity measure is needed, as project has to keep it high  The productivity is 2.5-5 KLOC/PMDrexel University Software …  Q: What is the productivity in a typical commercial SW organization ?  A: Between 100 to 1000 LOC/PM  Q: Why is it low, when your productivity is so high? (people like you work in the industry)  A: What the student is building and what the industry builds are two different thingsDrexel University Software…  In a univ a student system is built while the commercial org builds industrial strength sw  What is the difference between a student program and industrial strength sw for the same problem?Drexel University Software… Student  Developer is the user  bugs are tolerable  UI not important  No documentation Industrial Strength  Others are the users  bugs not tolerated  UI v. imp. issue  Documents needed for the user as well as for the organization and the projectDrexel University Software… Student  SW not in critical use  Reliability, robustness not important  No investment  Don’t care about portability Industrial Strength  Supports important functions / business  Reliability , robustness are very important  Heavy investment  Portability is a key issue here  Heavy testing: (30%-50% total effforts)Drexel University The Real ProblemsDrexel University Software is Expensive…  The HW/SW ratio for a computer system has shown a reversal from the early years.  In 50s , HW:SW :: 80:20  In 80s , HW:SW :: 20:80  So , SW is very expensive  Importance of optimizing HW is not much  More important to optimize SWDrexel University Late & Unreliable  20-25% of SW projects never complete  Because after some time they realize that the final cost will be much higher  Many companies report runaways  budget & cost out of control  consulting companies to help control them  One defence survey found that 70% of the equipment problems are due to SW  Many examples of software failuresDrexel University Unreliable…  SW failures are different from failures of mechanical or electrical systems  In software, failures are not due to aging related problems  Failures occur due to bugs or errors that get introduced during development  I.e. the bug that causes a failure exists from start, only manifests laterDrexel University Maintenance is More Expansive  Once sw delivered, it enters maintenance phase  Why is maintenance needed for sw when it does not wear with age?  Residual errors requiring corrective maint  Upgrades and environment changes – adaptive maint  Over sw life, maint can cost more than the development cost of swDrexel University Software Engineering ChallengesDrexel University Basic ProblemDrexel University Scale  SE must deal with problem of scale  methods for solving small problems do not scale up for large problems  industrial strength SW problems tend to be large  SE methods must be scalable  Two clear dimensions in this  engineering methods  project management  For small, both can be informal or ad-hoc, for large both have to be formalizedDrexel University Scale…Drexel University Scale…  An illustration of issue of scale is counting the number of people in a room vs taking a census  Both are counting problems  Methods used in first not useful for census  For large scale counting problem, must use different techniques and models  Management will become criticalDrexel University Scale: Examples Gcc 980KLOC C, C++, yacc Perl 320 KLOC C, perl, sh Appache 100 KLOC C, sh Linux 30,000 KLOC C, c++ Windows XP 40,000 KLOC C, C++Drexel University Change  Only constant in business is change!  Software must change to support the changing business needs  SE practices must accommodate change  Methods that disallow change, even if high Q and P, are of little useDrexel University 22 Hardware-CharacteristicsDrexel University Software - Characteristics 23Drexel University Software - Characteristics Software is developed or engineered, it is not manufactured in the classic sense. Except obviously the need to copy the disk or download the program. Software does not wear out. Is this true? The book states, Software is not susceptible to the environmental maladies the cause hardware to wear out.Drexel University More Questions to Think About  The differences between software and hardware  Do they change similarly? Why or why not?  Do they age similarly? Why or why not?  Do they all need to be specified before construction?  Some open source software are much more successful than similar proprietary software. Does it mean that open source developers are smarter than company employees? Why or why not?  Will making a software project open source always improve the quality of the product? 25Drexel University Summary  The concept of Software  The difference between industrial vs. student software  The challenges of software development