Introduction SWE 619 Why Is Building Good Software

Introduction SWE 619

Why Is Building Good Software Hard? n Large software systems enormously complex q n People expect software to be malleable q n After all, it’s “only software” We are always trying to do new things with software q n Millions of “moving parts” Relevant experience often missing Software engineering is about: q q q Managing complexity Managing change Coping with potential defects n Customers, developers, environment, software

Decomposition and Abstraction Decomposition – divide and conquer n Abstraction helps to decompose productively n Abstraction changes the level of details to be considered n q q A many-to-one mapping “abstracts” from “irrelevant” details

Decomposition and Abstraction n Decomposition q q q n Abstraction q q n When to decompose Identifying components Modeling components Abstraction by parameterization Abstraction by specification Pre-conditions and Post-conditions q University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Decomposition n Separable subproblems q q Each subproblem is at the same level of detail Each subproblem can be solved independently The solutions to the subproblems can be combined to solve the original problem University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Decomposition n n Large problems can be tackled with “divide and conquer” Decompose the problem so that: q Each subproblem is at (roughly) the same level of detail q Each subproblem can be solved independently q The solutions to the subproblems can be combined to solve the original problem Advantages q Different people can work on different subproblems q Parallelization may be possible q Maintenance is easier Disadvantages q The solutions to the subproblems might not combine to solve the original problem q Poorly understood problems are hard to decompose q University of Toronto Department of Computer Science © 2001, Steve Easterbrook

How to Decompose n Step 1: Identify Components q a good decomposition minimizes dependencies between components n n q information hiding n n coupling - a measure of inter-component connectivity cohesion - a measure of how well the contents of a component go together having modules keep their data private provide limited access procedures this reduces coupling Step 2: Model the components q University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Abstraction n n Abstraction is the main tool used in reasoning about software Why? It allows you to: q q ignore inconvenient detail treat different entities as though they are the same simplify many types of analysis University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Using Abstraction n Abstraction can help with Decomposition q q n e. g. To manage the economy, try focusing on some abstracted features such as inflation, growth, GDP, etc. Abstraction allows us to ignore inconvenient details In programming: q Abstraction is the process of naming compound objects and dealing with them as single entities n n (i. e. ignoring their details) Abstraction doesn’t solve problems… q q …but it allows us to simplify them University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Abstraction mechanisms n Two abstraction mechanisms: q q Abstraction by parameterization abstracts from the identity of the data by replacing them with parameters. It generalizes modules so that they can be used in more situation Abstraction by specification abstracts from the implementation details (how the module is implemented) to the behavior users can depend on (what the module does). It isolates modules from one another’s implementations.

Abstraction by Parameterization n n The program fragment: q x * x - y * y q computes the difference of the squares of two specific variables, x and y. The abstraction: q int squares (int x, int y) { q return(x * x - y * y); q } n n n describes a set of computations which act on any two (integer) variables tocompute the difference of their squares Note: locally the variables are called x and y for convenience The specific computation: q result = squares (big, small); n q uses the abstraction ‘squares’ on two specific variables (‘big’ and ‘small’) University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Abstraction by Specification n Abstraction by parameterization… q q n …allows us to express infinitely many computations …but does not tell us about the intention of those computations We need to capture the intention q e. g. consider what is true before and after a computation Before Unsorted Function for Sorting arrays Array n n After Sorted array We can abstract away from a computation (or a plan, program, function, etc) by talking about what it achieves Specification: this function can be used whenever we have an array. After it is applied, the array will be sorted into ascending order q University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Pre-conditions and Postconditions n The two forms of abstraction are complementary q q n parameterization allows us to perform a computation on any arbitrary variables (values) specification allows us to ignore how it is done Unfortunately… q only abstraction by parameterization is built into our programming languages n as function (procedure) definitions We can overcome this using comments: int strlen (char s[]) { /* precondition: s must contain a character array delimited by the null character; postcondition: returns the length of s as an integer; */ int length = 0; while (s[length]) length++; return(length); } n q University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Kinds of Abstractions n n Procedural abstraction allows us to introduce new operations Data abstraction allows us to introduce new types of data objects Iteration abstraction allows us to iterate over items in a collection without revealing details of how the items are obtained Type hierarchy allows us to abstract from individual data types to families of related types

Summary 1 n n Decomposition allows us to simplify difficult design tasks A good decomposition q minimizes coupling between components q maximizes cohesion within components q permits information hiding Methods provide… q … techniques for decomposing problems q … notations for describing the components Abstraction allows us to ignore detail q by parameterization: allows us to describe and name sets of computations q by specification: allows us to ignore how the computation is done q University of Toronto Department of Computer Science © 2001, Steve Easterbrook

Summary 2 n n Program decomposition based on abstraction Procedural and iteration abstractions are valuable Data abstraction provides the primary organizational tool in the programming process Goal for various abstractions: q q q What they are? How to specify their behavior? How to implement them in Java?