CS160 Exploring Computer Science

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CS160 Exploring Computer Science
Review of Chapters 5, 6 7

• I think there is a world market for maybe five
  computers.
• --- T.J. Watson, IBM Chairman, 1943

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Chapter 5 Programming Languages

• Language generations evolution
• The four programming paradigms
• Traditional programming concepts
• Procedural Units
• Program Translation

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Programming Language Toolset
C
If all you have is a hammer, then everything
looks like a nail.
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Language Generations
Five Generations Procedural Languages 1GL
Machine language 2GL Assembly language 3GL
High-level language Nonprocedural Languages 4GL
Very high-level language 5GL Natural language

• Low levels closer to binary format
• High levels - closer to human language

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Machine Language

• Written in strings of 0 and 1
• Only language the computer understands
• All other programming languages are translated to
  machine language
• Computer dependent
• Recall that CISC instructions wont work for a
  RISC architecture

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Assembly Language

• Uses Mnemonic codes
• Assigns Names for memory locations
• Depends on the Computer
• Needs an Assembler to translates from Assembly to
  machine language so the machine can execute the
  program

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High Level Languages 3GL

• Identify a collection of high-level primitives
• e.g. loops and selection constructs
• Think and express concepts at a higher level of
  abstraction than machine language
• Implement translation of such high-level
  primitives into machine language using an
  intermediary (Compilers)

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High Level Languages 3GL

• High level languages were invented to
• break away from machine-dependence
• allow the expression of abstract concepts
• Compilers and interpreters are software tools
  that translate high-level source code (text) into
  machine language (binary)

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Programming Paradigms

• Procedural (Imperative)
• Cobol, Fortran, C, Pascal
• Focused at expressing an algorithm
• Declarative
• Prolog, SQL
• Focused at expressing the solution to a problem
• Functional
• Scheme, Lisp, ML
• Focused at identifying functional components
• Object-Oriented
• Smalltalk, C, Java
• Programs are sets of cooperating components that
  contain both data and operations

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Evolution of Programming Paradigm
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Traditional Programming Concepts (TPC)

• Variables and Data Types
• Describe data and data format
• Data Structures
• Complex data types
• Constants and Literals
• Using a value directly
• Assignment Statements
• Assign values to variables
• Assign result of an evaluation to a variable
• Control Statements
• Selection
• Loop

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Procedural Units

• Procedure is an abstract modular tool that can be
  used by several different program units.
• A Procedure needs to be defined first, and then
  invoked via procedure call wherever needed
• Control transfers from current statement in the
  program unit to the procedure unit by means of a
  JUMP control at the time of procedure call
• Control is returned to the original program unit
  once the procedure unit has finished executing
• Procedures have their own set of local variables
• Values from one program unit to another procedure
  unit can be passed via parameters declared for
  that procedure unit
• Reading Chapter 5 Section 5.3

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Procedural Units Control transfer
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Procedures vs. Functions

• Function is similar to Procedure except that a
  value is transferred back to the calling program
  as the value of the function
• Procedures do not pass back a return value and
  preserve the calling environment
• Functions pass back a return value that can be
  used by the calling program whenever needed

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Grammar

• Every language has a distinct grammar, which is a
  set of rules for creating expressions in the
  language
• (define (sum n m) ( n m)) in Scheme
• x n m in C
• The syntax of a language consists of the grammar
  combined with an alphabet
• Most languages use the normal alphabet, e.g.
  Scheme
• Some languages use special symbols, e.g. APL

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Program Translation

• The steps completed by a compiler are
• Lexical Analysis identify the individual tokens
  in the language statements reading symbol by
  symbol
• Syntax and Semantics Analysis (a.k.a Parsing)
  Build a parse tree by reading the tokens analyzed
  by Lexical analyzer and Identify the intent of
  the program statements
• Code Generation Produce machine language
  instructions

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Program Translation Process
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Program Translation Parsing

• Early parsers required fixed-format for source
  code
• Modern 3GL are free-format languages
• Example
• If cost lt cashOnHand pay cash else use
  credit card
• is understood by the modern parsers correctly,
  but, makes it harder to read for humans, so, we
  write it as
• If (cost lt cashOnHand)
• pay cash
• Else
• use credit card
• Semi-colons are typically used to indicate end of
  each statement
• Key words are defined which cannot be used in
  programs to represent anything other than what
  they are defined for

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Choosing a Language

• Choose based on
• What is available
• Required interface
• What do you know best?
• More importantly Which language lends itself to
  the problem to be solved?

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4GLVery High-Level Languages

• Programmer specifies the desired results the
  language develops the solution
• Many times more productive with a 4GL than a
  procedural language
• Query Languages
• Retrieve information from databases
• Easy to learn and use

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5GL Natural Languages

• Resemble natural or spoken English
• Translates human instructions into code the
  computer can execute

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OOP Object-Oriented Programming

• Object
• Self-contained unit of data and instructions
• Includes
• Related facts (data)
• Related functions (instructions to act on that
  data)
• Example
• Object cat
• Data feet, nose, fur, tail
• Functions eat, purr, scratch, walk
• Cat Kitty, Susan

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Summary

• All programs must be translated into machine
  language in order to run
• There are four identifiable programming
  paradigms, each with its own special features
• High level languages provide machine independence
  and better productivity for developers and need
  some intermediary like compliers to translate to
  machine language
• Languages are specified using grammars. This
  allows compilers to translate the programs
  unambiguously by creating appropriate parse trees
• Traditional programming concepts include
• Variables, Data Types, Data Structures
• Assignment Statements
• Control Statements like Selection and Repetition

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Chapter 6 Software Engineering

• Software Engineering (SE) has unique features
• SE is a non-traditional discipline
• SE should be
• Measurable, predictable, repeatable
• The System Development Life Cycle (SDLC)
• Waterfall Model
• Incremental Development Model
• Program verification and validation
• Testing and debugging techniques

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Software Engineering is non-traditional

• Software Engineering lacks the scientific
  foundation found in traditional engineering
• Traditional engineering is based on scientific
  laws of physics, chemistry, and other fields
• Software engineering has no such corresponding
  fundamental science

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Software Engineering Studies

• Practicum
• Some software engineers focus their efforts on
  developing methodologies that can help
  contemporary computer professionals
• Theory
• Some software engineers focus their efforts on
  finding underlying principles upon which future
  methodologies can based

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SDLC

• Software Development Life Cycle
• The details of the process used to develop
  software, e.g. a subset of the SLC
• Often consists of these steps
• Analysis (problem definition and solution
  statement)
• Design (algorithm development)
• Implementation (creating a program)
• Testing (making sure the program works)

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Development ApproachWater-Fall Model (Old)
Analysis
Design
Implement
Test

• Requires that each stage be entirely complete
  before beginning next stage.

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Traditional SDLC Analysis

• Analysis
• Identify the needs of the user
• Interviews or market analysis
• Establish functional specifications
• What is the input data?
• What is the required output?
• What are the performance requirements?
• Analysis focuses on what needs to happen and sets
  the goals of the system

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Defining Diagram Table

• A table that describes the basic operations of
  your program
• Processing details are not shown
• These are documentation and thinking tools for
  humans, not precise specifications

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Traditional SDLC Design

• Design
• What steps are required to produce the output
  from the specified input?
• What are the algorithms that will be used?
• How will the process be broken down into smaller
  steps?
• Design focuses on how the system will accomplish
  the specified goals and on the structure of the
  system

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Modularization

• Jargon for dividing a large program into smaller,
  more manageable pieces called routines,
  functions, procedures, and many other names
• Requires understanding how to break a large task
  into smaller tasks

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Structure Charts

• A structure chart is a graphical way of
  representing a functional design
• The chart shows the structure or hierarchy of
  your program, i.e. which functions call which
  other functions
• All functions in the program are listed

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Structure Charts

• Design process is top-down
• Processes on the upper levels call lower level
  processes never the other way around
• Good function names often will be a verb followed
  by a noun
• Get_Input
• Calculate_Invoice

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Coupling Control and Data

• Links and dependencies between modules
• Control coupling
• when one module passes control to another
• Examples function call, return
• Data coupling
• sharing of data between modules.
• Examples function parameters, return values

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Object Oriented Approach

• Minimizing Data Coupling is inherent in OO
  approach
• Collect routines, methods that manipulate a
  particular data item into a single module viz.,
  the object
• Inter module coupling then becomes inter object
  communication, implemented via control coupling

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Cohesion

• Internal binding within function, i.e. degree of
  relatedness of a modules internal parts.
• Logical cohesion
• Internal elements perform activities that are
  logically similar. (E.g.. I/O function)
• Functional cohesion
• all parts or elements are geared towards the same
  single activity
• Aim high intra-module cohesion

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Golden Rule 1
Design Top-Down, but always build Bottom-Up.

• Code and test the simplest components first.
• Test each component before using them to make
  sure they work
• Then use those components to build more complex
  components.

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Golden Rule 2
Modules in a well-structured program are highly
cohesive and loosely coupled.

• The size of the data coupling corresponds roughly
  to the level of the module in the hierarchy.

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Dataflow Diagrams (DFD)

• Pictorial representation of data paths
• origin (source)
• destination (sink, storage)
• processing points (location of data manipulation,
  modules)

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Dataflow diagrams (DFD)

• Emphasize the data (information) to flow through
  system.
• (rather than procedures to be executed)
• By following data paths, discover where data
  units are merged, split, or altered.

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Traditional SDLC Implementation

• Implementation
• Implementation consists creating programs to run
  in a specific computer environment
• Programming language
• Operating system
• Hardware components
• Users

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Traditional SDLC Testing

• Testing
• Testing is done to ensure that the results is
  what is needed
• Verification testing is done to ensure that the
  program adheres to the functional specifications
• Validation testing is done to ensure that the
  functional specifications meet the needs of the
  user

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Testing

• Glass Box testing techniques utilize a knowledge
  of program structure and design to identify
  specific conditions to be tested
• Black Box testing techniques focus on input and
  output, and ignore the internal details of how
  the program functions

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Documentation

• System Documentation explains the internal
  technical details of how the software is
  implemented so that it can be maintained later in
  its life cycle
• User Documentation explains the features of the
  software from a user perspective to serve as a
  manual for the non-technical user.

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Non-Traditional SDLC

• Several attempts have been made to address
  problems perceived with the traditional system
  development processes
• Incremental Development
• Rapid Prototyping
• Computer-Aided Software Engineering

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Incremental Development Model
Analysis
Design
Implement
Test

• Increments from simplified version with limited
  functionality to complete system.
• At each stage prototype.

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Summary

• Modularity is crucial for developing large
  software projects
• Structure charts and dataflow diagrams are useful
  design tools
• Design top-down, but build bottom-up
• Build incrementally with prototypes
• Well-structured programs are highly cohesive, and
  loosely coupled.

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Chapter 7 Data Structures

• What is ADT?
• Why introduce data structures?
• What is a pointer?
• The common data structures are
• Arrays
• Linked Lists
• Queues
• Stacks
• Trees

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Data Structures and Programming

• Data structures is concerned with the
  representation and manipulation of data
• All programs manipulate data
• So, all programs represent data in some way
• Data manipulation requires an algorithm
• Algorithm design methods are needed to develop
  programs that do the data manipulation
• The study of data structures and algorithms is
  fundamental to Computer Science

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ADT Abstract Data Types

• Memory cells are the basic storage units
• Memory cells can be conceptually organized into
  clusters with specific forms and shapes that we
  as programmers find easier to handle
• Example Instead of giving your scores for the
  course as a string of numbers in the grade book,
  it is organized into a table with headers and
  cell entries for readability
• ADT is a mathematical model with a collection of
  operation defined on that model

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Static vs. Dynamic Data

• The shape or size or volume of data can be fixed
  (static) or can change (dynamic) over time
• Example Registrars Student list at PCC is a
  dynamic data type as students can add/drop
  courses as well as, the number of students
  enrolling is not a fixed quantity at any given
  time.
• We must define data types that should allow for
  such flexibility

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What is a Data Structure?

• A data structure is a set of variables,
  constants, and literals that are organized in a
  particular manner for ease of use and
  manipulation
• Some forms of organization are very common, and
  have specific names, e.g.
• Arrays
• Lists
• Queues
• Stacks
• Trees

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Summary

• Data can be organized in a variety of ways that
  support the development of algorithms arrays,
  linked lists, stacks, queues and trees
• Data structures are ultimately laid out in linear
  memory cells
• Pointers are a useful technique for creating data
  structures that do not require contiguous memory