Software EngineeringSoftware Engineering

Testing (Concepts and Principles)

ObjectivesObjectives

To introduce the concepts and principles of testing

To summarize the debugging process

To consider a variety of testing and debugging methods

analysis design code test

Software TestingSoftware Testing

Narrow View: Testing is the process of exercising a program with the specific

intent of finding errors prior to delivery to the end user. A good test case is one that has a high probability of an as-yet-

undiscovered error A successful test is one that uncovers an as-yet-undiscovered

error

Broad View: Testing is the process used to ensure that the software conforms

to its specification and meets the user requirements Validation “Are we building the right product?” Verification “Are we building the product right?” Takes place at all stages of software engineering

What Testing ShowsWhat Testing Shows

errorserrors

requirements conformancerequirements conformance

performanceperformance

an indicationan indicationof qualityof quality

Testing PrinciplesTesting Principles

All tests should be traceable to customer requirements

Tests should be planned long before testing begins

80% of errors occur in 20% of classes

Testing should begin “in the small” and progress toward testing “in the large”

Exhaustive testing is not possible

To be most effective, testing should be conducted by an independent third party

Who Tests the Software?Who Tests the Software?

developerdeveloper independent testerindependent tester

Understands the system but will test “gently” and is driven by delivery

Must learn about the system but will attempt to break it and is driven by quality

Software TestabilitySoftware Testability

Software that is easy to test:1. Operability —“the better it works, the more efficiently it can be tested”.

Bugs are easier to find in software which at least executes

2. Observability—“what you see is what you test”. The results of each test case are readily observed

3. Controlability—“the better we can control the software, the more testing can be automated and optimized”. Easier to set up test cases

4. Decomposability—“by controlling the scope of testing, we can more quickly isolate problems and perform smarter retesting”. Testing can be targeted

5. Simplicity—“the less there is to test, the more quickly we can test it”. Reduce complex architecture and logic to simplify tests

6. Stability—“the fewer the changes the fewer the disruptions to testing”. Changes disrupt test cases

7. Understandability—“the more information we have the smarter we will test”

Test Case DesignTest Case Design

A test case is a controlled experiment that tests the system

Process:Objectives—to uncover errors

Criteria—in a complete manner

Constraints—with a minimum of effort and time

Often badly designed in an ad hoc fashion

“Bugs lurk in corners and congregate at boundaries.” Good test case design applies this maxim

Exhaustive Testing (infeasible)Exhaustive Testing (infeasible)

There are 10^14 possible paths! If we execute one test per millisecond, it would take 3170 years to test this program

Two nested loops containing four if..then..else statements. Each loop can execute up to 20 times

Selective Testing (feasible)Selective Testing (feasible)

Test a carefully selected execution path. Cannot be comprehensive

Testing MethodsTesting Methods

1. Black Box: examines fundamental interface aspects without regard to internal structure

2. White (Glass) Box: closely examine the internal procedural detail of system components

3. Debugging: fixing errors identified during testing

Methods

Strategies

white-boxmethods

black-box methods

[1] White-Box Testing[1] White-Box Testing

Goal: Ensure that all statements

and conditions have been executed at least once

Derive test cases that:1. Exercise all independent

execution paths

2. Exercise all logical decisions on both true and false sides

3. Execute all loops at their boundaries and within operational bounds

4. Exercise internal data structures to ensure validity

Why Cover all Paths?Why Cover all Paths?

Logic errors and incorrect assumptions are inversely proportional to the probability that a program path will be executed.

We often believe that a logical path is not likely to be executed when, in fact, it may be executed on a regular basis

Typographical error are random; it is likely that untested paths will contain some

Basis Path TestingBasis Path Testing

1. Provides a measure of the logical complexity of a method and provides a guide for defining a basis set of execution paths

2. Represent control flow using flow graph notationNodes represent processing, arrows represent control flow

Sequence

IfWhile

Cyclomatic ComplexityCyclomatic Complexity

2. Compute the cyclomatic complexity V(G) of a flow graph G: Number of simple predicates

(decisions) + 1 or

V(G) = E-N+2 (where E are edges and N are nodes) or

Number of enclosed areas + 1

In this case V(G) = 4

Cyclomatic Complexity and ErrorsCyclomatic Complexity and Errors

A number of industry studies have indicated that the higher V(G), the higher the probability of errors

V(G)V(G)

modulesmodules

modules in this range aremodules in this range are more error pronemore error prone

Basis Path TestingBasis Path Testing

3. V(G) is the number of linearly independent paths through the program (each has at least one edge not covered by any other path)

4. Derive a basis set of V(G) independent paths Path 1: 1-2-3-8 Path 2: 1-2-3-8-1-2-3 Path 3: 1-2-4-5-7-8 Path 4: 1-2-4-6-7-8

5. Prepare test cases that will force the execution of each path in the basis set

1

2

34

5 6

7

8

Basis Path TipsBasis Path Tips

You don’t need a flow graph, but it helps in tracing program paths

Count each simple logical test, compound tests (e.g. switch statements) count as 2 or more

Basis path testing should be applied to critical modules only

When preparing test cases use boundary values for the conditions

Other White Box MethodsOther White Box Methods

Condition Testing: exercises the logical (boolean) conditions in a program

Data Flow Testing: selects test paths according to the location of the definition and use of variables in a program

Loop Testing: focuses on the validity of loop constructs

Loop TestingLoop Testing

Nested Nested LoopsLoops

Concatenated Concatenated LoopsLoops Unstructured Unstructured

LoopsLoops

Simple Simple looploop

Simple LoopsSimple Loops

Test cases for simple loops: Skip the loop entirely

Only one pass through the loop

Two passes through the loop

m passes through the loop (m < n)

(n-1), n and (n+1) passes through the loop

Where n is the maximum number of allowable passes

Nested LoopsNested Loops

Test cases for nested loops:1. Start at the innermost loop. Set all the outer loops to

their minimum iteration parameter values

2. Test the min+1, typical, max-1 and max for the innermost loop, while holding the outer loops at their minimum values

3. Move out one loop and set it up as in step 2, holding all other loops at typical values. Continue this step until the outermost loop has been tested

Test cases for concatenated loops:1. If the loops are independent of one another then treat

each as a simple loop, otherwise treat as nested loops

[2] Black-Box Testing[2] Black-Box Testing

Complementary to white box testing. Derive external conditions that fully exercise all functional requirements

requirementsrequirements

eventseventsinputinput

outputoutput

Black Box StrengthsBlack Box Strengths

Attempts to find errors in the following categories: Incorrect or missing functions

Interface errors

Errors in data structures or external database access

Behaviour or performance errors

Initialization or termination errors

Black box testing is performed during later stages of testing

There are a variety of black box techniques: comparison testing (develop independent versions of the system),

orthogonal array testing (sampling of an input domain which has several variables)

Black Box MethodsBlack Box Methods

Equivalence Partitioning: Divide input domain into classes of data.

Each test case then uncovers whole classes of errors.

Examples: valid data (user supplied commands, file names, graphical data (e.g., mouse picks)), invalid data (data outside bounds of the program, physically impossible data, proper value supplied in wrong place)

Boundary Value Analysis: More errors tend to occur at the boundaries of the input domain

Select test cases that exercises bounding values

Examples: an input condition specifies a range bounded by values a and b. Test cases should be designed with values a and b and just above and below a and b

[3] Debugging[3] Debugging

Testing is a structured process that identifies an error’s “symptoms” Debugging is a diagnostic process that identifies an error’s “source”

test casestest cases

resultsresults

DebuggingDebugging

suspectedsuspectedcausescauses

identifiedidentifiedcausescausescorrectionscorrections

regressionregressionteststests

new testnew testcasescases

execution execution of casesof cases

Debugging EffortDebugging Effort

time required to time required to diagnose the diagnose the symptom and symptom and determine the determine the causecause

time requiredtime requiredto correct the to correct the errorerrorand conductand conductregression testsregression tests

Definition (Regression Tests): re-execution of a subset of test cases to ensure that changes do not have unintended side effects

Symptoms and CausesSymptoms and Causes

symptomsymptomcausecause

symptom and cause may be symptom and cause may be geographically separatedgeographically separated

symptom may disappear whensymptom may disappear when another problem is fixedanother problem is fixed

cause may be due to acause may be due to a combination of non-errorscombination of non-errors

cause may be due to a systemcause may be due to a system or compiler erroror compiler error

cause may be due tocause may be due to assumptions that everyoneassumptions that everyone believesbelieves

symptom may be intermittentsymptom may be intermittent

Not all bugs are equalNot all bugs are equal

damagedamage

mildmild annoyingannoying

disturbingdisturbingseriousserious

extremeextremecatastrophiccatastrophic

infectiousinfectious

Bug TypeBug Type

Bug Categories: function-related bugs, system-related bugs, data bugs, coding bugs, design bugs, documentation bugs, standards violations, etc.

Debugging TechniquesDebugging Techniques

Brute Force: Use when all else fails. Memory dumps and run-time traces. Mass of information amongst which the error may be found

Backtracking: Works in small programs where there are few backward paths Trace the source code backwards from the error to the source

Cause Elimination: Create a set of “cause hypotheses” Use error data (or further tests) to prove or disprove these

hypotheses

But debugging is an art. Some people have innate prowess and others don’t

Debugging TipsDebugging Tips

Don’t immediately dive into the code, think about the symptom you are seeing

Use tools (e.g. dynamic debuggers) to gain further insight

If you are stuck, get help from someone else

Ask these questions before “fixing” the bug:1. Is the cause of the bug reproduced in another part of the

program?

2. What bug might be introduced by the fix?

3. What could have been done to fix the bug in the first place?

Be absolutely sure to conduct regression tests when you do “fix” the bug