程序代写代做代考 database System, Acceptance, and Regression Testing

System, Acceptance, and Regression Testing
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 1

Staging A&T techniques
Requirements Requirements Architectural Detailed Elicitation Specification Design Design
Unit Coding
Integration & Delivery
Maintenance
Identify qualites
Plan acceptance test
Plan system test
Plan unit & integration test
Monitor the A&T process
Validate specifications
Analyze architectural design
Inspect architectural design
Inspect detailed design
Generate system test
Generate integration test
Generate unit test
Design scaffolding Design oracles
Code inspection
Generate regression test
Update regression test
Execute unit test Analyze coverage
Generate structural test
Execute integration test
Execute system test Execute acceptance test
Execute regression test
Collect data on faults
analyze faults and improve the process
(c) 2007 Mauro Pezzè & Michal Young
Ch 1, slide 2
Process improvement
test caseexecution and swvalidation
Generation of tests
Verification of specs Planning & monitoring

Learning objectives
• Distinguish system and acceptance testing
– How and why they differ from each other and from unit and integration testing
• Understand basic approaches for quantitative assessment (reliability, performance, …)
• Understand interplay of validation and verification for usability and accessibility
– How to continuously monitor usability from early design to delivery
• Understand basic regression testing approaches
– Preventing accidental changes
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 3

System
Acceptance
Regression
Test for … Test by …
Correctness, completion
Development test group
Verification
Usefulness, satisfaction
Test group with users
Validation
Accidental changes
Development test group
Verification
(c) 2007 Mauro Pezzè & Michal Young
Ch 22, slide 4

System Testing
• Key characteristics:
– Comprehensive (the whole system, the whole spec)
– Based on specification of observable behavior
Verification against a requirements specification, not validation, and not opinions
– Independent of design and implementation
Independence: Avoid repeating software design errors in system test design
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 5

Independent V&V
• One strategy for maximizing independence: System (and acceptance) test performed by a different organization
– Organizationally isolated from developers (no pressure to say “ok”)
– Sometimes outsourced to another company or agency
• Especiallyforcriticalsystems
• Outsourcing for independent judgment, not to save money • May be additional system test, not replacing internal V&V
– Not all outsourced testing is Independent V&V
• Not independent if controlled by development organization
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 6

Independence without changing staff
• If the development organization controls system testing …
– Perfect independence may be unattainable, but we can reduce undue influence
• Develop system test cases early
– As part of requirements specification, before major design decisions have been made
• Agile “test first” and conventional “V model” are both examples of designing system test cases before designing the implementation
• An opportunity for “design for test”: Structure system for critical system testing early in project
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 7

Incremental System Testing
• System tests are often used to measure progress
– System test suite covers all features and scenarios of use
– As project progresses, the system passes more and more system tests
• Assumes a “threaded” incremental build plan: Features exposed at top level as they are developed
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 8

Global Properties
• Some system properties are inherently global
– Performance, latency, reliability, …
– Early and incremental testing is still necessary, but provide only estimates
• A major focus of system testing
– The only opportunity to verify global properties against actual system specifications
– Especially to find unanticipated effects, e.g., an unexpected performance bottleneck
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 9

Context-Dependent Properties
• Beyond system-global: Some properties depend on the system context and use
– Example: Performance properties depend on environment and configuration
– Example: Privacy depends both on system and how it is used
• Medical records system must protect against unauthorized use, and authorization must be provided only as needed
– Example: Security depends on threat profiles • And threats change!
• Testing is just one part of the approach
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 10

Stress Testing
• Often requires extensive simulation of the execution environment
– With systematic variation: What happens when we push the parameters? What if the number of users or requests is 10 times more, or 1000 times more?
• Often requires more resources (human and machine) than typical test cases
– Separate from regular feature tests
– Run less often, with more manual control
– Diagnose deviations from expectation
• Which may include difficult debugging of latent faults!
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 11

Example: testing of the timetabling system at King’s in September 2014
• The system was tested on 20 users • It was released to 14000 users
• The system crashed immediately • Possible solutions:
– stress testing (to accommodate multiple read requests)
– extensive functional testing (to accommodate multiple constraints)
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 12

22.3
Acceptance testing
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 13

Estimating Dependability
• Measuring quality, not searching for faults
– Fundamentally different goal than systematic testing
• Quantitative dependability goals are statistical – Reliability
– Availability
– Mean time to failure – …
• Requires valid statistical samples from
operational profile
– Fundamentally different from systematic testing
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 14

Statistical Sampling
• We need a valid operational profile (model)
– Sometimes from an older version of the system
– Sometimes from operational environment (e.g., for an embedded controller)
– Sensitivity testing reveals which parameters are most important, and which can be rough guesses
• And a clear, precise definition of what is being measured
– Failure rate? Per session, per hour, per operation?
• And many, many random samples
– Especially for high reliability measures
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 15

Is Statistical Testing Worthwhile?
• Necessary for
– Critical systems (safety critical, infrastructure, …)
• But difficult or impossible when
– Operational profile is unavailable or just a guess
• Often for new functionality involving human interaction
– But we may factor critical functions from overall use to obtain a good model of only the critical properties
– Reliability requirement is very high
• Required sample size (number of test cases) might require years of test execution
• Ultra-reliability can seldom be demonstrated by testing
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 16

Process-based Measures
• Less rigorous than statistical testing – Based on similarity with prior projects
• System testing process
– Expected history of bugs found and resolved
• Alpha, beta testing
– Alpha testing: Real users, controlled environment
– Beta testing: Real users, real (uncontrolled) environment
– May statistically sample users rather than uses
– Expected history of bug reports
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 17

Usability
• A usable product
– is quickly learned
– allows users to work efficiently – is pleasant to use
• Objective criteria
– Time and number of operations to perform a task
– Frequency of user error
• blame user errors on the product!
• Plus overall, subjective satisfaction
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 18

Verifying Usability
• Usability rests ultimately on testing with real users — validation, not verification
– Preferably in the usability lab, by usability experts
• But we can factor usability testing for process visibility — validation and verification throughout the project
– Validation establishes criteria to be verified by testing, analysis, and inspection
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 19

Factoring Usability Testing
Validation (usability lab)
• Usability testing establishes usability check-lists
– Guidelines applicable across a product line or domain
• Early usability testing evaluates “cardboard prototype” or mock-up
– Produces interface design
Verification (developers, testers)
• Inspection applies usability check-lists to specification and design
• Behavior objectively verified (e.g., tested) against interface design
(c) 2007 Mauro Pezzè & Michal Young
Ch 22, slide 20

Varieties of Usability Test
• Exploratory testing
– Investigate mental model of users
– Performed early to guide interface design
• Comparison testing
– Evaluate options (specific interface design choices)
– Observe (and measure) interactions with alternative interaction patterns
• Usability validation testing
– Assess overall usability (quantitative and qualitative) – Includes measurement: error rate, time to complete
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 21

Regression Testing
• Yesterday it worked, today it doesn’t – I was fixing X, and accidentally broke Y
– That bug was fixed, but now it’s back
• Tests must be re-run after any change
– Adding new features
– Changing, adapting software to new conditions – Fixing other bugs
• Regression testing can be a major cost of software maintenance
– Sometimes much more than making the change
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 22

Basic Problems of Regression Test
• Maintaining test suite
– If I change feature X, how many test cases must be revised because they use feature X?
– Which test cases should be removed or replaced? Which test cases should be added?
• Cost of re-testing
– Often proportional to product size, not change size
– Big problem if testing requires manual effort
• Possible problem even for automated testing, when the test suite and test execution time grows beyond a few hours
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 23

Test Case Maintenance
• Some maintenance is inevitable
– If feature X has changed, test cases for feature X will require updating
• Some maintenance should be avoided
– Example: Trivial changes to user interface or file format should not invalidate large numbers of test cases
• Test suites should be modular! – Avoid unnecessary dependence
– Generating concrete test cases from test case specifications can help
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 24

Obsolete and Redundant
• Obsolete: A test case that is not longer valid
– Tests features that have been modified, substituted, or removed
– Should be removed from the test suite
• Redundant: A test case that does not differ significantly from others
– Unlikely to find a fault missed by similar test cases
– Has some cost in re-execution
– Has some (maybe more) cost in human effort to maintain
– May or may not be removed, depending on costs
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 25

Selecting and Prioritizing Regression Test Cases
• Should we re-run the whole regression test suite? If so, in what order?
– Maybe you don’t care. If you can re-rerun everything automatically over lunch break, do it.
– Sometimes you do care …
• Selection matters when
– Test cases are expensive to execute
• Because they require special equipment, or long run-times, or cannot be fully automated
• Prioritization matters when
– A very large test suite cannot be executed every day
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 26

Code-based Regression Test Selection
• Observation: A test case cannot find a fault in code it does not execute
– In a large system, many parts of the code are untouched by many test cases
• =>Only execute test cases that execute changed or new code or are influenced by the changed or new code
Executed by test case
New or changed
(c) 2007 Mauro Pezzè & Michal Young
Ch 22, slide 27

Control-flow and Data-flow Regression Test Selection
• Same basic idea as code-based selection
– Re-run test cases only if they include changed elements
– Elements may be modified control flow nodes and edges, or definition-use (DU) pairs in data flow
• To automate selection:
– Tools record elements touched by each test case • Stored in database of regression test cases
– Tools note changes in program
– Check test-case database for overlap
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 28

Specification-based Regression Test Selection
• Like code-based and structural regression test case selection
– Pick test cases that test new and changed functionality
• Difference: No guarantee of independence
– A test case that is not “for” changed or added feature X might find a bug in feature X anyway
• Typical approach: Specification-based prioritization
– Execute all test cases, but start with those that related to changed and added features
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 29

Summary
• System testing is verification
– System consistent with specification?
– Especially for global properties (performance, reliability)
• Acceptance testing is validation
– Includes user testing and checks for usability
• Usability and accessibility require both
– Usability testing establishes objective criteria to verify throughout development
• Regression testing repeated after each change – After initial delivery, as software evolves
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 30

Home reading
• Chapter 22 of the book Software Testing and Analysis, by Mauro Pezze and Michal Young
– System testing
(c) 2007 Mauro Pezzè & Michal Young Ch 1, slide 31

Next week – revision lecture
• Use the slides and the tutorials as a guidance when revising
• Use the book for clarification if needed
• Prepare questions for the next lecture
(c) 2007 Mauro Pezzè & Michal Young Ch 22, slide 32