LECTURE 1.ppt

Introduction to Software Engineering (LECT 1) Prof. R. Mall Dept. of CSE, IIT, Kharagpur 1 Organization of this Lecture What is Software Engineering? Programs vs. Software Products Evolution of Software Engineering Notable Changes In Software Development Practices Introduction to Life Cycle Models Summary 2 What is Software Engineering? Engineering approach to develop software. – Building Construction Analogy. Systematic collection of past experience: – Techniques, – Methodologies, – Guidelines. 3 Engineering Practice Heavy use of past experience: – Past experience is systematically arranged. Theoretical basis and quantitative techniques provided. Many are just thumb rules. Tradeoff between alternatives. Pragmatic approach to cost-effectiveness. 4 Technology Development Pattern Engineering Esoteric Past Experience Technology Craft Systematic Use of Past Experience and Scientific Basis Unorganized Use of Art Past Experience Time 5 Evolution of an Art into an Engineering Discipline The early programmers used an exploratory (also called build and fix) style. – In the build and fix (exploratory) style, normally a `dirty' program is quickly developed. – The different imperfections that are subsequently noticed are fixed. 6 What is Wrong with the Exploratory Style? Can successfully be used for very small programs only. Software Exploratory Engineering Effort, time, cost Machine Program Size 7 What is Wrong with the Exploratory Style? Cont… Besides the exponential growth of effort, cost, and time with problem size: – Exploratory style usually results in unmaintainable code. – It becomes very difficult to use the exploratory style in a team development environment. 8 What is Wrong with the Exploratory Style? Cont… Why does the effort required to develop a product grow exponentially with product size? – Why does the approach completely breaks down when the product size becomes large? 9 An Interpretation Based on Human Cognition Mechanism Human memory can be thought to be made up of two distinct parts [Miller 56]: – Short term memory and – Long term memory. If you are asked the question: ``If it is 10AM now, how many hours are remaining today?" – First, 10AM would be stored in the short-term memory. – Next, a day is 24 hours long would be fetched from the long term memory into short term memory. – Finally, the mental manipulation unit would compute the difference (24-10). 10 Human Cognition Mechanism Short Term Memory Processing Center Long Term Memory Brain 11 Short Term Memory An item stored in the short term memory can get lost: – Either due to decay with time or – Displacement by newer information. This restricts the time for which an item is stored in short term memory to few tens of seconds. – However, an item can be retained longer in the short term memory by recycling. 12 What is an Item? An item is any set of related information. – A character such as `a' or a digit such as `5' can be items. – A word, a sentence, a story, or even a picture can each be a single item. Each item normally occupies one place in memory. When you are able to relate several different items together (chunking): – The information that should normally occupy several places can be stored using only one place in the memory. 13 Chunking If you are given the binary number 110010101001 – It may prove very hard for you to understand and remember. – But, the octal form of 6251 (i.e. (110)(010)(101)(001)) would be easier. – You have managed to create chunks of three items each. 14 Evidence of Short Term Memory Short term memory is evident: – In many of our day-to-day experiences. Suppose, you look up a number from the telephone directory and start dialling it. – If you find the number to be busy, you can dial the number again after a few seconds almost effortlessly without having to look up the directory. But, after several days: – You may not remember the number at all, and would need to consult the directory again. 15 The Magical Number 7 If a person deals with seven or less number items: – These would be easily be accommodated in the short term memory. – So, he can easily understand it. As the number of new information increases beyond seven, – It becomes exceedingly difficult to understand it. 16 Implication in Program Development A small program having just a few variables: – Is within the easy grasp of an individual. As the number of independent variables in the program increases: – It quickly exceeds the grasping power of an individual: Requires an unduly large effort to master the problem. 17 Implication in Program Development Instead of a human, if a machine could be writing (generating) a program, – The slope of the curve would be linear. But, why does the effort-size curve become almost linear when software engineering principles are deployed? – Software engineering principles extensively use techniques specifically to overcome the human cognitive limitations. 18 Principles Deployed by Software Engineering to Overcome Human Cognitive Limitations Mainly two important principles are deployed: – Abstraction – Decomposition 19 Abstraction Simplify a problem by omitting unnecessary details. – Focus attention on only one aspect of the problem and ignore irrelevant details. Suppose you are asked to develop an overall understanding of some country. – No one in his right mind would meet all the citizens of the country, visit every house, and examine every tree of the country, etc. – You would possibly refer to various types of maps for that country. A map, in fact, is an abstract representation of a country. 20 Decomposition Decompose a problem into many small independent parts. – The small parts are then taken up one by one and solved separately. – The idea is that each small part would be easy to grasp and can be easily solved. – The full problem is solved when all the parts are solved. 21 Decomposition A popular way to demonstrate the decomposition principle: – Try to break a bunch of sticks tied together versus breaking them individually. Example use of decomposition principle: – You understand a book better when the contents are organized into independent chapters – Compared to when everything is mixed up. 22 Why Study Software Engineering? (1) To acquire skills to develop large programs. – Exponential growth in complexity and difficulty level with size. – The ad hoc approach breaks down when size of software increases. 23 Why Study Software Engineering? (2) Ability to solve complex programming problems: – How to break large projects into smaller and manageable parts? – How to use abstraction? Also learn techniques of: – Specification, design, user interface development, testing, project management, etc. 24 Why Study Software Engineering? (3) To acquire skills to be a better programmer: Higher Productivity Better Quality Programs 25 Software Crisis Software products: – Fail to meet user requirements. – Frequently crash. – Expensive. – Difficult to alter, debug, and enhance. – Often delivered late. – Use resources non-optimally. 26 Software Crisis (cont.) Hw cost Sw cost 1960 Year 2008 Relative Cost of Hardware and Software 27 Factors Contributing to the Software Crisis Larger problems, Lack of adequate training in software engineering, Increasing skill shortage, Low productivity improvements. 28 Programs versus Software Products Usually small in size Large Author himself is sole user Large number of users Single developer Team of developers Well-designed interface Lacks proper user interface Well documented & user- Lacks proper documentation manual prepared Systematic development Ad hoc development. 29 Types of Software Projects Software products Outsourced projects Indian companies have focused on outsourced projects. 30 Computer Systems Engineering Computer systems engineering: – encompasses software engineering. Many products require development of software as well as specific hardware to run it: – a coffee vending machine, – a mobile communication product, etc. 31 Computer Systems Engineering The high-level problem: – Deciding which tasks are to be solved by software. – Which ones by hardware. 32 Computer Systems Engineering (CONT.) Often, hardware and software are developed together: – Hardware simulator is used during software development. Integration of hardware and software. Final system testing 33 Computer Systems Engineering (CONT.) Feasibility Study Requirements Analysis and Specification Hardware Development Hardware Software Partitioning Software Development Integration and Testing Project Management 34 Emergence of Software Engineering Early Computer Programming (1950s): – Programs were being written in assembly language. – Programs were limited to about a few hundreds of lines of assembly code. 35 Early Computer Programming (50s) Every programmer developed his own style of writing programs: – According to his intuition (exploratory programming). 36 High-Level Language Programming (Early 60s) High-level languages such as FORTRAN, ALGOL, and COBOL were introduced: – This reduced software development efforts greatly. 37 High-Level Language Programming (Early 60s) Software development style was still exploratory. – Typical program sizes were limited to a few thousands of lines of source code. 38 Control Flow-Based Design (late 60s) Size and complexity of programs increased further: – Exploratory programming style proved to be insufficient. Programmers found: – Very difficult to write cost-effective and correct programs. 39 Control Flow-Based Design (late 60s) Programmers found: – programs written by others very difficult to understand and maintain. To cope up with this problem, experienced programmers advised: ``Pay particular attention to the design of the program's control structure.'’ 40 Control Flow-Based Design (late 60s) A program's control structure indicates: – The sequence in which the program's instructions are executed. To help design programs having good control structure: – Flow charting technique was developed. 41 Control Flow-Based Design (late 60s) Using flow charting technique: – One can represent and design a program's control structure. – Usually one understands a program: By mentally simulating the program's execution sequence. 42 Control Flow-Based Design (Late 60s) A program having a messy flow chart representation: – Difficult to understand and debug. 43 Control Flow-Based Design (Late 60s) It was found: – GO TO statements makes control structure of a program messy. – GO TO statements alter the flow of control arbitrarily. – The need to restrict use of GO TO statements was recognized. 44 Control Flow-Based Design (Late 60s) Many programmers had extensively used assembly languages. – JUMP instructions are frequently used for program branching in assembly languages. – Programmers considered use of GO TO statements inevitable. 45 Control-flow Based Design (Late 60s) At that time, Dijkstra published his article: – “Goto Statement Considered Harmful” Comm. of ACM, 1969. Many programmers were unhappy to read his article. 46 Control Flow-Based Design (Late 60s) They published several counter articles: – Highlighting the advantages and inevitability of GO TO statements. 47 Control Flow-Based Design (Late 60s) But, soon it was conclusively proved: – Only three programming constructs are sufficient to express any programming logic: sequence (e.g. a=0;b=5;) selection (e.g.if(c=true) k=5 else m=5;) iteration (e.g. while(k>0) k=j-k;) 48 Control-flow Based Design (Late 60s) Everyone accepted: – It is possible to solve any programming problem without using GO TO statements. – This formed the basis of Structured Programming methodology. 49 Structured Programming A program is called structured – When it uses only the following types of constructs: sequence, selection, iteration 50 Structured Programs Unstructured control flows are avoided. Consist of a neat set of modules. Use single-entry, single-exit program constructs. 51 Structured Programs However, violations to this feature are permitted: – Due to practical considerations such as: Premature loop exit to support exception handling. 52 Structured programs Structured programs are: – Easier to read and understand, – Easier to maintain, – Require less effort and time for development. 53 Structured Programming Research experience shows: – Programmers commit less number of errors: While using structured if-then-else and do-while statements. Compared to test-and-branch constructs. 54 Data Structure-Oriented Design (Early 70s) Soon it was discovered: – It is important to pay more attention to the design of data structures of a program Than to the design of its control structure. 55 Data Structure-Oriented Design (Early 70s) Techniques which emphasize designing the data structure: – Derive program structure from it: Are called data structure- oriented design techniques. 56 Data Structure Oriented Design (Early 70s) Example of data structure-oriented design technique: – Jackson's Structured Programming(JSP) methodology Developed by Michael Jackson in 1970s. 57 Data Structure Oriented Design (Early 70s) JSP technique: – Program code structure should correspond to the data structure. 58 Data Structure Oriented Design (Early 70s) In JSP methodology: – A program's data structures are first designed using notations for sequence, selection, and iteration. – Then data structure design is used : To derive the program structure. 59 Data Structure Oriented Design (Early 70s) Several other data structure-oriented Methodologies also exist: – e.g., Warnier-Orr Methodology. 60 Data Flow-Oriented Design (Late 70s) Data flow-oriented techniques advocate: – The data items input to a system must first be identified, – Processing required on the data items to produce the required outputs should be determined. 61 Data Flow-Oriented Design (Late 70s) Data flow technique identifies: – Different processing stations (functions) in a system. – The items (data) that flow between processing stations. 62 Data Flow-Oriented Design (Late 70s) Data flow technique is a generic technique: – Can be used to model the working of any system. not just software systems. A major advantage of the data flow technique is its simplicity. 63 Data Flow Model of a Car Assembly Unit Engine Store Door Store Partly Assembled Chassis with Car Engine Fit Fit Fit Paint and Car Engine Doors Wheels Assembled Car Test Chassis Store Wheel Store 64 Object-Oriented Design (80s) Object-oriented technique: – An intuitively appealing design approach: – Natural objects (such as employees, pay-roll- register, etc.) occurring in a problem are first identified. 65 Object-Oriented Design (80s) Relationships among objects: – Such as composition, reference, and inheritance are determined. Each object essentially acts as – A data hiding (or data abstraction) entity. 66 Object-Oriented Design (80s) Object-Oriented Techniques have gained wide acceptance: – Simplicity – Reuse possibilities – Lower development time and cost – More robust code – Easy maintenance 67 Evolution of Design Techniques Object-Oriented Data flow-based Data structure-based Control flow-based Ad hoc 68 Evolution of Other Software Engineering Techniques The improvements to the software design methodologies – are indeed very conspicuous. In additions to the software design techniques: – Several other techniques evolved. 69 Evolution of Other Software Engineering Techniques – lifecycle models, – specification techniques, – project management techniques, – testing techniques, – debugging techniques, – quality assurance techniques, – software measurement techniques, – CASE tools, etc. 70 Differences between the exploratory style and modern software development practices Use of Life Cycle Models Software is developed through several well- defined stages: – requirements analysis and specification, – design, – coding, – testing, etc. 71 Differences between the exploratory style and modern software development practices Emphasis has shifted – from error correction to error prevention. Modern practices emphasize: – detection of errors as close to their point of introduction as possible. 72 Differences between the exploratory style and modern software development practices (CONT.) In exploratory style, – errors are detected only during testing, Now, – focus is on detecting as many errors as possible in each phase of development. 73 Differences between the exploratory style and modern software development practices (CONT.) In exploratory style, – coding is synonymous with program development. Now, – coding is considered only a small part of program development effort. 74 Differences between the exploratory style and modern software development practices (CONT.) A lot of effort and attention is now being paid to: – Requirements specification. Also, now there is a distinct design phase: – Standard design techniques are being used. 75 Differences between the exploratory style and modern software development practices (CONT.) During all stages of development process: – Periodic reviews are being carried out Software testing has become systematic: – Standard testing techniques are available. 76 Differences between the exploratory style and modern software development practices (CONT.) There is better visibility of design and code: – Visibility means production of good quality, consistent and standard documents. – In the past, very little attention was being given to producing good quality and consistent documents. – We will see later that increased visibility makes software project management easier. 77 Differences between the exploratory style and modern software development practices (CONT.) Because of good documentation: – fault diagnosis and maintenance are smoother now. Several metrics are being used: – help in software project management, quality assurance, etc. 78 Differences between the exploratory style and modern software development practices (CONT.) Projects are being thoroughly planned: – estimation, – scheduling, – monitoring mechanisms. Use of CASE tools. 79 Software Life Cycle Software life cycle (or software process): – Series of identifiable stages that a software product undergoes during its life time: Feasibility study Requirements analysis and specification, Design, Coding, Testing maintenance. 80 Life Cycle Model A software life cycle model (or process model): – a descriptive and diagrammatic model of software life cycle: – identifies all the activities required for product development, – establishes a precedence ordering among the different activities, – Divides life cycle into phases. 81 Life Cycle Model (CONT.) Several different activities may be carried out in each life cycle phase. – For example, the design stage might consist of: structured analysis activity followed by structured design activity. 82 Why Model Life Cycle ? A written description: – Forms a common understanding of activities among the software developers. – Helps in identifying inconsistencies, redundancies, and omissions in the development process. – Helps in tailoring a process model for specific projects. 83 Why Model Life Cycle ? Processes are tailored for special projects. – A documented process model Helps to identify where the tailoring is to occur. 84 Life Cycle Model (CONT.) The development team must identify a suitable life cycle model: – and then adhere to it. – Primary advantage of adhering to a life cycle model: Helps development of software in a systematic and disciplined manner. 85 Life Cycle Model (CONT.) When a program is developed by a single programmer --- – he has the freedom to decide his exact steps. 86 Life Cycle Model (CONT.) When a software product is being developed by a team: – there must be a precise understanding among team members as to when to do what, – otherwise it would lead to chaos and project failure. 87 Life Cycle Model (CONT.) A software project will never succeed if: – one engineer starts writing code, – another concentrates on writing the test document first, – yet another engineer first defines the file structure – another defines the I/O for his portion first. 88 Life Cycle Model (CONT.) A life cycle model: – definesentry and exit criteria for every phase. – A phase is considered to be complete: only when all its exit criteria are satisfied. 89 Life Cycle Model (CONT.) The phase exit criteria for the software requirements specification phase: – Software Requirements Specification (SRS) document is complete, reviewed, and approved by the customer. A phase can start: – only if its phase-entry criteria have been satisfied. 90 Life Cycle Model (CONT.) It becomes easier for software project managers: – to monitor the progress of the project. 91 Life Cycle Model (CONT.) When a life cycle model is adhered to, – the project manager can at any time fairly accurately tell, at which stage (e.g., design, code, test, etc. ) of the project is. – Otherwise, it becomes very difficult to track the progress of the project the project manager would have to depend on the guesses of the team members. 92 Life Cycle Model (CONT.) This usually leads to a problem: – known as the 99% complete syndrome. 93 Life Cycle Model (CONT.) Many life cycle models have been proposed. We will confine our attention to a few important and commonly used models. – Classical waterfall model – Iterative waterfall, – Evolutionary, – Prototyping, and – Spiral model 94 Summary Software engineering is: – Systematic collection of decades of programming experience – Together with the innovations made by researchers. 95 Summary A fundamental necessity while developing any large software product: – Adoption of a life cycle model. 96 Summary Adherence to a software life cycle model: – Helps to do various development activities in a systematic and disciplined manner. – Also makes it easier to manage a software development effort. 97

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