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+ <div class="page">
+ <header>
+ <h1>An Introduction to Structured Testing</h1>
+ <p>© 2024 Thomas Walker Lynch - All Rights Reserved.</p>
+ </header>
+
+
+ <h2>Introduction</h2>
+
+ <p>This guide provides a general overview of testing concepts to help
+ readers understand how the Mosaic test bench integrates within a testing
+ setup. Note that this is not a reference manual for the Mosaic test bench
+ itself. At the time of writing, no such reference document exists, so
+ developers and testers are advised to consult the source code directly for
+ implementation details. A small example can be found in
+ the <code>Test_MockClass</code> file within the tester directory. Other
+ examples can be found in projects that make use of Mosaic.</p>
+
+ <p>A typical testing setup comprises three main components:
+ the <span class="term">test bench</span>, the <span class="term">test
+ routines</span>, and a collection of <span class="term">units under
+ test</span> (UUTs). Here, a UUT is any individual software or hardware
+ component intended for testing. Because this guide focuses on software, we
+ use the term <span class="term">RUT</span> (routine under test) to denote
+ the unit under test in software contexts. Although we use software-centric
+ terminology, the principles outlined here apply equally to hardware
+ testing.</p>
+
+ <p>Each test routine supplies inputs to a RUT, collects the resulting
+ outputs, and determines whether the test passes or fails based on those
+ values. The results are then relayed to the test bench. Testers and
+ developers write the test routines and place them into the test bench.
+ </p>
+
+ <p>Mosaic is a test bench. It serves as a structured environment for
+ organizing and executing tests, and it provides a library of utility
+ routines for assisting the test writer. When run, the test bench sequences
+ through the set of test routines, one by one, providing each test routine
+ with an interface to control and examine standard input and output. (The
+ test routine, depending on its design, might in turn sequence through a
+ series of <span class="term">test cases</span>.) During execution, the test
+ bench records pass/fail results, lists the names of the tests that failed,
+ and generates a summary report with pass/fail totals.</p>
+
+ <p>At the time of this writing, Mosaic does not provide features for
+ breaking up large test runs into parallel pieces and then load balancing
+ those pieces. Perhaps such a feature will be developed for a future version.
+ However, this does not prevent an enterprising tester from running multiple
+ Mosaic runs with different tests in parallel in an ad hoc manner, or
+ with other tools.</p>
+
+ <h2>Function versus Routine</h2>
+
+ <p>A routine is an encapsulated sequence of instructions, with a symbol
+ table for local variables, and an interface for importing and exporting
+ data through the encapsulation boundary. This interface
+ maps <span class="term">arguments</span> from a caller
+ to <span class="term">parameters</span> within the routine, enabling data
+ transfer at runtime. In the context of testing, the arguments that bring
+ data into the routine are referred to as
+ <span class="term">inputs</span>, while those that carry data out are called
+ <span class="term">outputs</span>. Notably, in programming, outputs are often called
+ <span class="term">return values</span>.</p>
+
+ <p>In computer science, a <span class="term">pure function</span> is a routine
+ in which outputs depend solely on the provided inputs, without reference to
+ any internal state or memory that would persist across calls. A pure function
+ produces the same output given the same inputs every time it is called.
+ Side effects, such as changes to external states or reliance on external
+ resources, are not present in pure functions; any necessary interactions
+ with external data must be represented explicitly as inputs or outputs.
+ By definition, a function produces a single output, though this output can
+ be a collection, such as a vector or set.</p>
+
+ <p>Routines with internal state variables that facilitate temporal behavior
+ can produce outputs that depend on the sequence and values of prior
+ inputs. This characteristic makes such routines challenging to
+ test. Generally, better testing results are achieved when testing pure
+ functions, where outputs depend only on current inputs.</p>
+
+
+ <h2>Block and Integration</h2>
+
+ <p>A test routine provides inputs to a RUT and collects its outputs, often
+ doing so repeatedly in a sequence of test cases. The test routine then
+ evaluates these values to determine if the test has passed or failed.</p>
+
+ <p>When a test routine evaluates a RUT that corresponds to a single function
+ or module within the program, it performs a <span class="term">block
+ test</span>.</p>
+
+ <p>When a test routine evaluates a RUT that encompasses multiple program
+ components working together, it is conducting
+ an <span class="term">integration test</span>.</p>
+
+ <p>Integration tests often involve combining significant components of a
+ program that were developed independently, and they may occur later in the
+ project schedule. This phase can be challenging for testers, as it may
+ reveal complex, unforeseen interactions. To mitigate such challenges, some
+ software development methodologies encourage introducing simpler versions of
+ such components early in development, then refining them over time.</p>
+
+
+ <h2>Failures and Faults</h2>
+
+ <p>A test routine has two primary responsibilities: supplying inputs and
+ collecting outputs from the RUT, and determining whether the RUT passed or
+ failed the test. This second responsibility is handled by
+ the <span class="term">failure decider</span>. The failure decider may not
+ always be an explicit function in the test routine, but its logical
+ functionality will be there.</p>
+
+ <p>A failure decider implementation can make false positive and false
+ negative decisions. A false positive occurs when the failure decider
+ indicates that a test has passed when ideally it would have
+ failed. Conversely, a false negative decision occurs when the decider
+ indicates failure when ideally it would have
+ passed. An <span class="term">ideal failure decider</span> would produce
+ neither false positives nor false negatives.</p>
+
+ <p>In general, false negatives are more likely to be caught, as all negative
+ results (fails) lead to debugging sessions and further scrutiny. In
+ contrast positives (passes) garner no further scrutiny, and thus false
+ positives are unlikely to be caught.</p>
+
+ <p>A failure occurs when there is a deviation between
+ the <span class="term">observed output</span> from a RUT and
+ the <span class="term">ideal output</span>. When the ideal output is not
+ available, a <span class="term">reference output</span> is often used in
+ its place. When using reference outputs, the accuracy of the test results
+ depends on both the accuracy of the failure decider and the accuracy of
+ the reference values themselves.</p>
+
+ <p>Some folks will refer to an <span class="term">observed output</span> as
+ an <span class="term">actual output</span>. Also, some engineers will
+ refer to a <span class="term">reference value</span> as
+ a <span class="term">golden value</span>, especially when the reference
+ value is considered to be highly accurate. However, these alternative
+ terms are less precise, so in our shop, we prefer the terminology
+ introduced in the previous paragraph.</p>
+
+ <p>In testing, a <span class="term">fault</span> refers to an error or flaw
+ within a design, implementation, or realization that, under specific
+ conditions, would lead to an observable failure. While the origins of a
+ fault often be traced back further, perhaps to a root cause such as a
+ human error, providing a fix at such a root cause will not prevent the
+ failure in the next product release.</p>
+
+ <p>Thus the goal of testing is to create conditions that cause faults to
+ manifest as observed failures. The tester's responsibility is not to
+ identify or locate the underlying faults. Once a failure is observed, it
+ then becomes the task of a person playing a developer’s role to
+ investigate the cause, identify the fault, and to address it
+ appropriately.</p>
+
+ <p>The Mosaic tool assists testers in finding failures, but it does not
+ directly help with identifying the underlying fault that led to the
+ failure. Mosaic is a tool for testers. However, these two tasks of
+ finding failures and faults are not entirely separate. Knowing where a
+ failure occurs can provide the developer with a good place to start for
+ looking for the fault, and also narrows down the possibilities.
+ Additionally, once a developer claims to have fixed a fault, that claim
+ can be verified by re-running the tests, which is useful.</p>
+
+ <h2>Unstructured Testing</h2>
+
+ <p>Unstructured testing forms the foundation of all testing strategies. This
+ section outlines some common approaches to unstructured testing.</p>
+
+ <h3>Reference-Value Based Testing</h3>
+
+ <p>In <span class="term">reference-value based testing</span>, an ordering
+ is assigned to the <span class="term">inputs</span> for
+ the routine under test, as well as to
+ its <span class="term">outputs</span>. Through this ordering the inputs
+ and outputs become vectors. Thus the routine under test is given
+ an <span class="term">input vector</span> and it returns
+ an <span class="term">observed output vector</span>.</p>
+
+ <p>A <span class="term">Reference Model</span> is then
+ given the same input vector, and then it
+ produces a <span class="term">reference output vector</span>. The reference
+ output vector has the same component ordering as the
+ <span class="term">observed output vector</span>.
+
+ <p>The <span class="term">failure detection function</span> then compares
+ each observed output vector with its corresponding reference output vector. If
+ they do not match, the test is deemed to have failed.</p>
+
+ <p>It follows that in reference-value based testing, the accuracy of
+ the <span class="term">failure detection function</span> depends solely on
+ the accuracy of the reference model.</p>
+
+ <p>When the implementation of the reference model is unrelated to the
+ routine under test, we tend to expect that the errors produced by the
+ reference model will be uncorrelated with those produced by the routine
+ under test, and thus not probable to coincide. This property will bias
+ tests towards delivering false negatives. As noted earlier, false negatives
+ are likely to be caught as test fails are followed up with further
+ scrutiny. Hence, reference-value based testing tends to be pretty
+ accurate even when the reference generator is not ideal.</p>
+
+ <h3>Property-Check Testing</h3>
+
+ <p><span class="term">property-check testing</span> is an alternative to
+ reference-value based testing. Here, rather than comparing each observed
+ output to a reference output, the observed output is validated against
+ known properties or expected characteristics.</p>
+
+ <p>For example, given an integer as input, a function that correctly squares
+ this input will preserve the parity of the input, as an odd number squared
+ will be odd, and an even number squared will be even. The failure decider
+ can check this property for each test case, and if it does not hold, the
+ test case fails. Such a weak property check would be biased towards
+ false positive decisions. Those are the bad ones, as passing tests
+ typically receive no further scrutiny.</p>
+
+ <h3>Spot Checking</h3>
+
+ <p>In spot checking, the function under test is checked against one or
+ two input vectors.</p>
+
+ <p>Moving from zero to one, i.e., running a program for the first time,
+ can have a particularly high threshold of difficulty. A tremendous
+ amount is learned during development if even one test passes for
+ a function.</p>
+
+ <p>There are sometimes notorious edge cases. Zeros and values just off the
+ end of arrays come to mind. Checking a middle value and edge cases
+ is often an effective approach.</p>
+
+ <p>It takes two points to determine a line. In Fourier analysis,
+ it takes two samples per period of the highest frequency component
+ to determine an entire waveform. A piece of code that works for both
+ edge cases and values in between is often reliable. This effect
+ explains why ad hoc testing has lead to so much working code.</p>
+
+ <p>Spot checking is particularly useful during development. It provides
+ the highest leverage in testing for the lowest investment. High
+ investment is not appropriate for code still in development that
+ is not yet stable and is open to being refactored.</p>
+
+
+ <h2>Structured Testing</h2>
+
+ <h3>The need for structured testing</h3>
+
+ <p>Another name for unstructured testing is <span class="term">black box testing</span>. Black box testing has a serious problem in that
+ search space for failures becomes exponentially larger as the number of inputs grows.</p>
+
+
+
+ <p>A developer will use routines as building blocks for building
+ a program. This leads to a hierarchy of routines.
+
+
+
+ <p>A test of a single RUT that corresponds to a single routine in a program is
+ known as a <span class="term">block test</span>. When the RUT encompasses
+ multiple functions, it is called an <span class="term">integration
+ test</span>.</p>
+
+ <p>A common structured testing approach is to first validate individual functions, then
+ test their communication and interactions, and, finally, assess the complete
+ integration of functions across a system.</p>
+
+ <p>When functions are composed without adding internal state (memory), the composition itself acts as a single <span class="term">function</span>. Therefore, a test designed for an individual function may also be applied to composed functions, provided they are stateless.</p>
+
+
+
+
+ </div>
+</body>
+</html>
+
+<!--
+discipline, if it was a bug, it should be test
+
+ structured testing
+
+ <p>An important testing technique is to first test functions, then
+ to test the communication between them, and then as a last step
+ to test the integration of the functions.</p>
+
+
+ sequential
+
+
+ <p>To transform a routine with state variables into a more testable pure
+ function, the internal memory is replaced by additional inputs. These
+ inputs then supply the memory values for each test.
+ The values to be written to the
+ memory can then be made into additional outputs. Additionally, the
+ sequencing logic must be arranged to <span class="term">single-step</span>
+ the routine, meaning that each call to the routine under test results in
+ exactly one update to memory.</p>
+
+
+
+
+ <p>A routine can be transformed into a function
+ by replacing the memory with further inputs that
+ provide the memory value, adding further outputs that signify writes
+ to the memory, and organizing the sequencing logic such that the
+ routine <span class="term">single steps</span>, i.e. one write
+ update to the memory occurs per call to the routine under test.</p>
+
+ <p>Haskell, for example, provides a language semantic that makes testing
+ of stateful routines more convenient. Short of such language support
+ the process of converting routines to functions can be error prone
+ itself, and lead to testing of a function that does not necessarily
+ correspond to what would happen when testing the routine.</p>
+
+ <p>Many languages employ the term <span class="term">function</span>
+ to stand for a language construct, where said construct is not
+ a function according to the formal definition of the term, but
+ rather are routines. This started with the FORTRAN language, which
+ distinguished functions from other routines, because they could
+ return a single value that could be used in an expression, while
+ routines in the language only passed values through arguments.
+ In this guide, we will use the term routine to describe program
+ units that do not fit the formal definition of function.</p>
+
+
+
+ <p>Because the test routine only has access to the rut through its interfaces,
+ the rut is said to be a black box. However, this term is misleading, as
+ all computer code is accessed through inputs and outputs.
+
+
+
+ <h1>White Box Testing</h1>
+
+ <h2>Terminology</h2>
+
+ <p>Testing centers around three key components: the <span class="term">test
+ bench</span>, the <span class="term">test functions</span> (or tests), and
+ the <span class="term">functions under test</span>. In most cases, the
+ developer provides the functions under test. When this tool is used, Mosaic
+ supplies the test bench. This leaves the tester with role of creating and
+ running the tests. Often times, of course, the tester role and the developer
+ role are performed by the same person, still these roles are distinct.</p>
+
+ <p>The term <span class="term">function</span> refers to any program or
+ circuit where outputs are determined solely by inputs, without internal
+ state being kept, and without side effects. All inputs and outputs are
+ explicitly defined. By definition, a function returns a single result, but
+ this is not a very strong constraint because said single result can be a
+ collection, such as a vector or set.</p>
+
+ <p>We need this precise definition for function so as to make meaningful
+ statements in this document, but the Mosaic TestBench can be used with
+ tests that are designed to test any sort of subroutine. There is a later
+ chapter (provide that I get around to writing it) on testing stateful
+ subroutines.</p>
+
+ <p>There is also a nuanced distinction
+ between <span class="term">function</span> in singular and plural forms,
+ because a collection of functions can be viewed as a single larger function
+ with perhaps more inputs and outputs. Hence, when a test is said to work on
+ a function, we cannot conclude that it is a single function defined in the
+ code.</p>
+
+ <p>A test must have access to the function under test so that it can supply
+ inputs and harvest results from it. A test must also have a
+ <span class="term">failure detection function</span> that is when given
+ copies of the inputs and outputs will returns a result indicating if a
+ test failed, or not. Hopefully the failure detection function is accurate,
+ or even perfect, as then fewer failures will be missed, and less work must
+ be done to verify cases it has concluded have failed.</p>
+
+ <h2> Property-Check Testing
+
+ <p>Another form of testing is that of <span class="term">property-check
+ testing</span>. With this type of testing input vectors are generated and
+ introduced to the function under test as before; however instead of using a
+ reference value, the actual result vector
+
+
+
+<h2> spot checking</h2>
+
+another form of testing, inputs are generated as for the
+
+properties
+
+<p>An ordered set of inputs used in testing is called an "input vector" or "test
+vector". When an input vector is given to the function under test, the result is
+ an "corresponding actual output vector".</p>
+
+<p>In one form of testing, there is a golden model that when given an input
+vector will produce the "corresponding expected output vector". This is also
+called the "golden value". The bit order in the expected output vector is made
+the same as for that of the actual output venctor.</p>
+
+<p>In a common for
+
+
+ <p>As a test bench, Mosaic does not define failure functions directly; rather, the tester implements these functions within the tests.</p>
+
+ <p>The tester's goal is to identify <span class="term">failures</span>, which represent observable mistakes by the developer. The identified cause of failure is called a <span class="term">fault</span>, and it may relate to specific code lines, logic flaws, or physical hardware issues. In hardware testing, faults might also stem from manufacturing defects or component degradation.</p>
+
+ <p>Mosaic is a tool for finding failures. Once a failure is identified, the developer typically uses a debugger to trace the mechanism behind the failure, ultimately locating the fault. While Mosaic aids in failure detection, its primary role is not in the debugging process itself.</p>
+
+ </div>
+</body>
+</html>
+-->
+
+<!-- LocalWords: decider's
+ -->
+++ /dev/null
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- font-size: 1.5rem;
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- color: hsl(42, 100%, 84%);
- text-transform: uppercase;
- margin-top: 1.5rem;
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- font-family: 'Courier New', Courier, monospace;
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- font-family: 'Courier New', Courier, monospace;
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- }
- </style>
-</head>
-<body>
- <div class="page">
- <header>
- <h1>White Box Testing</h1>
- <p>© 2024 Thomas Walker Lynch - All Rights Reserved.</p>
- </header>
-
- <h2>Introduction</h2>
-
- <div>
- <p>Testing centers around three key components: the <span class="term">test
- bench</span>, the <span class="term">test functions</span> (or tests), and
- the <span class="term">functions under test</span>. In most cases, the
- developer provides the functions under test. When this tool is used, Mosaic
- supplies the test bench. This leaves the tester with the role of creating and
- running the tests. Often, of course, the tester role and the developer role are
- performed by the same person, though these roles are distinct.</p>
-
- <p>The term <span class="term">function</span> refers to any program or
- circuit where outputs are determined solely by inputs, without internal
- state being kept, and without side effects. All inputs and outputs are
- explicitly defined. By definition, a function returns a single result, but
- this is not a very strong constraint because said single result can be a
- collection, such as a vector or set.</p>
-
- <p>We need this precise definition for a function to make meaningful
- statements in this document, but the Mosaic TestBench can be used with
- tests designed to evaluate any type of subroutine. A later chapter will
- cover testing stateful subroutines, provided that I get around to writing it.</p>
-
- <p>There is also a nuanced distinction between <span class="term">function</span>
- in singular and plural forms, because a collection of functions can be viewed as
- a single larger function with perhaps more inputs and outputs. Hence, when a test
- is said to work on a function, we cannot conclude that it is a single function
- defined in the code.</p>
-
- <p>A test must have access to the function under test so that it can supply
- inputs and harvest outputs from it. A test must also have a
- <span class="term">failure detection function</span> that, when given
- copies of the inputs and outputs, will return a result indicating if a
- test failed or not. Ideally, the failure detection function is accurate,
- or even perfect, as this reduces missed failures and minimizes the need
- to verify cases that it has flagged as failures.</p>
-
- <p>The tester’s goal is to identify <span class="term">failures</span>,
- observable differences between actual outputs and expected outputs. Once a
- failure is identified, a developer can investigate the issue, locate
- the <span class="term">fault</span>, and implement corrections as
- necessary. While Mosaic aids in failure detection, it does not directly
- assist with debugging.</p>
-
- </div>
-
- <h2>Unstructured Testing</h2>
-
- <p>Unstructured testing is at the base of all testing strategies. The following are some
- examples of approaches to unstructured testing. The Mosaic TestBench is agnostic
- to the approach used for unstructured testing, rather this section is about writing
- the test code that the TestBench will call.</p>
-
- <h3> Reference Value based testing </h3>
-
- <p>In <span class="term">reference value-based testing</span>, an ordering
- is assigned to the <span class="term">inputs</span> for
- the <span class="term">function under test</span>, as well as to
- its <span class="term">outputs</span>. With this ordering, the function
- under test can be said to receive an <span class="term">input
- vector</span> and to return an <span class="term">actual output vector</span>.</p>
-
- <p> In this testing approach, a <span class="term">Reference Model</span> is also used.
- When given an <span class="term">input vector</span>, the Reference Model will produce
- a corresponding <span class="term">reference output vector</span> that follows the
- same component ordering as the <span class="term">actual output vector</span> from the
- function under test.</p>
-
- <p>The <span class="term">failure detection function</span> then compares each
- actual output vector with its respective reference output vector. If they do
- not match, the test is deemed to have failed.</p>
-
- <p>The Reference Model is sometimes referred to as the <span class="term">golden
- model</span>, and said to produce <span class="term">golden values</span>. However, this
- terminology is often an exaggeration, as testing frequently reveals inaccuracies
- in reference values.</p>
-
- <p>Thus, in reference value-based testing, the failure detection function
- relies on a comparison between the actual and reference output vectors. Its accuracy
- depends directly on the accuracy of the Reference Model.</p>
-
- <h3>Property Check Testing</h3>
-
- <p><span class="term">Property check testing</span> is an alternative to
- reference value-based testing. Here, rather than comparing the actual
- outputs to reference outputs, the actual output is validated against
- known properties or expected characteristics.</p>
-
- <p>For example, given an integer as input, a function that squares this
- input should yield an even result for even inputs and an odd result for odd
- inputs. If the output satisfies the expected property, the test passes;
- otherwise, it fails. This approach allows testing of general behaviors
- without specific reference values.</p>
-
- <h3>Spot Checking</h3>
-
- <p>With spot checking, the function under test is checked against one or
- two input vectors.</p>
-
- <p>Moving from zero to one, i.e. trying a program for the first time,
- can have a particularly high threshold of difficulty. A tremendous
- around is learned during development if even one tests passes for
- a function.</p>
-
- <p>Sometimes there are notorious edge cases. Zeros and one off the
- end of arrays come to mind. Checking a middle value and the edge
- cases is often an effective test.</p>
-
- <p>It takes two points to determine a line. In Fourier Analysis,
- it takes two samples per period of the highest frequency component
- to determine an entire wave form. There is only so much a piece of
- code can do different if it works at the edge cases and in between.
- It is because of this effect that ad hoc testing has produced so
- much working code.
- </p>
-
- <p>Spot checking is particularly useful during development. It is the
- highest leverage testing return for low investment. High investment is
- not approrpiate for code in development that is not stable, and is open to
- being refactored.
- </p>
-
- </div>
-</body>
-</html>
-
-<!--
-
- <h1>White Box Testing</h1>
-
- <h2>Terminology</h2>
-
- <p>Testing centers around three key components: the <span class="term">test
- bench</span>, the <span class="term">test functions</span> (or tests), and
- the <span class="term">functions under test</span>. In most cases, the
- developer provides the functions under test. When this tool is used, Mosaic
- supplies the test bench. This leaves the tester with role of creating and
- running the tests. Often times, of course, the tester role and the developer
- role are performed by the same person, still these roles are distinct.</p>
-
- <p>The term <span class="term">function</span> refers to any program or
- circuit where outputs are determined solely by inputs, without internal
- state being kept, and without side effects. All inputs and outputs are
- explicitly defined. By definition, a function returns a single result, but
- this is not a very strong constraint because said single result can be a
- collection, such as a vector or set.</p>
-
- <p>We need this precise definition for function so as to make meaningful
- statements in this document, but the Mosaic TestBench can be used with
- tests that are designed to test any sort of subroutine. There is a later
- chapter (provide that I get around to writing it) on testing stateful
- subroutines.</p>
-
- <p>There is also a nuanced distinction
- between <span class="term">function</span> in singular and plural forms,
- because a collection of functions can be viewed as a single larger function
- with perhaps more inputs and outputs. Hence, when a test is said to work on
- a function, we cannot conclude that it is a single function defined in the
- code.</p>
-
- <p>A test must have access to the function under test so that it can supply
- inputs and harvest results from it. A test must also have a
- <span class="term">failure detection function</span> that is when given
- copies of the inputs and outputs will returns a result indicating if a
- test failed, or not. Hopefully the failure detection function is accurate,
- or even perfect, as then fewer failures will be missed, and less work must
- be done to verify cases it has concluded have failed.</p>
-
- <h2> Property Check Testing
-
- <p>Another form of testing is that of <span class="term">property check
- testing</span>. With this type of testing input vectors are generated and
- introduced to the function under test as before; however instead of using a
- reference value, the actual result vector
-
-
-
-<h2> spot checking</h2>
-
-another form of testing, inputs are generated as for the
-
-properties
-
-<p>An ordered set of inputs used in testing is called an "input vector" or "test
-vector". When an input vector is given to the function under test, the result is
- an "corresponding actual output vector".</p>
-
-<p>In one form of testing, there is a golden model that when given an input
-vector will produce the "corresponding expected output vector". This is also
-called the "golden value". The bit order in the expected output vector is made
-the same as for that of the actual output venctor.</p>
-
-<p>In a common for
-
-
- <p>As a test bench, Mosaic does not define failure functions directly; rather, the tester implements these functions within the tests.</p>
-
- <p>The tester's goal is to identify <span class="term">failures</span>, which represent observable mistakes by the developer. The identified cause of failure is called a <span class="term">fault</span>, and it may relate to specific code lines, logic flaws, or physical hardware issues. In hardware testing, faults might also stem from manufacturing defects or component degradation.</p>
-
- <p>Mosaic is a tool for finding failures. Once a failure is identified, the developer typically uses a debugger to trace the mechanism behind the failure, ultimately locating the fault. While Mosaic aids in failure detection, its primary role is not in the debugging process itself.</p>
-
- </div>
-</body>
-</html>
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