software testing see also sommerville, chapter 8 amman and offut, introduction to software testing,...

Software Testing

See also Sommerville, Chapter 8Amman and Offut, Introduction to Software Testing, Cambridge University Press, 2008.

Testing

• Most basic form of post-hoc SQA• Helps define program functionality• Can be used as documentation (c.f. XP)• Must ensure program is testable (c.f. PSS docs)• Methods become callable• Modules get looser coupling

Basic Terminology

• The system under test (SUT) can be of different types (procedural, reactive, etc.)

• A test case consists of a single input for the SUT• A verdict is a judgment after a test case

terminates – pass/fail/warning/don’t know• An oracle is a method to produce verdicts• A test suite is a set of test cases• How much have we tested? – coverage

measures!

User Requirements

Software Requirements

Architecture Design

Detailed design & Coding Unit Testing

Integration testing

The ”V” modelIntegrates design and testing

Time

Test cases

4

System testing

Acceptance testing

Test cases

Test cases

Test cases

Structural Testing (Glass or white box)

• An error must exist along a path• If tests don’t exercise that path then error can

never be observed• So identify and exercise each path• No loops – finitely many paths – good!• Loops – infinitely many paths – bad! • Loops + branches – exponential growth in path

numbers with loop depth – very bad !!!!

Structural Testing - Problems

• What about sins of omission? – no path to go down!

• What about dead code – is a path possible? • How to avoid redundant testing?

Condensation Graph

Assignments1

Assignments2

Assignments3Assignments4

Halt

Start

Cond1

Cond2

Path analysis: 1&3, 1&4, 1&2&3, 1&2&4 …etc

Structural Testing Requirements

• These are structural requirements on a test suite

• They ignore functionality!• Easy to define using graph theory• Possible to automate generation by constraint

solving• Easy to measure coverage!

Graph Coverage

• A path is a sequence of nodes n0 ,…, nk in a (condensation) graph G, such that each adjacent node pair, (ni, ni+1) forms an edge in G.

• A test requirement tr(.) is a predicate on paths– Noden( p ) p has node n

– Edgee (p) p has edge e

Graph Coverage

Definition: Given a set TR of test requirementsfor a graph criterion C, A test suite T satisfies Con graph G if, and only if for every testrequirement tr(.) TR, there is at least one path p in G such that tr(p) is true

(i.e. p satisfies tr(.))

Why so Formal?

• Answer: Sometimes coverage properties become very technical to define for efficiency reasons.

Structural Coverage Criteria(Amman and Offut, Chapter 2)

2.1. Node Coverage (NC) TR contains each reachable node in G.

2.2. Edge Coverage (EC) TR contains each reachable path of length ≤ 1.

2.3 Edge-Pair Coverage (EPC) TR contains each reachable path of length ≤ 2.

2.7. Complete Path Coverage (CPC) TR contains all paths in G.

2.8. Specified Path Coverage (SPC) TR contains a set S of test paths, where S is supplied as a parameter.

Example. S contains paths that traverse everyloop free path p in G and every loop in G both 0and 1 times.

Functional Testing(Black-box Testing)

• Black-box = structure of code is invisible+ Tests the specification not the code+ Insensitive to code refactoring- Hard to find test verdicts – aka oracle problem- Hard to define coverage- Huge volume of testing – user profiles?- Use cases are an excellent source of tests

Random Testing

• Generate input vectors (or sequences) at random, fire into system and observe.

• Easy or tricky to implement– Low level data types … e.g. Int … easy– High level data types … e.g. graphs … tricky

• High volume of test cases … but is that good structural coverage?

• Good for low input dimension 1-5?– But poor for high input dimension

Random Testing

• Oracle step is difficult to automate without precise requirements

• Set up and tear down must also be considered• Does random distribution match expected

distribution?• Are some data combinations meaningless? Data

interdependencies and constraints!– Example consider calendar combinations: – Year/month/day/day of week– 1961/02/29/Wednesday … is this legal or not?

• Can try to filter out bad data but this can be very slow

k-wise testing

• Some components have fixed input size k e.g. a method myMethod(X:string,Y:char,Z:int)

• We need test vectors of length k i.e. ( i1, …, ik )

• Choose (say) C=10 input values Vi = vi1,…,vi

c for each 1≤ i ≤k

• Test suite Sk is all combinations of V1 ,…, Vk

• Cartesian Product S = V1 … Vk

• Test suite size S is then Ck = 10k

• Probably not feasible for S ≥ 10,000

Example

• Suppose k = 3, C = 2, then Ck = 23 = 8• V1 = Sat, Sun • V2 = A, B • V3 = 1, 2 • S3 =

(Sat, A, 1), (Sun, A, 1), (Sat, B, 1), (Sun, B, 1), (Sat, A, 2), (Sun, A, 2), (Sat, B, 2), (Sun, B, 2)

Clearly S3 has size 8 In general Sk has size Ck which is exponential in k.

n-Wise Testing – for n≤k

For 1 ≤i≤k, let ci be a fixed value from Vi

An n-wise test is a vector ( i1, …, ik )

such that n elements are chosen from V1 ,…, Vk

and the rest are chosen from c1, …, ck .

Let Sn be the set of all n-wise tests.

Example: 1-wise testing

• Suppose n = 1 and let c1 = Sat, c2 = A, c3 = 1 • V1 = Sat, Sun • V2 = A, B • V3 = 1, 2 • S1 =

(Sat, A, 1), (Sun, A, 1), (Sat, B, 1), (Sat, A, 2)

Clearly S1 has size k*(C-1)+1 which is linear in k.So S1 is small but has limited coverage.

Example: 2-wise testing(aka all-pairs or pairwise testing)

• Suppose n = 2 and c1 = Sat, c2 = A, c3 = 1 • V1 = Sat, Sun • V2 = A, B • V3 = 1, 2 • S2 =

(Sat, A, 1), (Sun, A, 1), (Sat, B, 1), (Sun, B, 1) (Sat, A, 2), (Sun, A, 2), (Sat, B, 2)

Clearly S2 has size 7 which is not much smaller than S3.In general S2 is much smaller than Sk.S2 grows O(C2), which is much slower than Ck!

Why Pairwise Testing?

• Bugs involving interactions between three or more parameters are progressively less common[2].

• NASA database application. 67 percent of the failures were triggered by only a single parameter value, 93 percent by two-way combinations, and 98 percent by three-way combinations [13].

• 10 UNIX commands. Cohen et al. showed that the pairwise tests gave over 90 percent block coverage [9].

• Medical software devices. Only 3 of 109 failure reports indicated that more than two conditions were required to cause the failure [14].

Why Pairwise Testing

• Browser and server. More than 70 percent of bugs were detected with two or fewer conditions (75 percent for browser and 70 percent for server) and approximately 90 percent of the bugs reported were detected with three or fewer conditions (95 percent for browser and 89 percent for server) [13].

• User interface software at Telcordia. Studies [8] showed that most field faults were caused by either incorrect single values or by an interaction of pairs of values. Their code coverage study also indicated that pairwise coverage is sufficient for good code coverage.

• Established tools, e.g. PICT• See www.pairwise.org

Test Cases from Use Cases

• Instantiate a scenario with concrete data values, and expected results.

• Different flows lead to different use cases– Sunny day and rainy day scenarios

• Use graph coverage to measure use case coverage• Structured and easy to use• Natural focus on most significant use cases• Good approach to system and acceptance testing,

but may be difficult and unit and integration levels

UseCaseName: PurchaseTicket

Precondition: The passenger is standing in front of ticket distributor and has sufficient money to purchase a ticket.

Sequence:1. The passenger selects the number of zones to

be travelled, If the passenger presses multiple zone buttons, only the last button pressed is considered by the distributor.

2. The distributor displays the amount due3. The passenger inserts money

4. The passenger selects a new zone before inserting sufficient money, the distributor returns all the coins and bills inserted by the passenger

5. If the passenger inserted more money than the amount due the distributor returns excess change.

6. The distributor issues ticket.7. The passenger picks up the change and ticket.

TestCaseName: PurchaseTicket_SunnyDayPrecondition: The passenger is standing in front of

ticket distributor and has two 5€ notes and 3 * 10 Cent coins

Sequence:1. The passenger presses in succession the zone

buttons 2, 4, 1 and 22. The distributor should display in succession the

fares 1.25€ 2.25€, 0.75€ and 1.25€3. The passenger inserts a 5€ note4. The distributor returns 3*1€ coins, 75Cent

and a 2-zone ticket.

PostconditionThe passenger has one 2-zone ticket

We should also derive test cases that exerciserainy day scenarios (when something goeswrong) to test robustness.

Unit Testing with JUnit

• Developed by the XP community 2002• Framework for automating the execution of unit

test for Java classes• Write new test cases by subclassing the

TestCase class• Organise TestCases into TestSuites• Automates testing process• Built around Command and Composite patterns

Why use Junit?

• Junit tightly integrates development and testing, supports the XP approach

• Allows you to write code faster while increasing quality (???)– Can refactor code without worrying about

correctness• JUnit is simple.– Easy as running the compiler on your code

• JUnit tests check their own results (oracle step) and provide immediate feedback– No manual comparison of expected with actual– Simple visual feedback

• JUnit tests can be composed into a hierarchy of test suites– Can run tests for any layer in the hierarchy

• Writing JUnit tests is inexpensive– No harder than writing a method to exercise the code

• JUnit tests increase the stability of software– More tests = more stability

• Junit tests are developer tests– Tests fundamental building blocks of system– Tests delivered with code as a certified package

• Junit tests are written in Java– Seamless bond between test and code under test– Test code can be refactored into software code

and vice-versa– Data type compatibility (float, double etc.)

• Junit is free

Junit Design

• A TestCase is a Command object• A class of test methods subclasses TestCase• A TestCase has public testXXX() methods• To check expected with actual output invoke

assert() method• Use setUp() and tearDown() to prevent side

effects between subsequent testXXX() calls

Test

Run(TestResult)

Test

run(TestResult)setUp()tearDown()runTest()

TestSuite

addTest()Run(TestResult)

Test

setUp()tearDown()run(TestResult)

testName:String

• TestCase objects can be composed into TestSuite hierarchies. Automatically invoke all the testXXX() methods in each object

• A TestSuite is composed of TestCase instances or other TestSuite instances

• Nest to arbitrary depth• Run whole TestSuite with a single pass/fail

result• Get your own installation instructions

Writing a Test Case

• Define a subclass of TestCase• Override the setUp() method to intialise

object(s) under test• Optionally override the tearDown() method to

release objects under test• Define 1 or more public testXXX() methods hat

exercise the object(s) under test and assert expected results

Import junit.framework.TestCase

Public class ShoppingCartTest extends TestCase Private ShoppingCart cart;Private Product book1;

Protected void setUp() Cart = new ShoppingCart();Book1 = new Product(“myTitle”, “50€”);Cart.addItem(book1)

Protected void tearDown() //release objects under test here if necessary

Public void testEmpty() Cart.empty(); // empty out cartassertEquals(0,cart.getItemCount() );

Public void testAddItem() Product book2 = new Product(“title2”, “65€”);cart.addItem(book2);double expectedBalance = book1.getPrice() + book2.getPrice();assertEquals(expectedBalance,

cart.getBalance());assertEquals(2, cart.getItemCount() );

Public void testRemoveItem() throwsproductNotFoundException

Cart.removeItem(book1);assertEquals(1, cart.getItemCount() );

Public void testRemoveItemNotInCart() try

Product book3 = new Product(“title3”, “10€”);Cart.removeItem(book3);fail(“should raise a ProductNotFoundException”);

Catch(ProductNotFoundException expected)

//passed the test! // of class ShoppingCartTest