berrached::cs3320::ch131 implementation phase chapter 13 classical & object-oriented software...

Berrached::CS3320::Ch13 1

Implementation Phase

Chapter 13

Classical & Object-Oriented Software Engineering by Stephen R. Schach


Implementation Phase

• Aim: to translate the detailed design into code.• Programming-in-the-many: Product is

implemented by a team of programmers• All working at same time on different components

of the product.


Outline

• Choice of programming language• Good Programming Languages• Testing Techniques


Choice of a Programming Language• Language usually specified in contract by client.• If not, choice should be based on:

– cost-benefit analysis – COBOL: for data processing

– Object-Oriented Languages

– 4th generation Languages: e.g. SQL, DB2, Oracle, PowerBuilder

• Higher-level: each line equivalent to 30-50 line of machine code

• ease in programming, but slower

• mostly for data processing tasks


Good Programming Practice

• Use of consistent and meaningful variable name– Meaningful to future maintenance programmer

– Consistent to aid maintenance programmer

Example:– Module contains a variable to represent

maximum, minimum, and average temperatures:

• MaxFr: too ambiguous

• frequencyMax, minFreq: not consistent

• maxFrequency, minFreqency, avgFrequency

– Companies usually have their own internal conventions.


Good Programming Practice CNTD

• Self-documenting code: code can be understood without the aid of comments:– very rare

• Key question:– Can module be understood easily and unambiguously by

• SQA team

• maintenance programmers

• all others who have to read code

– E.g. xCooddinateOfPositionOfRobotArm

• abbreviate to xCoord


Prologue Comments• Mandatory at top of every single module

– module name– brief description of what module does– programmer’s name– date module was coded– date it was approved and by whom– Module parameters– Variable name, alphabetically and their uses– files accessed and updated by module– module I/O– error handling capabilities– name of file of test data– list if modifications made, when, by whom, approved by whom– known faults, if any


Other Comments

• In-line comments needed to explain code

Fallacy:– Comment are only needed when code is written in non-

obvious way, or makes use of subtle aspect of language

– If that is the case, re-code in clearer way

• Code layout for increased readability– use indentation

– use blank lines


Nested if Statements


Nested if Statements CNTD



• Combination of if-if and if-else-if statements usually difficult to read

• simplify by making use of fact that if-if combinationif <condition1>

if <condition2>

is frequently equivalent to single condition

if <condition1> && <condition2>

• Note: if programming language supports “short-circuit” evaluation of logical operations, they can always be equivalent.



Some basic rules:– if conditions are interdependent, use if-else statement

instead of a sequence of if statements

– Don’t forget the final else part

– Avoid if-if and if-else-if statements by combining conditions using the && operator

– Rule of thumb: if-statements nested to depth greater than three should be avoided as poor programming practice


Programming Standards• Standards are difficult to enforce• Can be both blessing and curse

– setting limits of module size

• Examples of good standards– documentation standards– program layout– naming standards– “ nesting of if-statements should not exceed a depth of 3,

except with prior approval from team leader”– “Use of goto should be avoided. However, with prior

approval from team leader, a forward goto many be used for error handling”


Module Testing

• After preliminary testing by programmer, each module is handed over to SQA group for formal testing.

• How to methodically test a module?


Module Test Case Selection

• Worst way- random testing• Need systematic way to construct test cases

Two extremes to testing:1. Test to specifications (also called black-box, data

driven, functional, or input/output driven testing).

• Ignore code. Use spec. document to select test cases

2. Test to code (also called glass-box, logic-driven, structured, or path-oriented testing)

• Ignore specifications. Use code to select test cases


Feasibility Of Testing To Specs

Example:– Specification for a data processing product include 5

commissions and 7 types of discount

– 35 test cases

• Suppose specs include 20 factors, each taking 4 values– 420 or over 1 trillion test cases

– if each takes 30 seconds to run, running all test cases takes > 1 million years!!

• Combinatorial explosion makes exhaustive testing to specification unfeasible.


Feasibility Of Testing To CodeEach path through module must be executed at least

once– Combinatorial explosion: flow chart has over 1012

different paths


Feasibility Of Testing To Code CNTD

• Can exercise every path without detecting every fault

Example:

if ( (x+y+z)/ 3 ==x)

cout <<“x, y, z are equal”<<endl;

else

cout <<“x, y, z are not equal”<<endl;

Test case 1: x=1, y=2, z=3

Test case 2: x=2, y=2, z=2


Feasibility Of Testing To Code CNTD

• Path can be tested only if it is presentExample 1:

if (d==0)

zeroDivisionRoutine();

else

x = n/d;

Example 2:

x = n/d;


Coping With The Combinatorial Explosion

• Exhaustive testing (to specs or to code) is not feasible

Art of testing:

• Small, manageable set of test cases to

– maximize chances of detecting faults, while

– minimizing chances of wasting test cases

• Every test case must be designed to detect previously undetected faults

• Methods that will high-light as many faults as possible

– First black-box test cases

– Then glass-box methods


Black-Box Module Testing

• Equivalence Testing

Example:– Specs for DBMS state that product must handle any

number of records between 1 and 16,000

– if system works for any one test in range [1..16,000], then it will probably work for any test case in range

• range [1..16,00] constitutes one equivalence class

• Any one member is as good a test case as any other member of the class.


Equivalence Testing CNTD

• Range [1..16,000] defines three difference equivalence classes:– Equivalence Class 1: Fewer than 1 record

– Equivalence Class 2: between 1 and 16,000 records

– Equivalence Class 3: More than 16,000 records

• Boundary Analysis:– Selecting test case on or just to one side of boundary of

equivalence class increases probability of detecting faults


Equivalence Testing & Boundary Analysis• DBMS Example:

– Test Case 1: 0 record: (member of class 1 & adjacent to boundary value)

– Test Case 2: 1 record (Boundary value)

– Test Case 3: 2 records (Adjacent to boundary value)

– Test Case 4: 8349 records (member of class 2)

– Test Case 5: 15,999 recs (Adjacent to Boundary value)

– Test Case 6: 16,000 recs (Boundary value)

– Test case 7: 16,001 recs (Adjacent to Boundary value)


Black-Box Testing Methods CNTD

Functional Testing• Test for each item of functionality• Example:

– module authenticates user login

– Module computes some arithmetic function

• Weakness:– Functionality may span several modules


Glass-Box Module Testing Methods

Statement Coverage• Series of test cases to check every statement• CASE tools needed to keep track• Weakness:

– Branch statements

if (S > 1 && t = 0) // && should have been ||

X= 8;

Test case: S=2, t=0

Both statements can be executed without fault showing up



Branch Coverage• Series of tests check all branches.• CASE tool needed

Path Coverage• Most powerful form of Glass box testing• Weakness: with loops, number of paths very

large , can be infinite• Want weaker condition than all paths but which

shows up more coverage than branch coverage



Path Coverage (continued)

Linear code sequences:• Identify set points L from which control flow may

jump, including entry and exit points– e.g.

• Restrict test cases to paths that begin and end with elements of L

• Uncovers many faults without testing every path.


Glass-Box Testing Methods CNTDAll-definition-use- path coverage

• Each occurrence of variable, zz say, is labeled either as – definition of variable:

e.g. zz=1 or read(zz)

– or use of variable:

e.g. Y = zz + 1 or if (zz > 0) ….

• Identify all paths from definition of variable to use of that variable– can be done by automated tool

• Set up a test case for each such path.


Glass-Box Testing Methods CNTD

All-definition-use- path coverage CNTD

• Disadvantages:– upper bound on number of paths is 2d, where d

is number of branches• In practice

– Actual number of paths is proportional to d


Glass-Box Testing Methods CNTD

Infeasible Code• May not be possible to test specific statement

because there is an infeasible path ("dead code")

if ( k < 2) {

if ( k > 3)

{ // dead code ….

• Dead code is frequently an indication of a fault


Glass-Box Testing -- Quality Assurance• Module m1 is more "complex" than module "m2"

=> m1 is likely to have more faults

• Software complexity– highlights modules most likely to have faults

• Unreasonably high complexity

=> re-design and re-code


Measures of Complexity

Lines of code– simplest measure of complexity– underlying assumption: constant probability p

that a line of code contains fault.

• Number of faults is related to size of product as a whole



Cyclomatic Complexity

• Essentially number of decisions (branches) in module

• Easy to compute• Good measure of faults



Software Science Metrics• Based on number of operators and operands in

module• Problem with cyclomatic and software science

– Being challenged theoretically and experimentally

– The both have high correlation wit LOC

• Several experiments have shown that LOC is as good predictor of fault rate as any other metrics

• Note: LOC is poor metric of productivity


Code Walkthrough and Inspections• Done by SQA team

– group of 4-6 members

– "walkthrough" code

– detect faults (no correction)

• Leads to rapid and thorough fault detection

• Experiments have shown that they are at least as effective in detecting faults as black-box and glass-box testing techniques.


CLEANROOM TESTING

• Incorporates several SW development techniques:– incremental process model

– Formal techniques for specification and design

– non-execution based testing: walkthroughs and inspections

• A module is not compiled until it has passed inspection


CLEANROOM TESTING

• 1820 lines of FoxBASE (U.S. Naval Underwater Systems Center, 1992)– 18 faults detected by "functional verification"

• based correctness proving techniques

– 19 faults detected in walkthroughs before compilation

– NO compilation errors

– NO execution errors


Approaches to Real Time Testing• Non-execution based

– Structure analysis techniques– deadlock detection methods– formal methods for modeling system behavior

that can take synchronization into consideration– e.g. PetriNets


Approaches to Real Time Testing (CNTD)

• Execution Based– Systematic testing

• all possible ordering of inputs

• often impossible (combinatorial explosion)

– Simulation is the most important testing method for real-time systems

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