MDD and the Tautology Problem: Discussion Notes.
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MoDeVVA @ MODELS 2009, Denver. 10/5/2009. What are the dangers of using the same model to both generate a system and the test suite for that system.
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Chapter 1 Logic of Compound Statements
This document introduces basic concepts in propositional logic and discrete mathematics including:
- Statements and their truth values
- Logical connectives such as negation, conjunction, disjunction, implication, biconditional
- Compound statements formed using logical connectives
- Truth tables to determine the truth values of compound statements
- Tautologies, contradictions and contingencies
- Negation, contrapositive, converse and inverse of conditional statements
- De Morgan's laws of negation for conjunction and disjunction
Examples are provided to illustrate key concepts and definitions throughout.
Discrete Mathematics - Propositional Logic
This document introduces some basic concepts in propositional logic. It defines propositional logic as the study of how simple propositions combine to form more complex propositions. It discusses statements as descriptions that can be true or false, and provides examples. It also introduces logical connectives like negation, conjunction, disjunction, implication and biconditional, and shows how they combine atomic propositions into compound propositions. Truth tables are provided to illustrate the truth values of compound propositions formed with different connectives.
Propositional logic
The document provides an overview of propositional logic including:
1. It defines statements, logical connectives, and truth tables. Logical connectives like negation, conjunction, disjunction and others are explained.
2. It discusses various logical concepts like tautology, contradiction, contingency, logical equivalence, and logical implications.
3. It outlines propositional logic rules and properties including commutative, associative, distributive, De Morgan's laws, identity law, idempotent law, and transitive rule.
4. It provides an example of using truth tables to test the validity of an argument about bachelors dying young.
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Unit testing is a method where developers write code to test individual units or components of an application to determine if they are working as intended. The document discusses various aspects of unit testing including:
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- Common unit testing techniques like statement coverage, branch coverage, and path coverage which aim to test all possible paths through the code.
- How unit testing fits into the software development lifecycle and is typically done by developers before handing code over for formal testing.
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The document provides examples to illustrate white box testing techniques
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testing.pdf
This document provides an overview of software testing at different levels. It discusses unit testing, integration testing, system testing, and acceptance testing. Unit testing validates individual code modules, integration testing validates how modules are combined based on the design, system testing ensures all requirements are met when the full system is integrated, and acceptance testing is done by the customer. The document also covers topics like test-driven development, black box vs white box testing, and strategies for integration testing like top-down and bottom-up.
IEEE 1633 Recommended Practices for Reliable Software
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Software Testing 1/5
The table ranks 10 features of a traffic light system based on their likelihood of failure and impact of failure, assigning each a priority number. It considers things like the push button, getting the time, turning lights on and off, and sounds. Higher priority numbers indicate features that are more likely to fail or would have a greater impact if they did fail, like correctly sequencing the lights.
testing strategies and tactics
Unit 8 discusses software testing concepts including definitions of testing, who performs testing, test characteristics, levels of testing, and testing approaches. Unit testing focuses on individual program units while integration testing combines units. System testing evaluates a complete integrated system. Testing strategies integrate testing into a planned series of steps from requirements to deployment. Verification ensures correct development while validation confirms the product meets user needs.
Testing concepts [3] - Software Testing Techniques (CIS640)
Slides from Software Testing Techniques course offered at Kansas State University in Spring'16 and Spring'17. Entire course material can be found at https://github.com/rvprasad/software-testing-course.
Software_Testing_Overview.pptx
This document provides an overview of software testing and debugging. It discusses the definitions and purposes of testing and debugging. Testing is the process of verifying that a system meets specified requirements, while debugging is the process of finding and fixing errors in source code. The document then covers various topics related to software testing such as the phases of a tester's work, the goals and dichotomies of testing versus debugging, models for testing, consequences of bugs, taxonomies of bugs, and test metrics.
A Software Testing Intro
What is testing?
“An empirical, technical investigation conducted to provide stakeholders with information about the quality of the product under test.”
- Cem Kaner
Utility of Test Coverage Metrics in TDD
This document discusses test coverage metrics in test-driven development (TDD). It defines common coverage metrics like statement coverage and branch coverage and explains mutation coverage in more detail. Mutation coverage involves making small changes to code to generate mutants and measuring whether tests can detect the changes. The document also lists some popular tools for measuring test coverage and mutation coverage. It observes that coverage metrics are relevant for TDD and mutation coverage specifically tells if aspects of code are truly tested.
Chapter 13 software testing strategies
This ppt covers the following
A strategic approach to testing
Test strategies for conventional software
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Validation testing
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The document provides guidelines for an annotated bibliography assignment aimed at increasing nursing students' knowledge of leadership in nursing practice. Students will select five nurse leaders to research and write one-page summaries for each leader. Each summary must include the leader's roles and responsibilities, accomplishments, barriers to achieving goals, and knowledge gained from reading about the leader. The assignment will help prepare students for a poster presentation on nursing leadership.
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Slides from presentation at the Chicago Quality Assurance Association, February 25, 2014.
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- 1. MDD and the Tautology Problem: Discussion Notes MoDeVVA @ MODELS 2009 October 5, 2009 Robert V. Binder
- 2. The Tautology Effect • Transformation of model into object code is like transformation of source code into object code • An antecedent and its transformation cannot provide additional information necessary to reveal many common faults • White-box testing has well know limitations • Do these apply to implementations produced with MDD?
- 3. White Box Testing Limitations • Cannot test missing code – can’t reveal omissions • Cannot completely infer requirements (intent) from code • Where do we get the oracle? (how to discern correct/incorrect outputs?) • Triggering of side-effects • Platform-specific behavior/interactions • Blind to interaction effects outside the scope of the unit under test • Doesn’t scale • Doesn’t support “non-functional” testing • Possible developer bias in test selection
- 4. Weuyker: Adequacy Axioms • In terms of the antecedent (source code), what must an adequate test suite exercise? • Must at least cover every statement – What is a statement in a model? • Anti-extensionality – The semantic equality of two programs is not sufficient to imply that they should necessarily be tested the same way • Anti-decomposition – Although a program has been adequately tested, it does not necessarily imply that each of its called modules has been adequately tested. • More … • Elaine J. Weyuker, “The Evaluation Of Program-based Software Test Data Adequacy Criteria,” Communications of the ACM, v 31 n 6, June 1988.
- 5. Manna: Limits of Verification • Verification = proof of correctness – We can never be sure that the specifications are correct – No verification system can verify every correct program – We can never be certain that a verification system is correct • Zohar Manna and Richard Waldinger, “The Logic of Computer Programming,” IEEE Transactions on Software Engineering, v SE-4, n 3, May 1978
- 6. Some Observations • Transforming model elements to an executable – Fewer constraints than code expression to machine instructions – Many assumptions baked-in with translator – More fault opportunities • Many functionally equivalent implementations possible, suggests test strategy – M to E1 with T1, M to E2 with T2 – Run same test suite on E1 and E2 – Expect identical results for deterministic behavior – Expect bounded results for non-deterministic behavior