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Software Testing

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Motivation

• People are not perfect– We make errors in design and code

• Goal of testing: given some code, uncover as many errors as possible

• Important and expensive activity:– May spend 30-40% of total project effort on testing– For safety critical system cost of testing is several

times higher than all other activities combined

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A Way of Thinking

• Design and coding are creative activities• Testing is destructive

– The primary goal is to “break” the code

• Often same person does both coding and testing– Need “split personality”: when you start testing,

become paranoid and malicious– This is surprisingly difficult: people don’t like

to find out that they made mistakes.

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Testing Objective

• Testing: a process of executing software with the intent of finding errors

• Good testing: a high probability of finding as-yet-undiscovered errors

• Successful testing: discovers unknown errors

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Basic Definitions

• Test case: specifies – Inputs + pre-test state of the software– Expected results (outputs an state)

• Black-box testing: ignores the internal logic of the software, and looks at what happens at the interface (e.g., given this inputs, was the produced output correct?)

• White-box testing: uses knowledge of the internal structure of the software– E.g., write tests to “cover” internal paths

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Testing Approaches

• We will look at a small sample of approaches for testing

• White-box testing– Control-flow-based testing– Loop testing– Data-flow-based testing

• Black-box testing– Equivalence partitioning

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Control-flow-based Testing

• A traditional form of white-box testing• Step 1: From the source, create a graph describing

the flow of control– Called the control flow graph

– The graph is created (extracted from the source code) manually or automatically

• Step 2: Design test cases to cover certain elements of this graph– Nodes, edges, paths

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Example of a Control Flow Graph (CFG)

if (x+y < 100) s:=s+x+y; else d:=d+x-y;}

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s:=0;d:=0;while (x<y) {

x:=x+3;y:=y+2;

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Elements of a CFG

• Three kinds of nodes:– Statement nodes: represent single-entry-single-exit

sequences of statements– Predicate nodes: represent conditions for branching– Auxiliary nodes: (optional) for easier understanding

(e.g., “join points” for IF, etc.)

• Edges: represents possible flow of control

• It is relatively easy to map standard constructs from programming languages to elements of CFGs

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IF-THEN, IF-THEN-ELSE, SWITCH

if (c) if (c) switch (c)then then case 1:// join point else case 2:

// join point // join point

…

… … …..

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Example

switch (position) case CASHIER if (empl_yrs > 5) bonus := 1; else bonus := 0.7; case MANAGER bonus := 1.5; if (retiring_soon) bonus := 1.2 * bonus case …endswitch

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Mapping for Loops

Note: other loops (e.g., FOR, DO-WHILE,…) are mapped similarly. Figure out how this is done.

while (c) {

} …

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Statement Coverage

• Basic idea: given the control flow graph define a “coverage target” and write test cases to achieve it

• Traditional target: statement coverage– Need to write test cases that cover all nodes in the

control flow graph

• Intuition: code that has never been executed during testing may contain errors– Often this is the “low-probability” code

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Example• Suppose that we write and

execute two test cases• Test case #1: follows path 1-

2-exit (e.g., we never take the loop)

• Test case #2: 1-2-3-4-5-7-8-2-3-4-5-7-8-2-exit (loop twice, and both times take the true branch)

• Do we have 100% statement coverage?

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T F

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Branch Coverage

• Target: write test cases that cover all branches of predicate nodes– True and false branches of each IF– The two branches corresponding to the

condition of a loop– All alternatives in a SWITCH statement

• In modern languages, branch coverage implies statement coverage

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Branch Coverage• Statement coverage does not imply branch

coverage– Can you think of an example?

• Motivation for branch coverage: experience shows that many errors occur in “decision making” (i.e., branching)– Plus, it subsumes statement coverage.

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Example

• Same example as before

• Test case #1: follows path 1-2-exit

• Test case #2: 1-2-3-4-5-7-8-2-3-4-5-7-8-2-exit

• What is the branch coverage?

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T F

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Achieving Branch Coverage

• For decades, branch coverage has been considered a necessary testing minimum

• To achieve it: pick a set of start-to-end paths (in the CFG) that cover all branches, and then write test cases to execute these paths

• It can be proven that branch coverage can be achieved with at most E-N+2 paths

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Example

• First path: 1-2-exit (no execution of the loop)

• Second path: we want to include edge 2-3, so we can pick 1-2-3-4-5-7-8-2-exit

• What would we pick for the third path?

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Determining a Set of Paths

• How do we pick a set of paths that achieves 100% branch coverage?

• Basic strategy:– Consider the current set of chosen paths– Try to add a new path that covers at least one

edge that is not covered by the current paths

• Sometimes, the set of paths chosen with this strategy is called the “basic set”

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Some Observations

• It may be impossible to execute some of the chosen paths from start-to-end.– Why?– Thus, branches should be executed as part of

other chosen paths

• There are many possible sets of paths that achieve branch coverage

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Loop Testing

• Branch coverage is not sufficient to test the execution of loops– It means two scenarios will be tested: the loop is

executed zero times, and the loop is executed at least once

• Motivation for more testing of loops: very often there are errors in the boundary conditions

• Loop testing is a white-box technique that focuses on the validity of loops

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Testing of Individual Loops

• Suppose that m is the min possible number of iterations, and n is the max possible number of iterations

• Write a test case that executes the loop m times and another one that executes it m+1 times

• Write a test case that executes the loop for a “typical number” of iterations

• Write a test case that executes the loop n-1 times and another one for n times

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Testing of Individual Loops (cont.)

• If it is possible to have variable values that imply less than m iterations or more than n iterations, write test cases using those

• E.g., if we have a loop that is only supposed to process at most the 10 initial bytes from an array, run a test case in which the array has 11 bytes

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Nested Loops

• Example: with 3 levels of nesting and 5 test cases for each level, total of 125 possible combinations: too much

• Start with the innermost loop do the tests (m,m+1, typical, ), keep the other loops at their min number of iterations

• Continue toward the outside: at each level, do tests (m,m+1, typical, )– The inner loops are at typical values– The outer loops are at min values

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Data-flow-based Testing

• Basic idea: test the connections between variable definitions (“write”) and variable uses (“read”)

• Starting point: variation of the control flow graph– Each node represents a single statement, not a chain of

statements

• Set DEF(n) contains variables that are defined at node n (i.e., they are written)

• Set USE(n): variables that are read

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ExampleAssume y is already initialized

1 s:= 0;2 x:= 0;3 while (x<y) {4 x:=x+3;5 y:=y+2;6 if (x+y<10)7 s:=s+x+y; else8 s:=s+x-y;

DEF(1) := {s}, USE(1) := DEF(2) := {x}, USE(2) :=DEF(3) := , USE(3) := {x,y}DEF(4) := {x}, USE(4) := {x}DEF(5) := {y}, USE(5) := {y}DEF(6) := , USE(6) := {x,y}DEF(7) := {s}, USE(7) := {s,x,y}

DEF(8) := {s}, USE(8) := {s,x,y}DEF(9) := , USE(9) := DEF(10) := , USE(10) :=

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Reaching DefinitionsA definition of variable x at node n1

reaches node n2 if and only if there is a path between n1 and n2 that does not contain a definition of x

DEF(1) := {s}, USE(1) := DEF(2) := {x}, USE(2) :=DEF(3) := , USE(3) := {x,y}DEF(4) := {x}, USE(4) := {x}DEF(5) := {y}, USE(5) := {y}DEF(6) := , USE(6) := {x,y}DEF(7) := {s}, USE(7) := {s,x,y}DEF(8) := {s}, USE(8) := {s,x,y}

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Reaches nodes 2,3,4,5,6,7,8, but not 9 and 10.

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Def-use Pairs

• A def-use pair (DU) for variable x is a pair of nodes (n1,n2) such that – x is in DEF(n1)

– The definition of x at n1 reaches n2

– x is in USE(n2)

• In other words, the value that is assigned to x at n1 is used at n2– Since the definition reaches n2, the value is not killed

along some path n1...n2.

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Examples of Def-Use Pairs

DEF(1) := {s}, USE(1) := DEF(2) := {x}, USE(2) :=DEF(3) := , USE(3) := {x,y}DEF(4) := {x}, USE(4) := {x}DEF(5) := {y}, USE(5) := {y}DEF(6) := , USE(6) := {x,y}DEF(7) := {s}, USE(7) := {s,x,y}DEF(8) := {s}, USE(8) := {s,x,y}

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Reaches nodes 2, 3, 4, 5, 6, 7, 8, but not 9,10

For this definition, two DU pairs:1-7, 1-8

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Data-flow-based Testing

• Identify all DU pairs and construct test cases that cover these pairs– Several variations with different “relative strength”

• All-DU-paths: For each DU pair (n1,n2) for x, exercise all possible paths n1, n2 that are clear of a definition of x

• All-uses: for each DU pair (n1,n2) for x, exercise at least one path n1 n2 that is clear of definitions of x

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Data-flow-based Testing

• All-definitions: for each definition, cover at least one DU pair for that definition– i.e., if x is defined at n1, execute at least one path n1..n2

such that x is in USE(n2) and the path is clear of definitions of x

• Clearly, all-definitions is subsumed by all-uses which is subsumed by all-DU-paths

• Motivation: see the effects of using the values produced by computations – Focuses on the data, while control-flow-based testing

focuses on the control

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Black-box Testing

• Unlike white-box testing, here we don’t use any knowledge about the internals of the code

• Test cases are designed based on specifications– Example: search for a value in an array

• Postcondition: return value is the index of some occurrence of the value, or -1 if the value does not occur in the array

• We design test cases based on this spec

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Equivalence Partitioning

• Basic idea: consider input/output domains and partition them into equiv. classes– For different values from the same class, the

software should behave equivalently

• Use test values from each class– Example: if the range for input x is 2..5, there

are three classes: “<2”, “between 2..5”, “5<”– Testing with values from different classes is

more likely to uncover errors than testing with values from the same class

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Equivalence Classes

• Examples of equivalence classes– Input x in a certain range [a..b]: this defines three

classes “x<a”, “a<=x<=b”, “b<x”– Input x is boolean: classes “true” and “false”– Some classes may represent invalid input

• Choosing test values– Choose a typical value in the middle of the class(es)

that represent valid input– Also choose values at the boundaries of all classes:

e.g., if the range is [a..b], use a-1,a, a+1, b-1,b,b+1

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Example

• Suppose our spec says that the code accepts between 4 and 24 inputs, and each one is a 3-digit integer

• One partition: number of inputs– Classes are “x<4”, “4<=x<=24”, “24<x”– Chosen values: 3,4,5, 14, 23,24,25

• Another partition: integer values– Classes are “x<100”, “100<=x<=999”, “999<x”– Chosen values: 99,100,101, 500, 998,999,1000

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Another Example

• Similar approach can be used for the output: exercise boundary values

• Suppose that the spec says “the output is between 3 and 6 integers, each one in the range 1000-2500

• Try to design input that produces– 3 outputs with value 1000– 3 outputs with value 2500– 6 outputs with value 1000– 6 outputs with value 2500

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Example: Searching

• Search for a value in an array– Return value is the index of some occurrence of

the value, or -1 if the value does not occur in the array

• One partition: size of the array– Since people often make errors for arrays of

size 1, we decide to create a separate equivalence class

– Classes are “empty arrays”, array with one element”, “array with many elements”

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Example: Searching

• Another partition: location of the value– Four classes: “first element”, “last element”, “middle element”,

“not found”

Array Value OutputEmpty 5 -1[7] 7 0[7] 2 -1[1,6,4,7,2] 1 0[1,6,4,7,2] 4 2[1,6,4,7,2] 2 4[1,6,4,7,2] 3 -1

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Testing Strategies

• We talked about testing techniques (white-box, black-box)

• Many unanswered questions– E.g., who does the testing? – Which techniques should we use ?– And when? – And more…?

• There are no universal strategies, just principles that have been useful in practice– E.g., the notions of unit testing and integration testing

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Some Basic Principles

• Testing starts at the component level and works “outwards”– Unit testing integration testing system testing

• Different testing techniques are appropriate at different scopes

• Testing is conducted by developers and/or by a specialized group of testers

• Testing is different from debugging– Debugging follows successful testing

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Scope and Focus

• Unit testing: scope = individual component– Focus: component correctness– White-box and black-box techniques

• Integration testing: scope = set of interacting components– Focus: correctness of component interactions– Mostly black-box, some white-box techniques

• System testing: scope = entire system– Focus: overall system correctness– Only black-box techniques

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Test-First Principle

• Modern practices emphasize the importance of testing during development

• Example: test-first programming– Basic idea: before you start writing any code, first write

the tests for this code

– Write a little test code, write the corresponding unit code, make sure it passes the tests, and then repeat

– What programming methodology uses this approach?

– What are the advantages of test-first programming?

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Advantages of Test-First Programming

• Developers do not “skip” unit testing• Satisfying for the programmer: feeling of

accomplishment when the tests pass• Helps clarify interface and behavior before

programming– To write tests for something, first you need to

understand it well!

• Software evolution– After changing existing code, rerun the tests to gain

confidence (regression testing)

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Traditional Testing Strategies

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Context for Traditional Testing• Waterfall model: starts with requirements

analysis then design– The design often has a hierarchical module

structure

Direction of increasing decision making

Typical decision making module

Typical worker modules

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Context for Traditional Testing

• Modules are tested and integrated in some order based on the module hierarchy– Two common cases: top-down order and bottom-up

order

– Unit testing: focus on an individual module

– Integration testing focus on module interactions, after integration

• System testing: the entire system is tested w.r.t. customer requirements, as described in the spec

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Unit Testing

• Scope: one component from the design– Often corresponds to the notion of “compilation unit”

from the programming language

• Responsibility of the developer– Not the job of an independent testing group

• Both white-box and black-box techniques are used for unit testing

• Maybe necessary to create stubs: – If modules not yet implemented or not yet tested

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Basic Strategy for Unit Testing

• Create black-box tests– Based on the specification of the unit (as determined

during design)• Evaluate the tests using white-box techniques (test

adequacy criteria)– How well did the tests cover statements, branches,

paths, DU-pairs, etc.?– Many possible criteria; at the very least need 100%

branch coverage• Create more tests for the inadequacies: e.g., to

increase coverage of DU-pairs

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System Testing

• Goal: find whether the program does what the customer expects to see– Black-box techniques

• In the spec created during requirements analysis, there should be validation criteria– How are the developers and the customers going to

agree that the software is OK?

• Many issues: functionality, performance, documentation, usability, portability, etc.

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System Testing (cont)

• Initial part of system testing is done by the software producer

• Eventually, we need testing done by the customers– Every time a customer runs the software he/she is

testing it– Customers are good at doing unexpected things, which

is great for testing• If the software is build for a single customer:

series of acceptance tests– Deploy the software in the customer environment and

have end-users run it

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System Testing (cont)

• If the software is produced for multiple customers: two phases

• Alpha testing: conducted at the vendor’s site by a few customers– The vendor records any errors and usage problems

• Beta testing: the software is distributed to many end-users; they run it in their own environment and report problems– Often done by thousands of users

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Stress Testing

• Form of system testing: the behavior of the system under very heavy load– E.g., what if we have data sets that are an order

of magnitude larger than normal? Will we run out of memory? Will the OS start writing memory pages to disk (thrashing)?

– E.g., what if our server gets 10 times more client requests than usual?

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Stress Testing (cont)

• Goal: find how well the system can cope with overload

• Reason 1: determine failure behavior – If load goes above the intended (which often is a

possibility) how gracefully does the system fail?

• Reason 2: expose bugs that only occur under heavy loads– Especially for OS, middleware, servers, etc.– E.g., memory leaks, incorrect resource allocation and

scheduling, race conditions

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Regression Testing

• Basic idea: rerun old tests to make sure that nothing was “broken” by a change– Changes: bug fixes, module integration, maintenance

enhancements, etc.

• To be able to do this regularly, need test automation tools– Load tests, execute them, check correctness – Everything has to be completely automatic

• Could happen at any time: during initial development or after deployment

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• Questions on the exam?