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Using UML, Patterns, and Java Object-Oriented Software Engineering Chapter 11: Testing These slides have been altered by Mohammad Ariful Hyder for CSE 321 using additional resources. (See references) Outline Terminology Types of errors Dealing with errors Quality assurance vs Testing Component Testing Unit testing Integration testing Testing Strategy Design Patterns & Testing Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 2 Terminology Reliability: The measure of success with which the observed behavior of a system confirms to some specification of its behavior. IEEE(The ability of a system or component to perform its required functions under stated conditions for a specified period of time. It is often expressed as a probability.) Failure: Any deviation of the observed behavior from the specified behavior Error: The system is in a state such that further processing by the system will lead to a failure. Stress or overload errors, Capacity or boundary errors, Timing errors, Throughput or performance errors Fault (Bug): The mechanical or algorithmic cause of an error. Quality: IEEE(the degree to which a system, component, or process meets customer or user needs or expectations.) There are many different types of errors and different ways how we can deal with them. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 3 Examples of Faults and Errors Faults in the Interface specification Mismatch between what the client needs and what the server offers Mismatch between requirements and implementation Algorithmic Faults Missing initialization Branching errors (too soon, too late) Missing test for nil Bernd Bruegge & Allen H. Dutoit Mechanical Faults (very hard to find) Documentation does not match actual conditions or operating procedures Errors Stress or overload errors Capacity or boundary errors Timing errors Throughput or performance errors Object-Oriented Software Engineering: Using UML, Patterns, and Java 4 Dealing with Errors Verification: Assumes hypothetical environment that does not match real environment Proof might be buggy (omits important constraints; simply wrong) Modular redundancy: Expensive Declaring a bug to be a “feature” Bad practice Patching A patch (sometimes called a "fix") is a quick-repair job for a piece of programming. During a software product's beta test distribution or try-out period and later after the product is formally released, problems (called bug) will almost invariably be found. A patch is the immediate solution that is provided to users; it can sometimes be downloaded from the software maker's Web site. The patch is not necessarily the best solution for the problem and the product developers often find a better solution to provide when they package the product for its next release. A patch is usually developed and distributed as a replacement for or an insertion in compiled code (that is, in a binary file or object module). In larger operating systems, a special program is provided to manage and keep track of the installation of patches. Slows down performance Testing (this lecture) Testing is never good enough Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 5 Another View on How to Deal with Errors Error prevention (before the system is released): Use good programming methodology to reduce complexity Use version control to prevent inconsistent system Apply verification to prevent algorithmic bugs Error detection (while system is running): Testing: Create failures in a planned way Debugging: Start with an unplanned failuresMonitoring: Deliver information about state. Find performance bugs Error recovery (recover from failure once the system is released): Data base systems (atomic transactions) Modular redundancy Recovery blocks Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 6 Some Observations It is impossible to completely test any nontrivial module or any system Theoretical limitations: Halting problem Practial limitations: Prohibitive in time and cost Testing can only show the presence of bugs, not their absence (Dijkstra). Successful test cases: In unit and integration testing: A successful test case is one that finds a previously undiscovered error. In acceptance testing: A successful test case is one that successfully implements a requirement. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 7 Testing takes creativity Testing often viewed as dirty work. To develop an effective test, one must have: Detailed understanding of the system Knowledge of the testing techniques Skill to apply these techniques in an effective and efficient manner Testing is done best by independent testers We often develop a certain mental attitude that the program should work in a certain way when in fact it does not. Programmers often stick to the data set that makes the program work - "Don’t mess up my code!" A program often does not work when tried by somebody else. Don't let this be the end-user. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 8 Testing Activities Subsystem Code Subsystem Code Unit Test Unit Test Tested Subsystem Tested Subsystem Requirements Analysis Document System Design Document Integration Test Integrated Subsystems Functional Test User Manual Functioning System Tested Subsystem Subsystem Code Unit Test Bernd Bruegge & Allen H. Dutoit All tests by developer Object-Oriented Software Engineering: Using UML, Patterns, and Java 9 Testing Activities continued Client’s Understanding of Requirements Global Requirements Validated Functioning System PerformanceSystem Test Accepted System Acceptance Test User Environment Installation Test Tests by client Tests by developer User’s understanding Tests (?) by user Bernd Bruegge & Allen H. Dutoit Usable System Object-Oriented Software Engineering: Using UML, Patterns, and Java System in Use 10 Fault Handling Techniques Fault Handling Fault Avoidance Design Methodology Verification Fault Tolerance Fault Detection Atomic Transactions Reviews Modular Redundancy Configuration Management Debugging Testing Unit Testing Bernd Bruegge & Allen H. Dutoit Integration Testing System Testing Correctness Debugging Object-Oriented Software Engineering: Using UML, Patterns, and Java Performance Debugging 11 Quality Assurance encompasses Testing Quality Assurance Usability Testing Scenario Testing Fault Avoidance Verification Prototype Testing Product Testing Fault Tolerance Configuration Management Atomic Transactions Modular Redundancy Fault Detection Reviews Walkthrough Inspection Unit Testing Bernd Bruegge & Allen H. Dutoit Debugging Testing Integration Testing System Testing Correctness Debugging Object-Oriented Software Engineering: Using UML, Patterns, and Java Performance Debugging 12 Types of Testing Unit Testing: Perfomed on individual method or class Carried out by developers Goal: Confirm that method or class is correctly coded and carries out the intended functionality Sometimes refers to testing on a subsystem Integration Testing: Groups of subsystems (collection of classes) and eventually the entire system Carried out by developers Goal: Test the interface among the subsystems Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 13 System Testing System Testing: The entire system Carried out by developers Goal: Determine if the system meets the requirements (functional and global) Acceptance Testing: Evaluates the system delivered by developers Carried out by the client. May involve executing typical transactions on site on a trial basis Goal: Demonstrate that the system meets customer requirements and is ready to use Implementation (Coding) and testing go hand in hand Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 14 Unit Testing Informal: Incremental coding Static Analysis: Hand execution: Reading the source code (This is called desk checking) Walkthrough (informal presentation to others) Code Inspection (formal presentation to others) Automated Tools checking for syntactic and semantic errors departure from coding standards Dynamic Analysis: Black-box testing (Test the input/output behavior) White-box or Glass-box testing (Test the internal logic of the subsystem or object) Data-structure based testing (Data types determine test cases) Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 15 Black-box Testing Focus: I/O behavior. If for any given input, we can predict the output, then the module passes the test. Almost always impossible to generate all possible inputs ("test cases") Goal: Reduce number of test cases by equivalence partitioning: Divide input conditions into equivalence classes Choose test cases for each equivalence class. Example: If an object is supposed to accept a negative number, testing one negative number is enough Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 16 Black-box Testing (Continued) Selection of equivalence classes (No rules, only guidelines): Input is valid across range of values. Select test cases from 3 equivalence classes: Below the range Within the range Above the range Input is valid if it is from a discrete set. Select test cases from 2 equivalence classes: Valid set member Invalid set member Input is valid if it is the Boolean value true or false. Select a true value a false value Input is valid if it is an exact value of a particular data type. Select the value any other value of that type Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 17 More on Equivalence Classes Example The specifications for a DBMS state that the product must handle any number of records between 1 and 16,383 (214–1) If the system can handle 34 records and 14,870 records, then it probably will work fine for 8,252 records Basic Idea If the system works for any one test case in the range (1..16,383), then it will probably work for any other test case in the range Range (1..16,383) constitutes an equivalence class Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 18 Equivalence Classes and Boundary Value Analysis Principle of Equivalence Classes Any one member of an equivalence class is as good a test case as any other member of the equivalence class Range Example: (1..16,383) Defines three different equivalence classes: Equivalence Class 1: Fewer than 1 record Equivalence Class 2: Between 1 and 16,383 records Equivalence Class 3: More than 16,383 records Principle of Boundary Value Analysis Select test cases on or just to one side of the boundary of equivalence classes This greatly increases the probability of detecting a fault Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 19 More on Database Example Test case 1: Test case 2: Test case 3: Test case 4: Test case 5: Test case 6: Test case 7: Bernd Bruegge & Allen H. Dutoit 0 records Member of equivalence class 1 and adjacent to boundary value 1 record Boundary value 2 records Adjacent to boundary value 723 records Member of equivalence class 2 16,382 records Adjacent to boundary value 16,383 records Boundary value 16,384 records Member of equivalence class 3 and adjacent to boundary value Object-Oriented Software Engineering: Using UML, Patterns, and Java 20 Equivalence Testing of Output Specifications We also need to perform equivalence testing of the output specifications Example: In 2003, the minimum Social Security (OASDI) deduction from any one paycheck was $0.00, and the maximum was $5,394.00 Test cases must include input data that should result in deductions of exactly $0.00 and exactly $5,394.00 Also, test data that might result in deductions of less than $0.00 or more than $5,394.00 Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 21 Overall Strategy Equivalence classes together with boundary value analysis to test both input specifications and output specifications This approach generates a small set of test data with the potential of uncovering a large number of faults Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 22 White-box Testing Focus: Thoroughness (Coverage). Every statement in the component is executed at least once. Four types of white-box testing Statement Testing Branch Testing Path Testing Loop Testing Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 23 White-box Testing (Continued) Statement Testing: Every statement should be tested at least once. Branch Testing (Conditional Testing): Make sure that each possible outcome from a condition is tested at least once if ( i = TRUE) printf("YES\n"); else printf("NO\n"); Test cases: 1) i = TRUE; 2) i = FALSE Path Testing: Make sure all paths in the program are executed. This is infeasible. (Combinatorial explosion) Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 24 White-box Testing Example FindMean(float Mean, FILE ScoreFile) {SumOfScores = 0.0; NumberOfScores = 0; Mean = 0; Read(ScoreFile, Score); /*Read in and sum the scores*/ while (!EOF(ScoreFile) { if ( Score > 0.0 ) { SumOfScores = SumOfScores + Score; NumberOfScores++; } Read(ScoreFile, Score); } /* Compute the mean and print the result */ if (NumberOfScores > 0 ) { Mean = SumOfScores/NumberOfScores; printf("The mean score is %f \n", Mean); } else printf("No scores found in file\n"); } Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 25 White Box Testing: Path Testing Draw a Flow Graph (see example next slide) Use McCabe’s Complexity Measure Definition Number of predicates (expressions returning a T/F value) + 1 #Edges – #Nodes + 2 Number of regions in flow graph Purpose: To determine a basis (the test cases) To limit the number of test cases Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 26 White-box Testing Example: Determining the Paths FindMean (FILE ScoreFile) { float SumOfScores = 0.0; int NumberOfScores = 0; 1 float Mean=0.0; float Score; Read(ScoreFile, Score); 2 while (!EOF(ScoreFile) { 3 if (Score > 0.0 ) { SumOfScores = SumOfScores + Score; 4 NumberOfScores++; } 5 Read(ScoreFile, Score); 6 } /* Compute the mean and print the result */ 7 if (NumberOfScores > 0) { Mean = SumOfScores / NumberOfScores; printf(“ The mean score is %f\n”, Mean); } else printf (“No scores found in file\n”); 9 } Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 8 27 Constructing the Logic Flow Diagram Start 1 F 2 T 3 T F 5 4 6 7 T F 9 8 Exit Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 28 Determine a Basis: Use example on slides 27 and 28 Determine McCabe’s Complexity Measure The easiest formula to evaluate is to read the code: Number of predicates (3) + 1 = 4 Check your answer by determining the number of regions: Number of closed regions (3) + number of outside regions (always 1) = 4 Determine a basis (a linearly independent set of paths): Will contain 4 paths. Use the following technique: Take the shortest path. Add a single predicate to the next path. Basis: Path 1: 1, 2, 7, 9, Exit (Could have the number 10) //at end of file after reading Path 2: 1, 2, 3, 5, 6, 2, 7, 9, Exit // reads a value that is negative or zero; // then at end of file Path 3: 1, 2, 3, 4, 5, 6, 2, 7, 8, Exit // reads a single value that is positive, so // completes mean Path 4: 1, 2, 7, 8, Exit: // infeasible path Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 29 Finding the Test Cases Start 1 a (Covered by any data) 2 b (Positive score) d c 4 (At end of file) e f 5 6 (NumberOfScores >i 0 8 k Bernd Bruegge & Allen H. Dutoit (File must contain at least one value) 3 7 (Negative score) h (Reached through g if either f or e is reached) g j (NumberOfScores < 0) 9 Exit l Object-Oriented Software Engineering: Using UML, Patterns, and Java 30 Another Example: Binary search flow graph Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 31 Independent paths 1, 2, 3, 4, 5, 14 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14 1, 2, 3, 4, 5, 6, 7, 11, 12, 5, … 1, 2, 3, 4, 6, 7, 2, 11, 13, 5, … Test cases should be derived so that all of these paths are executed A dynamic program analyser may be used to check that paths have been executed Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 32 Comparison of White & Black-box Testing White-box Testing: Potentially infinite number of paths have to be tested White-box testing often tests what is done, instead of what should be done Cannot detect missing use cases Black-box Testing: Potential combinatorical explosion of test cases (valid & invalid data) Often not clear whether the selected test cases uncover a particular error Does not discover extraneous use cases ("features") Bernd Bruegge & Allen H. Dutoit Both types of testing are needed White-box testing and black box testing are the extreme ends of a testing continuum. Any choice of test case lies in between and depends on the following: Number of possible logical paths Nature of input data Amount of computation Complexity of algorithms and data structures Object-Oriented Software Engineering: Using UML, Patterns, and Java 33 The 4 Testing Steps 1. Select what has to be measured 3. Develop test cases Analysis: Completeness of requirements Design: tested for cohesion Implementation: Code tests 2. Decide how the testing is done Code inspection Proofs (Design by Contract) Black-box, white box, Select integration testing strategy (big bang, bottom up, top down, sandwich) Bernd Bruegge & Allen H. Dutoit A test case is a set of test data or situations that will be used to exercise the unit (code, module, system) being tested or about the attribute being measured 4. Create the test oracle An oracle contains the predicted results for a set of test cases The test oracle has to be written down before the actual testing takes place Object-Oriented Software Engineering: Using UML, Patterns, and Java 34 Review: Design Principles Cohesion: The interaction (or relatedness) between items within a model. Goal: High A module should have one purpose so that it is more likely to be reusable and maintainable. Ex. In a class, the data and methods should be highly related. Coupling: The interaction among modules Goal: Low Limit the coupling between two modules to promote reuse. Ex. The number of modules called by the calling module should be 7±2 Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 35 Guidance for Test Case Selection Use analysis knowledge about functional requirements (blackbox testing): Use cases Expected input data Invalid input data Use implementation knowledge about algorithms: Examples: Force division by zero Use sequence of test cases for interrupt handler Use design knowledge about system structure, algorithms, data structures (white-box testing): Control structures Test branches, loops, ... Data structures Test records fields, arrays, ... Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 36 Unit-testing Heuristics 1. Create unit tests as soon as object design is completed: Black-box test: Test the use cases & functional model White-box test: Test the dynamic model Data-structure test: Test the object model 5. Create a test harness Test drivers and test stubs are needed for integration testing 6. Describe the test oracle Often the result of the first successfully executed test 2. Develop the test cases Goal: Find the minimal number of test cases to cover as many paths as possible 7. Execute the test cases Don’t forget regression testing Re-execute test cases every time a change is made. 3. Cross-check the test cases to eliminate duplicates Don't waste your time! 8. Compare the results of the test with the test oracle Automate as much as possible 4. Desk check your source code Reduces testing time Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 37