| Revision | 68784b1b114a3ea7ef6fc3d0dca66dd7392b2581 (tree) |
|---|---|
| Time | 2020-03-27 03:52:54 |
| Author | Albert Mietus < albert AT mietus DOT nl > |
| Commiter | Albert Mietus < albert AT mietus DOT nl > |
Moved 'Requirements Traceability' to 'System Engineering'; And some small txt updates
README.rst (diff) SoftwareCompetence/HTLD/index.rst (diff) SoftwareCompetence/index.rst (diff) index.rst (diff) SystemEngineering/RequirementsTraceability/BinSrc/V-IdeaWorkProduct.drawio (diff)
SystemEngineering/RequirementsTraceability/V-IdeaWorkProduct-alfa.png (diff) SystemEngineering/RequirementsTraceability/demo/TraceAll.rst (diff) SystemEngineering/RequirementsTraceability/demo/demo1-tracking.rst (diff) SystemEngineering/RequirementsTraceability/demo/demo1.rst (diff) SystemEngineering/RequirementsTraceability/demo/demo2-tracking.rst (diff) SystemEngineering/RequirementsTraceability/demo/demo2.rst (diff) SystemEngineering/RequirementsTraceability/demo/index.rst (diff) SystemEngineering/RequirementsTraceability/goal/RTM.rst (diff) SystemEngineering/RequirementsTraceability/goal/index.rst (diff) SystemEngineering/RequirementsTraceability/index.rst (diff) SystemEngineering/RequirementsTraceability/notes/forgotten_test.rst (diff) SystemEngineering/RequirementsTraceability/notes/index.rst (diff) SystemEngineering/RequirementsTraceability/notes/particulars-demo1.rst (diff) SystemEngineering/RequirementsTraceability/notes/particulars-demo2.rst (diff) SystemEngineering/index.rst (diff) SoftwareCompetence/RequirementsTraceability/BinSrc/V-IdeaWorkProduct.drawio
SoftwareCompetence/RequirementsTraceability/V-IdeaWorkProduct-alfa.png SoftwareCompetence/RequirementsTraceability/demo/TraceAll.rst SoftwareCompetence/RequirementsTraceability/demo/demo1-tracking.rst SoftwareCompetence/RequirementsTraceability/demo/demo1.rst SoftwareCompetence/RequirementsTraceability/demo/demo2-tracking.rst SoftwareCompetence/RequirementsTraceability/demo/demo2.rst SoftwareCompetence/RequirementsTraceability/demo/index.rst SoftwareCompetence/RequirementsTraceability/goal/RTM.rst SoftwareCompetence/RequirementsTraceability/goal/index.rst SoftwareCompetence/RequirementsTraceability/index.rst SoftwareCompetence/RequirementsTraceability/notes/forgotten_test.rst SoftwareCompetence/RequirementsTraceability/notes/index.rst SoftwareCompetence/RequirementsTraceability/notes/particulars-demo1.rst SoftwareCompetence/RequirementsTraceability/notes/particulars-demo2.rst| @@ -9,11 +9,11 @@ | ||
| 9 | 9 | |
| 10 | 10 | .. sidebar:: Engels & Dutch |
| 11 | 11 | |
| 12 | - * This side is partly in Dutch. | |
| 12 | + * This site is partly in Dutch. | |
| 13 | 13 | * En gedeeltelijk in het Engels |
| 14 | 14 | |
| 15 | 15 | .. MARKER_sidebar_end |
| 16 | - | |
| 16 | + | |
| 17 | 17 | .. glossary:: |
| 18 | 18 | |
| 19 | 19 | Modern Engineering |
| @@ -68,15 +68,15 @@ | ||
| 68 | 68 | ************************** |
| 69 | 69 | .. image:: /_std_settings/static/Needle_Tower_doorzichtig.png |
| 70 | 70 | |
| 71 | -`Tensegrity <https://en.wikipedia.org/wiki/Tensegrity>`__ is a synthesis of the names ‘tensional’ | |
| 72 | -and ‘integrity’. It is based on *“teamwork”* of tension and compression forces. Although the image | |
| 73 | -may look confusing, these structures are really very simple. All you need are some poles, some | |
| 74 | -cable and good engineering. This can result is a beautiful ‘tensegrity-tower’ where the poles | |
| 75 | -almost float in air; as shown `above <https://commons.wikimedia.org/wiki/File:Kenneth_Snelson_Needle_Tower.JPG>`__ | |
| 71 | +`Tensegrity <https://en.wikipedia.org/wiki/Tensegrity>`__ is a synthesis of the names ‘tensional’ and ‘integrity’. It is | |
| 72 | +based on *“teamwork”* of tension and compression forces. Although the image may look confusing, these structures are | |
| 73 | +very simple. All you need are some poles, some cable, and good engineering. This results in a beautiful | |
| 74 | +‘tensegrity-tower’ where the poles almost float in the air; as shown `above | |
| 75 | +<https://commons.wikimedia.org/wiki/File:Kenneth_Snelson_Needle_Tower.JPG>`__ | |
| 76 | 76 | |
| 77 | 77 | It is also a well-known architectural principle for skyscrapers! |
| 78 | 78 | |
| 79 | -For me, it is also a inspiration for Software-Engineering: It should be based of teamwork: a synthesis | |
| 79 | +For me, it is also an inspiration for Software-Engineering: It should be based on teamwork: a synthesis | |
| 80 | 80 | of creative and verifying people. Together with a methodical way-of-working the amplify each |
| 81 | 81 | other. Then, the sky becomes a limit, which is easy! |
| 82 | 82 |
| @@ -5,8 +5,9 @@ | ||
| 5 | 5 | HTLD: *HighTech Linux Delivery* |
| 6 | 6 | =============================== |
| 7 | 7 | |
| 8 | -Here, you will find some blog-style articles about HTLD; An service Sogeti.HighTech (NL) is going to offer. | |
| 8 | +Here you will find some blog-style articles about *HTLD*. | |
| 9 | 9 | |
| 10 | +.. warning:: This section is a bit delayed. | |
| 10 | 11 | |
| 11 | 12 | .. toctree:: |
| 12 | 13 | :glob: |
| @@ -1,1 +0,0 @@ | ||
| 1 | -<mxfile host="Electron" modified="2020-01-30T13:11:43.544Z" agent="Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) draw.io/12.5.3 Chrome/78.0.3904.130 Electron/7.1.9 Safari/537.36" etag="fuFbTfOa3BSZCyzCh0IO" version="12.5.3" type="device"><diagram id="CrEu0Ar_erRfH2SLY0si" name="Page-1">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</diagram></mxfile> | |
| \ No newline at end of file |
| @@ -1,35 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -.. _all_graph: | |
| 4 | - | |
| 5 | -All needs [BigTree] | |
| 6 | -=================== | |
| 7 | - | |
| 8 | -We can also show the relations between all product (cq releases) and it *needs* in one big tree [#forrest]_. | |
| 9 | - | |
| 10 | -.. needflow:: | |
| 11 | - | |
| 12 | -Lessons learned | |
| 13 | ---------------- | |
| 14 | - | |
| 15 | -#. We have at least one test-case for each requirement; as we can clearly see. | |
| 16 | -#. The “puzzling” specification for :need:`CALC2` have an affinity with both the requirements and the test-cases | |
| 17 | -#. The (general) requirements for both calculators are equal. | |
| 18 | -#. Both calculators are akin; :need:`CALC2` is kind of a enhanced version of :need:`CALC1` | |
| 19 | - | |
| 20 | -This “BigTree” gives a global overview of all ‘needs’ and there relations; which gives insight into product and how to | |
| 21 | -test it. It can be generated when the requirements (and other ‘needs’) are affixed with their (outgoing) links. | |
| 22 | -|BR| | |
| 23 | -Even when the number of ‘needs’ becomes huge, this graph can be drawn quite clear -- although you make like to use a big | |
| 24 | -slide of paper. | |
| 25 | - | |
| 26 | -It will directly shown some “isolated” requirements or test, when you forgot to add a link. Also other “curious looking” | |
| 27 | -parts of the drawing may need some attention. As it remarkable often denotes some mistakes. | |
| 28 | - | |
| 29 | -.. rubric:: Footnotes & Links | |
| 30 | - | |
| 31 | -.. [#forrest] In general, and strictly speaking, this graph can be a *“forrest”*: a collection of trees. Mostly, people | |
| 32 | - like to use the term “tree” anyhow. | |
| 33 | - |BR| | |
| 34 | - However as this chapter is about requirements and quality, and I’m trying to convince you to be | |
| 35 | - strict, this footnote seems non-trivial ... |
| @@ -1,89 +0,0 @@ | ||
| 1 | -Requirements Traceability [CALC1] | |
| 2 | -********************************** | |
| 3 | - | |
| 4 | -With the defined ‘needs’, their relations can be shown automatically, or some tables with relevant ones can be | |
| 5 | -listed. Below you will find two examples, for :need:`CALC1`. | |
| 6 | - | |
| 7 | -.. _demo1_graph: | |
| 8 | - | |
| 9 | -A graphical view (“tree”) | |
| 10 | -========================= | |
| 11 | - | |
| 12 | -This view shows the relationship between all kinds of specifications. It is fully automatically generated and will be | |
| 13 | -updated when the specifications change. | |
| 14 | - | |
| 15 | -.. needflow:: | |
| 16 | - :tags: demo1;general | |
| 17 | - | |
| 18 | - | |
| 19 | -Lessons learned | |
| 20 | ---------------- | |
| 21 | - | |
| 22 | -#. This graph clearly shows there are **no tests** for :need:`CALC_DIV`. This is easily overseen as there are four | |
| 23 | - requirements *and* four tests defined. | |
| 24 | -#. When the requirement :need:`CALC_ADD` changes, two tests might need an update. | |
| 25 | -#. Likewise, for the other requirements, it is directly visual where the relations are. | |
| 26 | - | |
| 27 | -This very simple demo has only *one* product with *four* requirements and a few tests. There are no product-variant, no | |
| 28 | -product-increments (“new releases”) and no intermediate (or hierarchical) specifications. As a (deliberate) result, its | |
| 29 | -**Requirements Traceability** is simple. | |
| 30 | -|BR| | |
| 31 | -Still, its easy to forget a test; as I did. Did you noticed it? | |
| 32 | - | |
| 33 | -.. attention:: | |
| 34 | - | |
| 35 | - .. _forgotten_test: | |
| 36 | - | |
| 37 | - The “forgotten test” is intentional in this first demo. It will be hot-fixed in the :ref:`next | |
| 38 | - chapter<test_hotfix>`, and you will see it in the other graphs. | |
| 39 | - | |
| 40 | - Therefore I had to use some “trick” in needs; see :ref:`the notes about the forgotten test<about_forgotten_test>` for | |
| 41 | - more info. | |
| 42 | - | |
| 43 | - | |
| 44 | -The Requirements Matrix (table) | |
| 45 | -=============================== | |
| 46 | - | |
| 47 | -Some people prefer to see the same information in a table; again this one is automatically generated. | |
| 48 | - | |
| 49 | -.. needtable:: | |
| 50 | - :tags: demo1;general | |
| 51 | - :style: table | |
| 52 | - :columns: id;type;title;incoming;outgoing | |
| 53 | - :sort: type | |
| 54 | - | |
| 55 | -.. hint:: | |
| 56 | - | |
| 57 | - For now, ignore the *links* to CALC2 and CALC2_1000ND. Those will be in documented in :ref:`demo2` | |
| 58 | - | |
| 59 | -Lessons learned | |
| 60 | ---------------- | |
| 61 | - | |
| 62 | -#. This generated tabular overview kind of act as an index to all “clickable” *needs*. It’s a great page to bookmark. | |
| 63 | -#. One can even add a status-column (not shown here), or filter on (show only) e.g. test that fails. | |
| 64 | -#. It gives less insight; therefore it good to have both overviews. | |
| 65 | - | |
| 66 | - | |
| 67 | -Everybody understands that when the product-definition changes, the implementation will change too. And, that the | |
| 68 | -test-set will change, partially; by example: new tests will be added. | |
| 69 | -|BR| | |
| 70 | -However, some tests may even become obsolete! | |
| 71 | - | |
| 72 | -So, just re-running all (existing) tests as a regression-test, may not work. The question is: which of all test are | |
| 73 | -related to the changed requirement? | |
| 74 | - | |
| 75 | -With a table as above, the answer is just one click away. | |
| 76 | - | |
| 77 | - | |
| 78 | -Next steps | |
| 79 | -========== | |
| 80 | - | |
| 81 | -When we introduce variants, sprint-increments, multiple (sub)components, libraries, versions, releases, etc, the | |
| 82 | -challenge becomes bigger. Especially when a project-teams grows, it might become a nightmare to know which test has to | |
| 83 | -be re-run, when a specification changes. | |
| 84 | - | |
| 85 | -Unless one uses a (simple) approach as shown above. Then, everybody can just see which *rework* is needed when something | |
| 86 | -“upstream” changes. And, by adding a “status” to each spec, we can even make this visual. | |
| 87 | - | |
| 88 | -See :ref:`demo2` for a bit more complex example: Adding a product-variant and (only) one extra (non-functional) | |
| 89 | -requirement. |
| @@ -1,120 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -.. _demo1: | |
| 4 | - | |
| 5 | -[CALC1] A simple calculator | |
| 6 | -*************************** | |
| 7 | - | |
| 8 | -The specifications are quite trivial ... | |
| 9 | - | |
| 10 | - | |
| 11 | -The product we need | |
| 12 | -=================== | |
| 13 | - | |
| 14 | -.. demo:: Simple Calculator | |
| 15 | - :ID: CALC1 | |
| 16 | - :tags: demo1 | |
| 17 | - | |
| 18 | - For this demo, a simple calculator is used. It should work with integers; and has only a few requirements. See below. | |
| 19 | - | |
| 20 | -We use this extremely simplistic example as you will agree on its requirements. | |
| 21 | - | |
| 22 | - | |
| 23 | -Some general requirements, for all calculators | |
| 24 | -=============================================== | |
| 25 | - | |
| 26 | -.. req:: Generic Add | |
| 27 | - :ID: CALC_ADD | |
| 28 | - :links: CALC1;CALC2 | |
| 29 | - :tags: general | |
| 30 | - | |
| 31 | - All calculators should be able to sum two numbers and show the result. | |
| 32 | - | |
| 33 | -.. req:: Generic Sub | |
| 34 | - :ID: CALC_SUB | |
| 35 | - :links: CALC1;CALC2 | |
| 36 | - :tags: general | |
| 37 | - | |
| 38 | - All calculators should be able to subtract a number form another number. | |
| 39 | - | |
| 40 | -.. req:: Generic Multiply | |
| 41 | - :ID: CALC_MULT | |
| 42 | - :links: CALC1;CALC2 | |
| 43 | - :tags: general | |
| 44 | - | |
| 45 | - All calculators should be able to multiply two numbers. | |
| 46 | - | |
| 47 | -.. req:: Generic Divide | |
| 48 | - :ID: CALC_DIV | |
| 49 | - :links: CALC1;CALC2 | |
| 50 | - :tags: general | |
| 51 | - | |
| 52 | - All calculators should be able to divide two numbers. | |
| 53 | - | |
| 54 | - | |
| 55 | -Add this is how we test it | |
| 56 | -========================== | |
| 57 | - | |
| 58 | -As we have defined only general requirements, we only need some generic tests. | |
| 59 | - | |
| 60 | -.. test:: Basic addition test | |
| 61 | - :id: CALC_TEST_ADD_1 | |
| 62 | - :links: CALC_ADD;CALC2_1000ND | |
| 63 | - :tags: general | |
| 64 | - | |
| 65 | - Sum two numbers and verify the result is correct. | |
| 66 | - | |
| 67 | - By example: Add ``2`` and ``5`` and check the result is **7** | |
| 68 | - | |
| 69 | -.. test:: Big addition test | |
| 70 | - :id: CALC_TEST_ADD_2 | |
| 71 | - :links: CALC_ADD;CALC2_1000ND | |
| 72 | - :tags: general | |
| 73 | - | |
| 74 | - Add the numbers ``2222`` and ``5555`` and check the result is **7777** | |
| 75 | - | |
| 76 | -.. test:: Subtract test | |
| 77 | - :id: CALC_TEST_SUB_1 | |
| 78 | - :links: CALC_SUB;CALC2_1000ND | |
| 79 | - :tags: general | |
| 80 | - | |
| 81 | - Feed two numbers to the calculators, in the right order and verify the result. | |
| 82 | - |BR| | |
| 83 | - E.g: | |
| 84 | - | |
| 85 | - * Subtract ``5`` from ``7`` and check the result is **2** | |
| 86 | - * Subtract ``5555`` from ``7777`` and check the result is **2222** | |
| 87 | - | |
| 88 | - .. note:: | |
| 89 | - | |
| 90 | - Here we specify two test in one test-requirement; just to show another style | |
| 91 | - | |
| 92 | -.. test:: Multiplication test | |
| 93 | - :id: CALC_TEST_MULT_1 | |
| 94 | - :links: CALC_MULT;CALC2_1000ND | |
| 95 | - :tags: general | |
| 96 | - | |
| 97 | - You get the idea ... | |
| 98 | - | |
| 99 | - | |
| 100 | -Experience practice | |
| 101 | -=================== | |
| 102 | - | |
| 103 | -#. There are several kinds of ‘needs’. | |
| 104 | - |BR| | |
| 105 | - Here we use the toplevel `Demonstrator` (as it is not a real product), `Requirement` and `Test_Case`; later we will | |
| 106 | - introduce `Specification` too. More kinds & levels can be configured. | |
| 107 | -#. Every ‘need’ should have an unique and stable ID; this label is used to link other ‘needs’. | |
| 108 | -#. Some ‘needs’ are linked to an “earlier/higher” ‘need’. | |
| 109 | - |BR| | |
| 110 | - You can see such an outgoing-link in e.g the requirements (You might need to “open” the details-row) | |
| 111 | -#. Each outgoing-link will automatically result in an incoming-link on the references need. (Again, open the | |
| 112 | - details-row, to be able to “follow” it in the ‘forward’ direction). | |
| 113 | - | |
| 114 | - | |
| 115 | - | |
| 116 | -.. hint:: | |
| 117 | - | |
| 118 | - This article uses ‘sphinx-doc’ with the ‘needs’ plugin to define requirement. This is a text-based (and so | |
| 119 | - version-controllable) tool; therefore it is painless to show the details of how it works; that is done in | |
| 120 | - :ref:`RT_Particulars_demo1` |
| @@ -1,71 +0,0 @@ | ||
| 1 | -Requirements Traceability [CALC2] | |
| 2 | -********************************* | |
| 3 | - | |
| 4 | -As in “:doc:`demo1`”, we can automatically generate the an overview of the requirements. | |
| 5 | - | |
| 6 | -The tree view | |
| 7 | -============= | |
| 8 | - | |
| 9 | -.. _demo2_graph: | |
| 10 | - | |
| 11 | -.. needflow:: | |
| 12 | - :tags: demo2;general | |
| 13 | - | |
| 14 | -Lessons learned | |
| 15 | ---------------- | |
| 16 | - | |
| 17 | -#. We can directly see that specification :need:`CALC2_1000ND` influences all existing test-cases. | |
| 18 | -#. Each test *depends* on both a (functional) requirement and a (non-functional) specification (at least in this case). | |
| 19 | -#. The requirements-relations can become more complicated, even by adding **only** *one* requirement! | |
| 20 | - | |
| 21 | -Can you imagine what will happen when we add a handful of requirements to the calculator (*memory*, *square-root*, | |
| 22 | -*powers*)? Or, a few more non-functionals (*speed-of-operation*, *floats*). Then the complexity quickly raises even for | |
| 23 | -such a simple product. And it becomes hard to predict which tests have to be adapted or rerun. | |
| 24 | - | |
| 25 | -Likewise, when a few requirements become altered in an upcoming sprint: can you predict which tests will have to change? | |
| 26 | -A graph, as above, will certainly help in working that out. | |
| 27 | - | |
| 28 | - | |
| 29 | -The table view | |
| 30 | -============== | |
| 31 | - | |
| 32 | -.. needtable:: | |
| 33 | - :tags: demo2,general | |
| 34 | - :style: table | |
| 35 | - :columns: id;type;title;incoming;outgoing | |
| 36 | - :sort: type | |
| 37 | - | |
| 38 | - | |
| 39 | -Lessons learned | |
| 40 | ---------------- | |
| 41 | - | |
| 42 | -#. The advantage of a table-view is that is will only grow in one direction: it just becomes a bit longer. | |
| 43 | -#. Even for a big project, it’s a great page to bookmark and use as a start-page for all kinds of requirements. | |
| 44 | - |BR| | |
| 45 | - Probably, you like to split it into the kind of ‘need’. | |
| 46 | - | |
| 47 | -It would be great to show a classical `Requirements Traceability matrix | |
| 48 | -<https://en.wikipedia.org/wiki/Traceability_matrix>`_ (RTM) too. This table shows the relations between all the | |
| 49 | -requirements and all the tests. | |
| 50 | - | |
| 51 | -.. note:: | |
| 52 | - | |
| 53 | - As ‘needs’ currently does not support classical *RTM*\s, I can’t generate/show it here. See :ref:`a manually made | |
| 54 | - TRM <RT_RTM_CALC2>` to get the idea. As you will see: it’s easy to read. | |
| 55 | - |BR| | |
| 56 | - However, its quite hard to grasp deep relations; then the tree above is more helpfull. | |
| 57 | - | |
| 58 | -Next steps | |
| 59 | -========== | |
| 60 | - | |
| 61 | -We might add more product-variants, or more sprints to convince you that requirement-traceability is important. The only | |
| 62 | -effect is more pages with (trivial) requirements, specifications or other ‘needs’. And the same to generated overviews; | |
| 63 | -the later cost only a small number of lines, independent of the size of the product. So we will leave that as an | |
| 64 | -exercise. | |
| 65 | - | |
| 66 | -As a bonus, we will show you one more generated graph: :ref:`all_graph`, combining the :need:`CALC1` and :need:`CALC2` | |
| 67 | -requirements. | |
| 68 | - | |
| 69 | -Whenever you have more quistions, you can email me :sogeti-email:`Albert.Mietus`. | |
| 70 | - | |
| 71 | - |
| @@ -1,95 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -.. _demo2: | |
| 4 | - | |
| 5 | -[CALC2] The exact calculator | |
| 6 | -**************************** | |
| 7 | - | |
| 8 | -This demo is just a bit more complicated then :ref:`demo1`: this product-variant has *one* extra requirement. | |
| 9 | - | |
| 10 | -A bit more complicated product | |
| 11 | -============================== | |
| 12 | - | |
| 13 | -.. demo:: Exact Calculator | |
| 14 | - :ID: CALC2 | |
| 15 | - :tags: demo2 | |
| 16 | - :links: CALC1 | |
| 17 | - | |
| 18 | - This calculator should work with `Fractional Numbers <https://en.wikipedia.org/wiki/Fraction_(mathematics)>`_, and be | |
| 19 | - exact for very big numbers; as defined in :need:`CALC2_1000ND` | |
| 20 | - | |
| 21 | - .. warning:: | |
| 22 | - | |
| 23 | - This implies ``floats`` are not possible in the implementation | |
| 24 | - | |
| 25 | - | |
| 26 | -The extra requirement | |
| 27 | -===================== | |
| 28 | - | |
| 29 | -.. spec:: Big fractional numbers | |
| 30 | - :id: CALC2_1000ND | |
| 31 | - :links: CALC_ADD;CALC_SUB;CALC_MULT;CALC_DIV; CALC2 | |
| 32 | - :tags: demo2 | |
| 33 | - | |
| 34 | - The :need:`CALC2` should work with fractions; where nominator and denominator can be very long: up to **1000 | |
| 35 | - digits**. | |
| 36 | - | |
| 37 | -.. _test_hotfix: | |
| 38 | - | |
| 39 | -Hotfix the missing test | |
| 40 | ------------------------ | |
| 41 | - | |
| 42 | -We also *repair* the missing test in demo1, but only for demo2 (Because it is still a *demo!*). | |
| 43 | - | |
| 44 | -.. test:: DIV test (demo2 only) | |
| 45 | - :id: CALC2_TEST_DIV_1 | |
| 46 | - :links: CALC_DIV; CALC2_1000ND | |
| 47 | - :tags: demo2 | |
| 48 | - | |
| 49 | - Subtract ``1/3`` from ``1/2`` and check the result is **1/6**. | |
| 50 | - | |
| 51 | - .. note:: | |
| 52 | - | |
| 53 | - This test is was intentionally “forgotten” as explained in the :ref:`forgotten test <forgotten_test>`. | |
| 54 | - | |
| 55 | - Therefore it is only added for the :need:`CALC2`. See :ref:`the notes about the forgotten | |
| 56 | - test<about_forgotten_test>` for more info. | |
| 57 | - | |
| 58 | -How to test? | |
| 59 | -============ | |
| 60 | - | |
| 61 | -The :need:`CALC2_1000ND` requirement is a good example of a “*nonfunctional*” (actually: a non-distributable) | |
| 62 | -specification. It is valid for all other requirements; all parts of the implementation should adhere to it. | |
| 63 | - | |
| 64 | -Testing this requirement is also different too. The same tests are valid: we have to add, subtract, multiply and | |
| 65 | -divide. | |
| 66 | -|BR| | |
| 67 | -Only, now we have to use other numbers; really big ones! | |
| 68 | - | |
| 69 | -Traditionally | |
| 70 | -------------- | |
| 71 | - | |
| 72 | -In the traditional world, using the TMAP-terms, this approximately come down to: | |
| 73 | - | |
| 74 | -* Reuse the *logic test*. | |
| 75 | -* Change a *physical test* (or add one). | |
| 76 | - | |
| 77 | -Modern | |
| 78 | ------- | |
| 79 | - | |
| 80 | -When using an agile test-automation framework this implies | |
| 81 | - | |
| 82 | -* The ATS (Automated Test Script) isn’t altered. | |
| 83 | -* Some “Test-Vectors” (or test-data) is added: the big-fractions. | |
| 84 | - | |
| 85 | - | |
| 86 | -Experience practice | |
| 87 | -=================== | |
| 88 | - | |
| 89 | -#. It is possible to have multiply “toplevel” ‘needs’. Here, that are ``Demonstrators``, but it possible to use | |
| 90 | - `Products`, `Variants`, and/or `Releases` etc, as well. | |
| 91 | -#. Here, a new kind of ‘need’ is introduced: ``Specification``. As you will see on the next page, it influences not only | |
| 92 | - the implementation, but also testing. | |
| 93 | -#. In the ‘details-row’, you can see it has (outgoing) links to many (all) earlier requirements. | |
| 94 | - | |
| 95 | - |
| @@ -1,50 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -.. _RT_demo: | |
| 4 | - | |
| 5 | -********************** | |
| 6 | -Demo: Some calculators | |
| 7 | -********************** | |
| 8 | - | |
| 9 | -This chapter contains a few demonstrations of the Requirements Traceability concept. | |
| 10 | - | |
| 11 | -We start with a very simple product: the :need:`CALC1`; with only a few generic requirements and tests. By defining | |
| 12 | -those “needs”[#needs]_ it becomes possible to show a (generated) :ref:`graph <demo1_graph>` with the relations between | |
| 13 | -them. |BR| Probably, you will be able to implement and verify this simple product without (formal) | |
| 14 | -requirements-traceability; but it gives a nice introduction to the concept. | |
| 15 | - | |
| 16 | - | |
| 17 | -Then, a new product the :need:`CALC2` is defined, in the same way. | |
| 18 | -|BR| | |
| 19 | -Even it has only one (*puzzling*) additional requirement; that one makes both the implementation and the validation | |
| 20 | -burdensome. And changes the test-cases completely; as shown in :ref:`its requirement-traceability graph <demo2_graph>`. | |
| 21 | - | |
| 22 | - | |
| 23 | -Likewise, we could add more demo’s with more and more specifications, tests and *need* at multiple-levels; but you will | |
| 24 | -get the idea: By simple ‘defining’ the needs, it becomes possible to get insight; independent of the size of the products | |
| 25 | -or the numbers of specifications. | |
| 26 | - | |
| 27 | -Finally, an :ref:`overall graph <all_graph>` is shown, with all the products, all the tests, and all the connecting | |
| 28 | -*needs*. | |
| 29 | - | |
| 30 | -.. rubric:: Content | |
| 31 | -.. toctree:: | |
| 32 | - :glob: | |
| 33 | - :maxdepth: 3 | |
| 34 | - | |
| 35 | - demo1 | |
| 36 | - demo1-tracking | |
| 37 | - demo2 | |
| 38 | - demo2-tracking | |
| 39 | - TraceAll | |
| 40 | - | |
| 41 | -.. rubric:: Footnotes & Links | |
| 42 | - | |
| 43 | -.. [#needs] The universal term ‘*need*’ is used for all kinds of requirements, specifications, test-specs, etc. | |
| 44 | - This name comes from the “needs” extension to “sphinx-docs” that we use in this demo. | |
| 45 | - | |
| 46 | -Needs: | |
| 47 | - http://sphinxcontrib-needs.readthedocs.io | |
| 48 | - | |
| 49 | -Sphinx: | |
| 50 | - https://www.sphinx-doc.org/ |
| @@ -1,60 +0,0 @@ | ||
| 1 | -.. _RT_RTM_CALC2: | |
| 2 | - | |
| 3 | -The classical Requirements Traceability Matrix | |
| 4 | -================================================ | |
| 5 | - | |
| 6 | -Most literature about requirements-traceability focus on the Requirements Traceability Matrix [#RTM]_. This table gives the relation between the (high level) requirements versus all test. As ‘needs’ can’t generate this table (yet), I have created one as example. | |
| 7 | - | |
| 8 | -With this overview one get insight about which test are needed to verify one requirement. Sometimes it explicitly counts the number of available tests pro requirement too. Albeit that is a nice result, the ATM isn’t that useful in an agile environment. When a requirement is added, ore one changes, the RTM itself gives little help to update the table. | |
| 9 | - | |
| 10 | - | |
| 11 | -.. list-table:: RTM for the :need:`CALC2` | |
| 12 | - :class: RTM-rotated-head | |
| 13 | - :header-rows: 1 | |
| 14 | - :widths: 25 15 15 15 15 15 | |
| 15 | - | |
| 16 | - * - Test\\Req | |
| 17 | - - :need:`CALC_ADD` | |
| 18 | - - :need:`CALC_SUB` | |
| 19 | - - :need:`CALC_MULT` | |
| 20 | - - :need:`CALC_DIV` | |
| 21 | - - :need:`CALC2_1000ND` | |
| 22 | - * - :need:`CALC_TEST_ADD_1` | |
| 23 | - - X | |
| 24 | - - | |
| 25 | - - | |
| 26 | - - | |
| 27 | - - X | |
| 28 | - * - :need:`CALC_TEST_ADD_2` | |
| 29 | - - X | |
| 30 | - - | |
| 31 | - - | |
| 32 | - - | |
| 33 | - - X | |
| 34 | - * - :need:`CALC_TEST_SUB_1` | |
| 35 | - - | |
| 36 | - - X | |
| 37 | - - | |
| 38 | - - | |
| 39 | - - X | |
| 40 | - * - :need:`CALC_TEST_MULT_1` | |
| 41 | - - | |
| 42 | - - | |
| 43 | - - X | |
| 44 | - - | |
| 45 | - - X | |
| 46 | - * - :need:`CALC2_TEST_DIV_1` | |
| 47 | - - | |
| 48 | - - | |
| 49 | - - | |
| 50 | - - X | |
| 51 | - - X | |
| 52 | - | |
| 53 | - | |
| 54 | - | |
| 55 | -.. rubric:: Footnotes & Links | |
| 56 | - | |
| 57 | -.. [#RTM] Often shorthanded to RTM, or simle “Traceability Matrix”, as wikipedia does. | |
| 58 | - | |
| 59 | -Wikipedia on RTM: | |
| 60 | - https://en.wikipedia.org/wiki/Traceability_matrix |
| @@ -1,41 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -***** | |
| 4 | -Goals | |
| 5 | -***** | |
| 6 | - | |
| 7 | - “Requirements traceability is a sub-discipline of requirements management within software development and systems | |
| 8 | - engineering ...” | |
| 9 | - | |
| 10 | - “... is defined as "the ability to describe and follow the life of a requirement in both a forwards and backwards direction” | |
| 11 | - | |
| 12 | - --- https://en.wikipedia.org/wiki/Requirements_traceability | |
| 13 | - | |
| 14 | -There are many reasons to enroll requirement-management and -traceability. | |
| 15 | - | |
| 16 | -* First of all, it’s a good habit: without an objective it hard to succeed. | |
| 17 | - *How can a system pass an acceptance-test when it is not clear what the (current) requirements are?* | |
| 18 | -* Often more urgent: in many domains, it is demanded by law or standardisation committees. In healthcare, automotive and | |
| 19 | - aerospace “safety” is mandatory. Standard like IEC61508, and (A)SIL more or less demand a process with proper | |
| 20 | - requirement traceability. | |
| 21 | - | |
| 22 | -With the uprise of lean, agile and scrum, there is a tendency to skip less popular steps (and expensive roles) and to | |
| 23 | -trust on craftsmanship. This implies the traditional 'requirement management' approach has to change. And also, that more | |
| 24 | -people should be involved. | |
| 25 | - | |
| 26 | -This chapter gives you an introduction into 'tracking requirements', in a lean, agile fashion. | |
| 27 | -|BR| | |
| 28 | -After this *lecture*, you should understand how to annex (written) requirements and other specifications, to be able to | |
| 29 | -link them with test-cases. You should be able to visualize those relations, to get insight into which tests are needed | |
| 30 | -for a specific product-release. (And the other way around.) Besides, you should be able to apply this manually, for | |
| 31 | -moderately simple products. For big, complicated products, you probably need a bit more experience and the assistance of | |
| 32 | -a standardized process and mayhap a tool, to make it lean. | |
| 33 | - | |
| 34 | -.. toctree:: | |
| 35 | - :hidden: | |
| 36 | - :glob: | |
| 37 | - | |
| 38 | - * | |
| 39 | - | |
| 40 | - | |
| 41 | - |
| @@ -1,55 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -========================= | |
| 4 | -Requirements Traceability | |
| 5 | -========================= | |
| 6 | - | |
| 7 | -.. post:: 2020/02/15 | |
| 8 | - :tags: SysEng | |
| 9 | - :category: lecture | |
| 10 | - :location: Vianen | |
| 11 | - :language: en | |
| 12 | - | |
| 13 | - :study-time: 1 hour | |
| 14 | - | |
| 15 | - Requirement-Management, and especially *“Tracking Requirements”* isn’t that complicated, but it needs some | |
| 16 | - discipline. Often that discipline is *replaced* by a tool, which is encouraged by tool-vendors. That hardly ever | |
| 17 | - works. | |
| 18 | - | |
| 19 | - This blog introduces requirements traceability in a conceptual, but pragmatic way. It shows :ref:`--as a | |
| 20 | - demo--<RT_demo>` what a team has to do (defining requirements and describing the relations) and what the benefit | |
| 21 | - is. It assumes a (more or less) agile way-of-work and shows how it can become lean. A small investment in good | |
| 22 | - requirements definitions makes validations a lot easier. | |
| 23 | - | |
| 24 | - And yes, it used a tool: a free one; as part of the documentation-system that is used for this side. An structured, | |
| 25 | - version-controllable, textual way to write documentation, including all requirements. With a plugin that | |
| 26 | - can visualize all specifications and their relations. | |
| 27 | - |BR| | |
| 28 | - Those *“particulars”* will be shown too. | |
| 29 | - | |
| 30 | -.. admonition:: Summary (testers view) | |
| 31 | - | |
| 32 | - .. image:: ./V-IdeaWorkProduct-alfa.png | |
| 33 | - :width: 33% | |
| 34 | - :align: right | |
| 35 | - | |
| 36 | - * For a simple development cycle, it easy to trace the validation of the product: | |
| 37 | - *All features should be covered by a test, and all should pass*. | |
| 38 | - * When multiple products --or multiple releases-- are mandatory, this becomes quickly ambiguous: | |
| 39 | - *Some tests have to pass, and only the essential specifications need test-cases.* | |
| 40 | - * Then ‘requirements traceability’ becomes crucial: | |
| 41 | - **It gives insight into which ‘specs’ are required by each product/release and which tests are essential.** | |
| 42 | - * This article (as part of a workshop) shows a down-to-earth demo of how you set-up the ‘requirements traceability’ | |
| 43 | - and how to use it. | |
| 44 | - * We use the ‘tester view’: Be able to demonstrate the *product* **does** what was *aimed for*! | |
| 45 | - | |
| 46 | -.. rubric:: Content | |
| 47 | -.. toctree:: | |
| 48 | - :maxdepth: 2 | |
| 49 | - | |
| 50 | - goal/index | |
| 51 | - demo/index | |
| 52 | - notes/index | |
| 53 | - | |
| 54 | - | |
| 55 | -More info? Contact Albert: :sogeti-email:`Albert.Mietus`; +31 (0)6 526 592 60. Or use the comment section below. |
| @@ -1,63 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus 2020 | |
| 2 | - | |
| 3 | -.. _about_forgotten_test: | |
| 4 | - | |
| 5 | - | |
| 6 | - | |
| 7 | -The forgotten test | |
| 8 | -================== | |
| 9 | - | |
| 10 | -Intentionally, one test is :ref:`“forgotten” <forgotten_test>` for the first demo. However it is needed and “hot-fixed” for :ref:`the second one <test_hotfix>`. | |
| 11 | -|BR| | |
| 12 | -Surely this is not typical in one documentation-release. | |
| 13 | - | |
| 14 | -Therefor some *tricks* are used to show this in one go. Those tricks are documented here. | |
| 15 | - | |
| 16 | -By adding some ‘tags’ to the various requirements one can filter on those when generating an overview. And only show the intend ones. This can be useful by-example to labels ‘needs’ for a specific release or product-variant. Here, used a bit more extensive. | |
| 17 | - | |
| 18 | -Particulars | |
| 19 | ------------ | |
| 20 | - | |
| 21 | -As typical each product has it “own” tag: ``demo1`` or ``demo2``. As we have some tests that should be selected on one page, but not on another we use an extra tag: ``general``. | |
| 22 | -|BR| | |
| 23 | -Most test-cases are labeled with ``general``, as are the generic requirements. Whereas the “forgotten” test :need:`CALC2_TEST_DIV_1` is labeled ``demo2`` | |
| 24 | - | |
| 25 | -.. code-block:: rst | |
| 26 | - :emphasize-lines: 4,11 | |
| 27 | - | |
| 28 | - .. test:: Basic addition test | |
| 29 | - :id: CALC_TEST_ADD_1 | |
| 30 | - :links: CALC_ADD;CALC2_1000ND | |
| 31 | - :tags: general | |
| 32 | - | |
| 33 | - Sum two numbers .... | |
| 34 | - | |
| 35 | - .. test:: DIV test (demo2 only) | |
| 36 | - :id: CALC2_TEST_DIV_1 | |
| 37 | - :links: CALC_DIV; CALC2_1000ND | |
| 38 | - :tags: demo2 | |
| 39 | - | |
| 40 | - Subtract ... | |
| 41 | - | |
| 42 | - | |
| 43 | -Now it becomes possible to show the relations with, or without that test. | |
| 44 | - | |
| 45 | -In the :ref:`first demo <demo1_graph>`, we filter on ‘demo1` and ‘general’. So we get the product, the generic requirements and most tests. But not the forgotten one. | |
| 46 | - | |
| 47 | -.. code-block:: rst | |
| 48 | - :emphasize-lines: 2 | |
| 49 | - | |
| 50 | - .. needflow:: | |
| 51 | - :tags: demo1;general | |
| 52 | - | |
| 53 | -*After* we have “hot-fixed” the test, we can simply select all test for the :ref:`second graph <demo1_graph>` | |
| 54 | - | |
| 55 | -.. code-block:: rst | |
| 56 | - :emphasize-lines: 2 | |
| 57 | - | |
| 58 | - .. needflow:: | |
| 59 | - :tags: demo2;general | |
| 60 | - | |
| 61 | -Actually, we didn’t really “hot fix” it; it was only defined for demo2. But linked to a general requirements. | |
| 62 | - | |
| 63 | -Normally, you don’t need to use this kind of tricks; it better to not forget a test, or really fix it. |
| @@ -1,35 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | - | |
| 3 | -.. _RT_notes: | |
| 4 | - | |
| 5 | -*********************** | |
| 6 | -Particulars of ‘needs’ | |
| 7 | -*********************** | |
| 8 | - | |
| 9 | -The main objective of this blog is introducing “Requirements Traceability” in general; especially in an agile | |
| 10 | -environment or when a roadmap of product-releases exists. That is done demoing :need_count:`type=='demo'` products, | |
| 11 | -:need_count:`type=='req'` requirements, :need_count:`type=='spec'` specification, and :need_count:`type=='test'` | |
| 12 | -tests. Also, some generated graphs and tables are shown. | |
| 13 | - | |
| 14 | -Those ‘needs’ aren’t just text; they are ‘life’ defined and generated by a plugin called *needs* in the *sphinx-doc* | |
| 15 | -documenting tool; which is just to generate this website. Partly, because I like this toolset. But also to show you that | |
| 16 | -is can be done. | |
| 17 | - | |
| 18 | -And despite this blog is not about (learning) a tool, this section will go a step deeper: It will show you how it is | |
| 19 | -done; without becoming a tutorial on ‘sphinx’ or ‘needs’. | |
| 20 | -|BR| | |
| 21 | -Possible, you like it and would love to play with the demo. Or, you are inquisitive whether this is truly | |
| 22 | -*not text-only*. | |
| 23 | - | |
| 24 | -The following pages show some excerpts of the *“RST-code”*, that is used to defined all ‘needs’. Feel free to | |
| 25 | -study the ‘sources’ and learn from it. | |
| 26 | -|BR| | |
| 27 | -I will even document the tricks needed for “:ref:`about_forgotten_test`”. | |
| 28 | - | |
| 29 | -.. toctree:: | |
| 30 | - | |
| 31 | - particulars-demo1 | |
| 32 | - particulars-demo2 | |
| 33 | - forgotten_test | |
| 34 | - | |
| 35 | - |
| @@ -1,90 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus 2020 | |
| 2 | - | |
| 3 | -.. _RT_Particulars_demo1: | |
| 4 | - | |
| 5 | -===================== | |
| 6 | -Particulars for CALC1 | |
| 7 | -===================== | |
| 8 | - | |
| 9 | -.. hint:: | |
| 10 | - | |
| 11 | - You should skip the particulars passages, when you not interested in the technical details of this particular tool. | |
| 12 | - | |
| 13 | - | |
| 14 | -A product (start of the V) | |
| 15 | -========================== | |
| 16 | - | |
| 17 | -To define the :need:`CALC1` product the following is described: | |
| 18 | - | |
| 19 | -.. code-block:: rst | |
| 20 | - | |
| 21 | - .. demo:: Simple Calculator | |
| 22 | - :ID: CALC1 | |
| 23 | - | |
| 24 | - For this demo ... | |
| 25 | - | |
| 26 | -You can see this product has the ID ``CALC1`` and some text. No links are needed, they will be added automatically by | |
| 27 | -requirements, which are described “later”. | |
| 28 | - | |
| 29 | - | |
| 30 | -With requirements (one step down into the V) | |
| 31 | --------------------------------------------- | |
| 32 | - | |
| 33 | -The requirement :need:`CALC_ADD` has an ID too, and a link to the products it is valid for; here `CALC1` and `CALC2`. | |
| 34 | - | |
| 35 | -.. code-block:: rst | |
| 36 | - :emphasize-lines: 2,3 | |
| 37 | - | |
| 38 | - .. req:: Generic Add | |
| 39 | - :ID: CALC_ADD | |
| 40 | - :links: CALC1;CALC2 | |
| 41 | - | |
| 42 | - All calculators ... able to sum ... | |
| 43 | - | |
| 44 | -All requirements are described in the same way, as well as each individual requirement can be linked to one or more | |
| 45 | -products (or product-variants). As this demo has (already) two products, and this requirement is valid for both; you see | |
| 46 | -them listed here. | |
| 47 | - | |
| 48 | - | |
| 49 | -And tests (the other side of the V) | |
| 50 | ------------------------------------ | |
| 51 | - | |
| 52 | -A test (-case) is also a ‘need’. It is defined in the same approach: a title, an ID and the links to all requirements that | |
| 53 | -are tested by this one. Here, that is only `CALC_ADD`. | |
| 54 | - | |
| 55 | -.. code-block:: rst | |
| 56 | - :emphasize-lines: 2 | |
| 57 | - | |
| 58 | - .. test:: Basic addition test | |
| 59 | - :id: CALC_TEST_ADD_1 | |
| 60 | - :links: CALC_ADD | |
| 61 | - | |
| 62 | - Sum two numbers and verify ... | |
| 63 | - | |
| 64 | -Again, the same construction is repeated for all tests. | |
| 65 | - | |
| 66 | - | |
| 67 | -Tracing the requirements | |
| 68 | -======================== | |
| 69 | - | |
| 70 | -Generaring the “requirements tree” as displayed :ref:`here <demo1_graph>` is very easy: | |
| 71 | - | |
| 72 | -.. code-block:: rst | |
| 73 | - :emphasize-lines: 1 | |
| 74 | - | |
| 75 | - .. needflow:: | |
| 76 | - :tags: demo1;general | |
| 77 | - | |
| 78 | -Likewise is showing the table overview: | |
| 79 | - | |
| 80 | -.. code-block:: rst | |
| 81 | - :emphasize-lines: 1 | |
| 82 | - | |
| 83 | - .. needtable:: | |
| 84 | - :tags: demo1;general | |
| 85 | - :style: table | |
| 86 | - :columns: id;type;title;incoming;outgoing | |
| 87 | - :sort: type | |
| 88 | - | |
| 89 | - | |
| 90 | -See the documentations of needs (https://sphinxcontrib-needs.readthedocs.io) for details on all options. |
| @@ -1,102 +0,0 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus 2020 | |
| 2 | - | |
| 3 | -.. _RT_Particulars_demo2: | |
| 4 | - | |
| 5 | -====================== | |
| 6 | - Particulars for CALC2 | |
| 7 | -====================== | |
| 8 | - | |
| 9 | -.. hint:: | |
| 10 | - | |
| 11 | - Again, you can skip the **particulars** passage when you have no curiosity in the technicalities of ‘needs’ itself. | |
| 12 | - | |
| 13 | - | |
| 14 | -Describing requirements | |
| 15 | -======================= | |
| 16 | - | |
| 17 | -The describing text of any requirement (in ‘needs’) is standard **rst** *(reStructuredText)*. So it can use hyperlinks, | |
| 18 | -forward-references to other needs and even warning-admonitions. | |
| 19 | -|BR| | |
| 20 | -The full textual definition of :need:`CALC2` is: | |
| 21 | - | |
| 22 | -.. code-block:: rst | |
| 23 | - :emphasize-lines: 6-7, 9-11 | |
| 24 | - | |
| 25 | - .. demo:: Exact Calculator | |
| 26 | - :ID: CALC2 | |
| 27 | - :tags: demo2 | |
| 28 | - :links: CALC1 | |
| 29 | - | |
| 30 | - This calculator should work with `Fractional Numbers <https://en.wikipedia.org/wiki/Fraction_(mathematics)>`_, and be | |
| 31 | - exact for very big numbers; as defined in :need:`CALC2_1000ND` | |
| 32 | - | |
| 33 | - .. warning:: | |
| 34 | - | |
| 35 | - This implies ``floats`` are not possible in the implementation | |
| 36 | - | |
| 37 | - | |
| 38 | -The added specification | |
| 39 | -======================= | |
| 40 | - | |
| 41 | -Like all other ‘needs’, the specification for :need:`CALC2_1000ND` is straightforward. It links to “earlier” | |
| 42 | -requirements. | |
| 43 | - | |
| 44 | -.. code-block:: rst | |
| 45 | - :emphasize-lines: 3 | |
| 46 | - | |
| 47 | - .. spec:: Big fractional numbers | |
| 48 | - :id: CALC2_1000ND | |
| 49 | - :links: CALC_ADD;CALC_SUB;CALC_MULT;CALC_DIV | |
| 50 | - :tags: demo2 | |
| 51 | - | |
| 52 | - The :need:`CALC2` ... | |
| 53 | - | |
| 54 | -.. tip:: | |
| 55 | - | |
| 56 | - * There is no *prescribed* order how the individual ‘needs’ can be linked. It kind of feels more natural to link to | |
| 57 | - “higher level” (in the V-model) ‘needs’, and to one that are described “earlier” (in project-time). But when you | |
| 58 | - can link them in any order. | |
| 59 | - | |
| 60 | - * Similar, a ‘need’ can link to any other ‘need’, independent of its type. | |
| 61 | - |BR| | |
| 62 | - Above we have used a `spec`, to add this requirement; but a normal `req` (requirement) is possible too. You can | |
| 63 | - configure any kind of ‘needs’, as you like. | |
| 64 | - | |
| 65 | - * You can even *export* ‘needs’ in one document and *import* them in another. For big projects with many levels of | |
| 66 | - modules, and so, specification-documents, this is typical behaviour. In this small calculator example tha is not | |
| 67 | - used. | |
| 68 | - | |
| 69 | -Tracing relations | |
| 70 | -================= | |
| 71 | - | |
| 72 | -To be able to trace whetter some test need to be adapted, we only have to add some “links” between the relevant test and the | |
| 73 | -additional (test) specification. | |
| 74 | - | |
| 75 | -In :need:`CALC2_1000ND` that is done by adding some (outgoing) links to the existing tests. You may have to open/click the see the details row. | |
| 76 | - | |
| 77 | -.. note:: | |
| 78 | - | |
| 79 | - The incoming links are added automatically. | |
| 80 | - | |
| 81 | -Inheriting links | |
| 82 | ----------------- | |
| 83 | - | |
| 84 | -Currently, there is no *inherit option*, One can’t specify that the requirements for `CALC1` are also valid for | |
| 85 | -`CALC2`. | |
| 86 | - | |
| 87 | -* By linking the two ``Demonstrators`` we get (almost) the same. | |
| 88 | -* Alternatively, you can just add the links manually. | |
| 89 | -* *(or you can use the export/import option and a simple script to modify the json file)* | |
| 90 | - | |
| 91 | -.. tip:: | |
| 92 | - | |
| 93 | - As ‘needs’ is an actively maintained open-source project, ‘inheriting’ may be added in a next release. | |
| 94 | - |BR| | |
| 95 | - Even by you:-) | |
| 96 | - | |
| 97 | -The hotfix | |
| 98 | -========== | |
| 99 | - | |
| 100 | -See :ref:`the notes about the forgotten test<about_forgotten_test>` for the particulars on how to :ref:`forget | |
| 101 | -<forgotten_test>` and :ref:`add <test_hotfix>` a test in one document. | |
| 102 | - |
| @@ -1,11 +1,12 @@ | ||
| 1 | -.. Copyright (C) ALbert Mietus & Sogeti.HT; 2019 | |
| 1 | +.. Copyright (C) ALbert Mietus; 2019, 2020 | |
| 2 | 2 | |
| 3 | +------------------- | |
| 3 | 4 | Software competency |
| 4 | 5 | ------------------- |
| 5 | 6 | |
| 6 | 7 | .. toctree:: |
| 7 | 8 | :maxdepth: 2 |
| 8 | 9 | |
| 10 | + HTLD/index | |
| 9 | 11 | DesignWorkShops/index |
| 10 | - RequirementsTraceability/index | |
| 11 | - HTLD/index | |
| 12 | + |
| @@ -0,0 +1,1 @@ | ||
| 1 | +<mxfile host="Electron" modified="2020-01-30T13:11:43.544Z" agent="Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) draw.io/12.5.3 Chrome/78.0.3904.130 Electron/7.1.9 Safari/537.36" etag="fuFbTfOa3BSZCyzCh0IO" version="12.5.3" type="device"><diagram id="CrEu0Ar_erRfH2SLY0si" name="Page-1">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</diagram></mxfile> | |
| \ No newline at end of file |
| @@ -0,0 +1,35 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +.. _all_graph: | |
| 4 | + | |
| 5 | +All needs [BigTree] | |
| 6 | +=================== | |
| 7 | + | |
| 8 | +We can also show the relations between all product (cq releases) and it *needs* in one big tree [#forrest]_. | |
| 9 | + | |
| 10 | +.. needflow:: | |
| 11 | + | |
| 12 | +Lessons learned | |
| 13 | +--------------- | |
| 14 | + | |
| 15 | +#. We have at least one test-case for each requirement; as we can clearly see. | |
| 16 | +#. The “puzzling” specification for :need:`CALC2` have an affinity with both the requirements and the test-cases | |
| 17 | +#. The (general) requirements for both calculators are equal. | |
| 18 | +#. Both calculators are akin; :need:`CALC2` is kind of a enhanced version of :need:`CALC1` | |
| 19 | + | |
| 20 | +This “BigTree” gives a global overview of all ‘needs’ and there relations; which gives insight into product and how to | |
| 21 | +test it. It can be generated when the requirements (and other ‘needs’) are affixed with their (outgoing) links. | |
| 22 | +|BR| | |
| 23 | +Even when the number of ‘needs’ becomes huge, this graph can be drawn quite clear -- although you make like to use a big | |
| 24 | +slide of paper. | |
| 25 | + | |
| 26 | +It will directly shown some “isolated” requirements or test, when you forgot to add a link. Also other “curious looking” | |
| 27 | +parts of the drawing may need some attention. As it remarkable often denotes some mistakes. | |
| 28 | + | |
| 29 | +.. rubric:: Footnotes & Links | |
| 30 | + | |
| 31 | +.. [#forrest] In general, and strictly speaking, this graph can be a *“forrest”*: a collection of trees. Mostly, people | |
| 32 | + like to use the term “tree” anyhow. | |
| 33 | + |BR| | |
| 34 | + However as this chapter is about requirements and quality, and I’m trying to convince you to be | |
| 35 | + strict, this footnote seems non-trivial ... |
| @@ -0,0 +1,89 @@ | ||
| 1 | +Requirements Traceability [CALC1] | |
| 2 | +********************************** | |
| 3 | + | |
| 4 | +With the defined ‘needs’, their relations can be shown automatically, or some tables with relevant ones can be | |
| 5 | +listed. Below you will find two examples, for :need:`CALC1`. | |
| 6 | + | |
| 7 | +.. _demo1_graph: | |
| 8 | + | |
| 9 | +A graphical view (“tree”) | |
| 10 | +========================= | |
| 11 | + | |
| 12 | +This view shows the relationship between all kinds of specifications. It is fully automatically generated and will be | |
| 13 | +updated when the specifications change. | |
| 14 | + | |
| 15 | +.. needflow:: | |
| 16 | + :tags: demo1;general | |
| 17 | + | |
| 18 | + | |
| 19 | +Lessons learned | |
| 20 | +--------------- | |
| 21 | + | |
| 22 | +#. This graph clearly shows there are **no tests** for :need:`CALC_DIV`. This is easily overseen as there are four | |
| 23 | + requirements *and* four tests defined. | |
| 24 | +#. When the requirement :need:`CALC_ADD` changes, two tests might need an update. | |
| 25 | +#. Likewise, for the other requirements, it is directly visual where the relations are. | |
| 26 | + | |
| 27 | +This very simple demo has only *one* product with *four* requirements and a few tests. There are no product-variant, no | |
| 28 | +product-increments (“new releases”) and no intermediate (or hierarchical) specifications. As a (deliberate) result, its | |
| 29 | +**Requirements Traceability** is simple. | |
| 30 | +|BR| | |
| 31 | +Still, its easy to forget a test; as I did. Did you noticed it? | |
| 32 | + | |
| 33 | +.. attention:: | |
| 34 | + | |
| 35 | + .. _forgotten_test: | |
| 36 | + | |
| 37 | + The “forgotten test” is intentional in this first demo. It will be hot-fixed in the :ref:`next | |
| 38 | + chapter<test_hotfix>`, and you will see it in the other graphs. | |
| 39 | + | |
| 40 | + Therefore I had to use some “trick” in needs; see :ref:`the notes about the forgotten test<about_forgotten_test>` for | |
| 41 | + more info. | |
| 42 | + | |
| 43 | + | |
| 44 | +The Requirements Matrix (table) | |
| 45 | +=============================== | |
| 46 | + | |
| 47 | +Some people prefer to see the same information in a table; again this one is automatically generated. | |
| 48 | + | |
| 49 | +.. needtable:: | |
| 50 | + :tags: demo1;general | |
| 51 | + :style: table | |
| 52 | + :columns: id;type;title;incoming;outgoing | |
| 53 | + :sort: type | |
| 54 | + | |
| 55 | +.. hint:: | |
| 56 | + | |
| 57 | + For now, ignore the *links* to CALC2 and CALC2_1000ND. Those will be in documented in :ref:`demo2` | |
| 58 | + | |
| 59 | +Lessons learned | |
| 60 | +--------------- | |
| 61 | + | |
| 62 | +#. This generated tabular overview kind of act as an index to all “clickable” *needs*. It’s a great page to bookmark. | |
| 63 | +#. One can even add a status-column (not shown here), or filter on (show only) e.g. test that fails. | |
| 64 | +#. It gives less insight; therefore it good to have both overviews. | |
| 65 | + | |
| 66 | + | |
| 67 | +Everybody understands that when the product-definition changes, the implementation will change too. And, that the | |
| 68 | +test-set will change, partially; by example: new tests will be added. | |
| 69 | +|BR| | |
| 70 | +However, some tests may even become obsolete! | |
| 71 | + | |
| 72 | +So, just re-running all (existing) tests as a regression-test, may not work. The question is: which of all test are | |
| 73 | +related to the changed requirement? | |
| 74 | + | |
| 75 | +With a table as above, the answer is just one click away. | |
| 76 | + | |
| 77 | + | |
| 78 | +Next steps | |
| 79 | +========== | |
| 80 | + | |
| 81 | +When we introduce variants, sprint-increments, multiple (sub)components, libraries, versions, releases, etc, the | |
| 82 | +challenge becomes bigger. Especially when a project-teams grows, it might become a nightmare to know which test has to | |
| 83 | +be re-run, when a specification changes. | |
| 84 | + | |
| 85 | +Unless one uses a (simple) approach as shown above. Then, everybody can just see which *rework* is needed when something | |
| 86 | +“upstream” changes. And, by adding a “status” to each spec, we can even make this visual. | |
| 87 | + | |
| 88 | +See :ref:`demo2` for a bit more complex example: Adding a product-variant and (only) one extra (non-functional) | |
| 89 | +requirement. |
| @@ -0,0 +1,120 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +.. _demo1: | |
| 4 | + | |
| 5 | +[CALC1] A simple calculator | |
| 6 | +*************************** | |
| 7 | + | |
| 8 | +The specifications are quite trivial ... | |
| 9 | + | |
| 10 | + | |
| 11 | +The product we need | |
| 12 | +=================== | |
| 13 | + | |
| 14 | +.. demo:: Simple Calculator | |
| 15 | + :ID: CALC1 | |
| 16 | + :tags: demo1 | |
| 17 | + | |
| 18 | + For this demo, a simple calculator is used. It should work with integers; and has only a few requirements. See below. | |
| 19 | + | |
| 20 | +We use this extremely simplistic example as you will agree on its requirements. | |
| 21 | + | |
| 22 | + | |
| 23 | +Some general requirements, for all calculators | |
| 24 | +=============================================== | |
| 25 | + | |
| 26 | +.. req:: Generic Add | |
| 27 | + :ID: CALC_ADD | |
| 28 | + :links: CALC1;CALC2 | |
| 29 | + :tags: general | |
| 30 | + | |
| 31 | + All calculators should be able to sum two numbers and show the result. | |
| 32 | + | |
| 33 | +.. req:: Generic Sub | |
| 34 | + :ID: CALC_SUB | |
| 35 | + :links: CALC1;CALC2 | |
| 36 | + :tags: general | |
| 37 | + | |
| 38 | + All calculators should be able to subtract a number form another number. | |
| 39 | + | |
| 40 | +.. req:: Generic Multiply | |
| 41 | + :ID: CALC_MULT | |
| 42 | + :links: CALC1;CALC2 | |
| 43 | + :tags: general | |
| 44 | + | |
| 45 | + All calculators should be able to multiply two numbers. | |
| 46 | + | |
| 47 | +.. req:: Generic Divide | |
| 48 | + :ID: CALC_DIV | |
| 49 | + :links: CALC1;CALC2 | |
| 50 | + :tags: general | |
| 51 | + | |
| 52 | + All calculators should be able to divide two numbers. | |
| 53 | + | |
| 54 | + | |
| 55 | +Add this is how we test it | |
| 56 | +========================== | |
| 57 | + | |
| 58 | +As we have defined only general requirements, we only need some generic tests. | |
| 59 | + | |
| 60 | +.. test:: Basic addition test | |
| 61 | + :id: CALC_TEST_ADD_1 | |
| 62 | + :links: CALC_ADD;CALC2_1000ND | |
| 63 | + :tags: general | |
| 64 | + | |
| 65 | + Sum two numbers and verify the result is correct. | |
| 66 | + | |
| 67 | + By example: Add ``2`` and ``5`` and check the result is **7** | |
| 68 | + | |
| 69 | +.. test:: Big addition test | |
| 70 | + :id: CALC_TEST_ADD_2 | |
| 71 | + :links: CALC_ADD;CALC2_1000ND | |
| 72 | + :tags: general | |
| 73 | + | |
| 74 | + Add the numbers ``2222`` and ``5555`` and check the result is **7777** | |
| 75 | + | |
| 76 | +.. test:: Subtract test | |
| 77 | + :id: CALC_TEST_SUB_1 | |
| 78 | + :links: CALC_SUB;CALC2_1000ND | |
| 79 | + :tags: general | |
| 80 | + | |
| 81 | + Feed two numbers to the calculators, in the right order and verify the result. | |
| 82 | + |BR| | |
| 83 | + E.g: | |
| 84 | + | |
| 85 | + * Subtract ``5`` from ``7`` and check the result is **2** | |
| 86 | + * Subtract ``5555`` from ``7777`` and check the result is **2222** | |
| 87 | + | |
| 88 | + .. note:: | |
| 89 | + | |
| 90 | + Here we specify two test in one test-requirement; just to show another style | |
| 91 | + | |
| 92 | +.. test:: Multiplication test | |
| 93 | + :id: CALC_TEST_MULT_1 | |
| 94 | + :links: CALC_MULT;CALC2_1000ND | |
| 95 | + :tags: general | |
| 96 | + | |
| 97 | + You get the idea ... | |
| 98 | + | |
| 99 | + | |
| 100 | +Experience practice | |
| 101 | +=================== | |
| 102 | + | |
| 103 | +#. There are several kinds of ‘needs’. | |
| 104 | + |BR| | |
| 105 | + Here we use the toplevel `Demonstrator` (as it is not a real product), `Requirement` and `Test_Case`; later we will | |
| 106 | + introduce `Specification` too. More kinds & levels can be configured. | |
| 107 | +#. Every ‘need’ should have an unique and stable ID; this label is used to link other ‘needs’. | |
| 108 | +#. Some ‘needs’ are linked to an “earlier/higher” ‘need’. | |
| 109 | + |BR| | |
| 110 | + You can see such an outgoing-link in e.g the requirements (You might need to “open” the details-row) | |
| 111 | +#. Each outgoing-link will automatically result in an incoming-link on the references need. (Again, open the | |
| 112 | + details-row, to be able to “follow” it in the ‘forward’ direction). | |
| 113 | + | |
| 114 | + | |
| 115 | + | |
| 116 | +.. hint:: | |
| 117 | + | |
| 118 | + This article uses ‘sphinx-doc’ with the ‘needs’ plugin to define requirement. This is a text-based (and so | |
| 119 | + version-controllable) tool; therefore it is painless to show the details of how it works; that is done in | |
| 120 | + :ref:`RT_Particulars_demo1` |
| @@ -0,0 +1,71 @@ | ||
| 1 | +Requirements Traceability [CALC2] | |
| 2 | +********************************* | |
| 3 | + | |
| 4 | +As in “:doc:`demo1`”, we can automatically generate the an overview of the requirements. | |
| 5 | + | |
| 6 | +The tree view | |
| 7 | +============= | |
| 8 | + | |
| 9 | +.. _demo2_graph: | |
| 10 | + | |
| 11 | +.. needflow:: | |
| 12 | + :tags: demo2;general | |
| 13 | + | |
| 14 | +Lessons learned | |
| 15 | +--------------- | |
| 16 | + | |
| 17 | +#. We can directly see that specification :need:`CALC2_1000ND` influences all existing test-cases. | |
| 18 | +#. Each test *depends* on both a (functional) requirement and a (non-functional) specification (at least in this case). | |
| 19 | +#. The requirements-relations can become more complicated, even by adding **only** *one* requirement! | |
| 20 | + | |
| 21 | +Can you imagine what will happen when we add a handful of requirements to the calculator (*memory*, *square-root*, | |
| 22 | +*powers*)? Or, a few more non-functionals (*speed-of-operation*, *floats*). Then the complexity quickly raises even for | |
| 23 | +such a simple product. And it becomes hard to predict which tests have to be adapted or rerun. | |
| 24 | + | |
| 25 | +Likewise, when a few requirements become altered in an upcoming sprint: can you predict which tests will have to change? | |
| 26 | +A graph, as above, will certainly help in working that out. | |
| 27 | + | |
| 28 | + | |
| 29 | +The table view | |
| 30 | +============== | |
| 31 | + | |
| 32 | +.. needtable:: | |
| 33 | + :tags: demo2,general | |
| 34 | + :style: table | |
| 35 | + :columns: id;type;title;incoming;outgoing | |
| 36 | + :sort: type | |
| 37 | + | |
| 38 | + | |
| 39 | +Lessons learned | |
| 40 | +--------------- | |
| 41 | + | |
| 42 | +#. The advantage of a table-view is that is will only grow in one direction: it just becomes a bit longer. | |
| 43 | +#. Even for a big project, it’s a great page to bookmark and use as a start-page for all kinds of requirements. | |
| 44 | + |BR| | |
| 45 | + Probably, you like to split it into the kind of ‘need’. | |
| 46 | + | |
| 47 | +It would be great to show a classical `Requirements Traceability matrix | |
| 48 | +<https://en.wikipedia.org/wiki/Traceability_matrix>`_ (RTM) too. This table shows the relations between all the | |
| 49 | +requirements and all the tests. | |
| 50 | + | |
| 51 | +.. note:: | |
| 52 | + | |
| 53 | + As ‘needs’ currently does not support classical *RTM*\s, I can’t generate/show it here. See :ref:`a manually made | |
| 54 | + TRM <RT_RTM_CALC2>` to get the idea. As you will see: it’s easy to read. | |
| 55 | + |BR| | |
| 56 | + However, its quite hard to grasp deep relations; then the tree above is more helpfull. | |
| 57 | + | |
| 58 | +Next steps | |
| 59 | +========== | |
| 60 | + | |
| 61 | +We might add more product-variants, or more sprints to convince you that requirement-traceability is important. The only | |
| 62 | +effect is more pages with (trivial) requirements, specifications or other ‘needs’. And the same to generated overviews; | |
| 63 | +the later cost only a small number of lines, independent of the size of the product. So we will leave that as an | |
| 64 | +exercise. | |
| 65 | + | |
| 66 | +As a bonus, we will show you one more generated graph: :ref:`all_graph`, combining the :need:`CALC1` and :need:`CALC2` | |
| 67 | +requirements. | |
| 68 | + | |
| 69 | +Whenever you have more quistions, you can email me :sogeti-email:`Albert.Mietus`. | |
| 70 | + | |
| 71 | + |
| @@ -0,0 +1,95 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +.. _demo2: | |
| 4 | + | |
| 5 | +[CALC2] The exact calculator | |
| 6 | +**************************** | |
| 7 | + | |
| 8 | +This demo is just a bit more complicated then :ref:`demo1`: this product-variant has *one* extra requirement. | |
| 9 | + | |
| 10 | +A bit more complicated product | |
| 11 | +============================== | |
| 12 | + | |
| 13 | +.. demo:: Exact Calculator | |
| 14 | + :ID: CALC2 | |
| 15 | + :tags: demo2 | |
| 16 | + :links: CALC1 | |
| 17 | + | |
| 18 | + This calculator should work with `Fractional Numbers <https://en.wikipedia.org/wiki/Fraction_(mathematics)>`_, and be | |
| 19 | + exact for very big numbers; as defined in :need:`CALC2_1000ND` | |
| 20 | + | |
| 21 | + .. warning:: | |
| 22 | + | |
| 23 | + This implies ``floats`` are not possible in the implementation | |
| 24 | + | |
| 25 | + | |
| 26 | +The extra requirement | |
| 27 | +===================== | |
| 28 | + | |
| 29 | +.. spec:: Big fractional numbers | |
| 30 | + :id: CALC2_1000ND | |
| 31 | + :links: CALC_ADD;CALC_SUB;CALC_MULT;CALC_DIV; CALC2 | |
| 32 | + :tags: demo2 | |
| 33 | + | |
| 34 | + The :need:`CALC2` should work with fractions; where nominator and denominator can be very long: up to **1000 | |
| 35 | + digits**. | |
| 36 | + | |
| 37 | +.. _test_hotfix: | |
| 38 | + | |
| 39 | +Hotfix the missing test | |
| 40 | +----------------------- | |
| 41 | + | |
| 42 | +We also *repair* the missing test in demo1, but only for demo2 (Because it is still a *demo!*). | |
| 43 | + | |
| 44 | +.. test:: DIV test (demo2 only) | |
| 45 | + :id: CALC2_TEST_DIV_1 | |
| 46 | + :links: CALC_DIV; CALC2_1000ND | |
| 47 | + :tags: demo2 | |
| 48 | + | |
| 49 | + Subtract ``1/3`` from ``1/2`` and check the result is **1/6**. | |
| 50 | + | |
| 51 | + .. note:: | |
| 52 | + | |
| 53 | + This test is was intentionally “forgotten” as explained in the :ref:`forgotten test <forgotten_test>`. | |
| 54 | + | |
| 55 | + Therefore it is only added for the :need:`CALC2`. See :ref:`the notes about the forgotten | |
| 56 | + test<about_forgotten_test>` for more info. | |
| 57 | + | |
| 58 | +How to test? | |
| 59 | +============ | |
| 60 | + | |
| 61 | +The :need:`CALC2_1000ND` requirement is a good example of a “*nonfunctional*” (actually: a non-distributable) | |
| 62 | +specification. It is valid for all other requirements; all parts of the implementation should adhere to it. | |
| 63 | + | |
| 64 | +Testing this requirement is also different too. The same tests are valid: we have to add, subtract, multiply and | |
| 65 | +divide. | |
| 66 | +|BR| | |
| 67 | +Only, now we have to use other numbers; really big ones! | |
| 68 | + | |
| 69 | +Traditionally | |
| 70 | +------------- | |
| 71 | + | |
| 72 | +In the traditional world, using the TMAP-terms, this approximately come down to: | |
| 73 | + | |
| 74 | +* Reuse the *logic test*. | |
| 75 | +* Change a *physical test* (or add one). | |
| 76 | + | |
| 77 | +Modern | |
| 78 | +------ | |
| 79 | + | |
| 80 | +When using an agile test-automation framework this implies | |
| 81 | + | |
| 82 | +* The ATS (Automated Test Script) isn’t altered. | |
| 83 | +* Some “Test-Vectors” (or test-data) is added: the big-fractions. | |
| 84 | + | |
| 85 | + | |
| 86 | +Experience practice | |
| 87 | +=================== | |
| 88 | + | |
| 89 | +#. It is possible to have multiply “toplevel” ‘needs’. Here, that are ``Demonstrators``, but it possible to use | |
| 90 | + `Products`, `Variants`, and/or `Releases` etc, as well. | |
| 91 | +#. Here, a new kind of ‘need’ is introduced: ``Specification``. As you will see on the next page, it influences not only | |
| 92 | + the implementation, but also testing. | |
| 93 | +#. In the ‘details-row’, you can see it has (outgoing) links to many (all) earlier requirements. | |
| 94 | + | |
| 95 | + |
| @@ -0,0 +1,50 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +.. _RT_demo: | |
| 4 | + | |
| 5 | +********************** | |
| 6 | +Demo: Some calculators | |
| 7 | +********************** | |
| 8 | + | |
| 9 | +This chapter contains a few demonstrations of the Requirements Traceability concept. | |
| 10 | + | |
| 11 | +We start with a very simple product: the :need:`CALC1`; with only a few generic requirements and tests. By defining | |
| 12 | +those “needs”[#needs]_ it becomes possible to show a (generated) :ref:`graph <demo1_graph>` with the relations between | |
| 13 | +them. |BR| Probably, you will be able to implement and verify this simple product without (formal) | |
| 14 | +requirements-traceability; but it gives a nice introduction to the concept. | |
| 15 | + | |
| 16 | + | |
| 17 | +Then, a new product the :need:`CALC2` is defined, in the same way. | |
| 18 | +|BR| | |
| 19 | +Even it has only one (*puzzling*) additional requirement; that one makes both the implementation and the validation | |
| 20 | +burdensome. And changes the test-cases completely; as shown in :ref:`its requirement-traceability graph <demo2_graph>`. | |
| 21 | + | |
| 22 | + | |
| 23 | +Likewise, we could add more demo’s with more and more specifications, tests and *need* at multiple-levels; but you will | |
| 24 | +get the idea: By simple ‘defining’ the needs, it becomes possible to get insight; independent of the size of the products | |
| 25 | +or the numbers of specifications. | |
| 26 | + | |
| 27 | +Finally, an :ref:`overall graph <all_graph>` is shown, with all the products, all the tests, and all the connecting | |
| 28 | +*needs*. | |
| 29 | + | |
| 30 | +.. rubric:: Content | |
| 31 | +.. toctree:: | |
| 32 | + :glob: | |
| 33 | + :maxdepth: 3 | |
| 34 | + | |
| 35 | + demo1 | |
| 36 | + demo1-tracking | |
| 37 | + demo2 | |
| 38 | + demo2-tracking | |
| 39 | + TraceAll | |
| 40 | + | |
| 41 | +.. rubric:: Footnotes & Links | |
| 42 | + | |
| 43 | +.. [#needs] The universal term ‘*need*’ is used for all kinds of requirements, specifications, test-specs, etc. | |
| 44 | + This name comes from the “needs” extension to “sphinx-docs” that we use in this demo. | |
| 45 | + | |
| 46 | +Needs: | |
| 47 | + http://sphinxcontrib-needs.readthedocs.io | |
| 48 | + | |
| 49 | +Sphinx: | |
| 50 | + https://www.sphinx-doc.org/ |
| @@ -0,0 +1,60 @@ | ||
| 1 | +.. _RT_RTM_CALC2: | |
| 2 | + | |
| 3 | +The classical Requirements Traceability Matrix | |
| 4 | +================================================ | |
| 5 | + | |
| 6 | +Most literature about requirements-traceability focus on the Requirements Traceability Matrix [#RTM]_. This table gives the relation between the (high level) requirements versus all test. As ‘needs’ can’t generate this table (yet), I have created one as example. | |
| 7 | + | |
| 8 | +With this overview one get insight about which test are needed to verify one requirement. Sometimes it explicitly counts the number of available tests pro requirement too. Albeit that is a nice result, the ATM isn’t that useful in an agile environment. When a requirement is added, ore one changes, the RTM itself gives little help to update the table. | |
| 9 | + | |
| 10 | + | |
| 11 | +.. list-table:: RTM for the :need:`CALC2` | |
| 12 | + :class: RTM-rotated-head | |
| 13 | + :header-rows: 1 | |
| 14 | + :widths: 25 15 15 15 15 15 | |
| 15 | + | |
| 16 | + * - Test\\Req | |
| 17 | + - :need:`CALC_ADD` | |
| 18 | + - :need:`CALC_SUB` | |
| 19 | + - :need:`CALC_MULT` | |
| 20 | + - :need:`CALC_DIV` | |
| 21 | + - :need:`CALC2_1000ND` | |
| 22 | + * - :need:`CALC_TEST_ADD_1` | |
| 23 | + - X | |
| 24 | + - | |
| 25 | + - | |
| 26 | + - | |
| 27 | + - X | |
| 28 | + * - :need:`CALC_TEST_ADD_2` | |
| 29 | + - X | |
| 30 | + - | |
| 31 | + - | |
| 32 | + - | |
| 33 | + - X | |
| 34 | + * - :need:`CALC_TEST_SUB_1` | |
| 35 | + - | |
| 36 | + - X | |
| 37 | + - | |
| 38 | + - | |
| 39 | + - X | |
| 40 | + * - :need:`CALC_TEST_MULT_1` | |
| 41 | + - | |
| 42 | + - | |
| 43 | + - X | |
| 44 | + - | |
| 45 | + - X | |
| 46 | + * - :need:`CALC2_TEST_DIV_1` | |
| 47 | + - | |
| 48 | + - | |
| 49 | + - | |
| 50 | + - X | |
| 51 | + - X | |
| 52 | + | |
| 53 | + | |
| 54 | + | |
| 55 | +.. rubric:: Footnotes & Links | |
| 56 | + | |
| 57 | +.. [#RTM] Often shorthanded to RTM, or simle “Traceability Matrix”, as wikipedia does. | |
| 58 | + | |
| 59 | +Wikipedia on RTM: | |
| 60 | + https://en.wikipedia.org/wiki/Traceability_matrix |
| @@ -0,0 +1,41 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +***** | |
| 4 | +Goals | |
| 5 | +***** | |
| 6 | + | |
| 7 | + “Requirements traceability is a sub-discipline of requirements management within software development and systems | |
| 8 | + engineering ...” | |
| 9 | + | |
| 10 | + “... is defined as "the ability to describe and follow the life of a requirement in both a forwards and backwards direction” | |
| 11 | + | |
| 12 | + --- https://en.wikipedia.org/wiki/Requirements_traceability | |
| 13 | + | |
| 14 | +There are many reasons to enroll requirement-management and -traceability. | |
| 15 | + | |
| 16 | +* First of all, it’s a good habit: without an objective it hard to succeed. | |
| 17 | + *How can a system pass an acceptance-test when it is not clear what the (current) requirements are?* | |
| 18 | +* Often more urgent: in many domains, it is demanded by law or standardisation committees. In healthcare, automotive and | |
| 19 | + aerospace “safety” is mandatory. Standard like IEC61508, and (A)SIL more or less demand a process with proper | |
| 20 | + requirement traceability. | |
| 21 | + | |
| 22 | +With the uprise of lean, agile and scrum, there is a tendency to skip less popular steps (and expensive roles) and to | |
| 23 | +trust on craftsmanship. This implies the traditional 'requirement management' approach has to change. And also, that more | |
| 24 | +people should be involved. | |
| 25 | + | |
| 26 | +This chapter gives you an introduction into 'tracking requirements', in a lean, agile fashion. | |
| 27 | +|BR| | |
| 28 | +After this *lecture*, you should understand how to annex (written) requirements and other specifications, to be able to | |
| 29 | +link them with test-cases. You should be able to visualize those relations, to get insight into which tests are needed | |
| 30 | +for a specific product-release. (And the other way around.) Besides, you should be able to apply this manually, for | |
| 31 | +moderately simple products. For big, complicated products, you probably need a bit more experience and the assistance of | |
| 32 | +a standardized process and mayhap a tool, to make it lean. | |
| 33 | + | |
| 34 | +.. toctree:: | |
| 35 | + :hidden: | |
| 36 | + :glob: | |
| 37 | + | |
| 38 | + * | |
| 39 | + | |
| 40 | + | |
| 41 | + |
| @@ -0,0 +1,55 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +========================= | |
| 4 | +Requirements Traceability | |
| 5 | +========================= | |
| 6 | + | |
| 7 | +.. post:: 2020/02/15 | |
| 8 | + :tags: SysEng | |
| 9 | + :category: lecture | |
| 10 | + :location: Vianen | |
| 11 | + :language: en | |
| 12 | + | |
| 13 | + :study-time: 1 hour | |
| 14 | + | |
| 15 | + Requirement-Management, and especially *“Tracking Requirements”* isn’t that complicated, but it needs some | |
| 16 | + discipline. Often that discipline is *replaced* by a tool, which is encouraged by tool-vendors. That hardly ever | |
| 17 | + works. | |
| 18 | + | |
| 19 | + This blog introduces requirements traceability in a conceptual, but pragmatic way. It shows :ref:`--as a | |
| 20 | + demo--<RT_demo>` what a team has to do (defining requirements and describing the relations) and what the benefit | |
| 21 | + is. It assumes a (more or less) agile way-of-work and shows how it can become lean. A small investment in good | |
| 22 | + requirements definitions makes validations a lot easier. | |
| 23 | + | |
| 24 | + And yes, it used a tool: a free one; as part of the documentation-system that is used for this side. An structured, | |
| 25 | + version-controllable, textual way to write documentation, including all requirements. With a plugin that | |
| 26 | + can visualize all specifications and their relations. | |
| 27 | + |BR| | |
| 28 | + Those *“particulars”* will be shown too. | |
| 29 | + | |
| 30 | +.. admonition:: Summary (testers view) | |
| 31 | + | |
| 32 | + .. image:: ./V-IdeaWorkProduct-alfa.png | |
| 33 | + :width: 33% | |
| 34 | + :align: right | |
| 35 | + | |
| 36 | + * For a simple development cycle, it easy to trace the validation of the product: | |
| 37 | + *All features should be covered by a test, and all should pass*. | |
| 38 | + * When multiple products --or multiple releases-- are mandatory, this becomes quickly ambiguous: | |
| 39 | + *Some tests have to pass, and only the essential specifications need test-cases.* | |
| 40 | + * Then ‘requirements traceability’ becomes crucial: | |
| 41 | + **It gives insight into which ‘specs’ are required by each product/release and which tests are essential.** | |
| 42 | + * This article (as part of a workshop) shows a down-to-earth demo of how you set-up the ‘requirements traceability’ | |
| 43 | + and how to use it. | |
| 44 | + * We use the ‘tester view’: Be able to demonstrate the *product* **does** what was *aimed for*! | |
| 45 | + | |
| 46 | +.. rubric:: Content | |
| 47 | +.. toctree:: | |
| 48 | + :maxdepth: 2 | |
| 49 | + | |
| 50 | + goal/index | |
| 51 | + demo/index | |
| 52 | + notes/index | |
| 53 | + | |
| 54 | + | |
| 55 | +More info? Contact Albert: :sogeti-email:`Albert.Mietus`; +31 (0)6 526 592 60. Or use the comment section below. |
| @@ -0,0 +1,63 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus 2020 | |
| 2 | + | |
| 3 | +.. _about_forgotten_test: | |
| 4 | + | |
| 5 | + | |
| 6 | + | |
| 7 | +The forgotten test | |
| 8 | +================== | |
| 9 | + | |
| 10 | +Intentionally, one test is :ref:`“forgotten” <forgotten_test>` for the first demo. However it is needed and “hot-fixed” for :ref:`the second one <test_hotfix>`. | |
| 11 | +|BR| | |
| 12 | +Surely this is not typical in one documentation-release. | |
| 13 | + | |
| 14 | +Therefor some *tricks* are used to show this in one go. Those tricks are documented here. | |
| 15 | + | |
| 16 | +By adding some ‘tags’ to the various requirements one can filter on those when generating an overview. And only show the intend ones. This can be useful by-example to labels ‘needs’ for a specific release or product-variant. Here, used a bit more extensive. | |
| 17 | + | |
| 18 | +Particulars | |
| 19 | +----------- | |
| 20 | + | |
| 21 | +As typical each product has it “own” tag: ``demo1`` or ``demo2``. As we have some tests that should be selected on one page, but not on another we use an extra tag: ``general``. | |
| 22 | +|BR| | |
| 23 | +Most test-cases are labeled with ``general``, as are the generic requirements. Whereas the “forgotten” test :need:`CALC2_TEST_DIV_1` is labeled ``demo2`` | |
| 24 | + | |
| 25 | +.. code-block:: rst | |
| 26 | + :emphasize-lines: 4,11 | |
| 27 | + | |
| 28 | + .. test:: Basic addition test | |
| 29 | + :id: CALC_TEST_ADD_1 | |
| 30 | + :links: CALC_ADD;CALC2_1000ND | |
| 31 | + :tags: general | |
| 32 | + | |
| 33 | + Sum two numbers .... | |
| 34 | + | |
| 35 | + .. test:: DIV test (demo2 only) | |
| 36 | + :id: CALC2_TEST_DIV_1 | |
| 37 | + :links: CALC_DIV; CALC2_1000ND | |
| 38 | + :tags: demo2 | |
| 39 | + | |
| 40 | + Subtract ... | |
| 41 | + | |
| 42 | + | |
| 43 | +Now it becomes possible to show the relations with, or without that test. | |
| 44 | + | |
| 45 | +In the :ref:`first demo <demo1_graph>`, we filter on ‘demo1` and ‘general’. So we get the product, the generic requirements and most tests. But not the forgotten one. | |
| 46 | + | |
| 47 | +.. code-block:: rst | |
| 48 | + :emphasize-lines: 2 | |
| 49 | + | |
| 50 | + .. needflow:: | |
| 51 | + :tags: demo1;general | |
| 52 | + | |
| 53 | +*After* we have “hot-fixed” the test, we can simply select all test for the :ref:`second graph <demo1_graph>` | |
| 54 | + | |
| 55 | +.. code-block:: rst | |
| 56 | + :emphasize-lines: 2 | |
| 57 | + | |
| 58 | + .. needflow:: | |
| 59 | + :tags: demo2;general | |
| 60 | + | |
| 61 | +Actually, we didn’t really “hot fix” it; it was only defined for demo2. But linked to a general requirements. | |
| 62 | + | |
| 63 | +Normally, you don’t need to use this kind of tricks; it better to not forget a test, or really fix it. |
| @@ -0,0 +1,35 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +.. _RT_notes: | |
| 4 | + | |
| 5 | +*********************** | |
| 6 | +Particulars of ‘needs’ | |
| 7 | +*********************** | |
| 8 | + | |
| 9 | +The main objective of this blog is introducing “Requirements Traceability” in general; especially in an agile | |
| 10 | +environment or when a roadmap of product-releases exists. That is done demoing :need_count:`type=='demo'` products, | |
| 11 | +:need_count:`type=='req'` requirements, :need_count:`type=='spec'` specification, and :need_count:`type=='test'` | |
| 12 | +tests. Also, some generated graphs and tables are shown. | |
| 13 | + | |
| 14 | +Those ‘needs’ aren’t just text; they are ‘life’ defined and generated by a plugin called *needs* in the *sphinx-doc* | |
| 15 | +documenting tool; which is just to generate this website. Partly, because I like this toolset. But also to show you that | |
| 16 | +is can be done. | |
| 17 | + | |
| 18 | +And despite this blog is not about (learning) a tool, this section will go a step deeper: It will show you how it is | |
| 19 | +done; without becoming a tutorial on ‘sphinx’ or ‘needs’. | |
| 20 | +|BR| | |
| 21 | +Possible, you like it and would love to play with the demo. Or, you are inquisitive whether this is truly | |
| 22 | +*not text-only*. | |
| 23 | + | |
| 24 | +The following pages show some excerpts of the *“RST-code”*, that is used to defined all ‘needs’. Feel free to | |
| 25 | +study the ‘sources’ and learn from it. | |
| 26 | +|BR| | |
| 27 | +I will even document the tricks needed for “:ref:`about_forgotten_test`”. | |
| 28 | + | |
| 29 | +.. toctree:: | |
| 30 | + | |
| 31 | + particulars-demo1 | |
| 32 | + particulars-demo2 | |
| 33 | + forgotten_test | |
| 34 | + | |
| 35 | + |
| @@ -0,0 +1,90 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus 2020 | |
| 2 | + | |
| 3 | +.. _RT_Particulars_demo1: | |
| 4 | + | |
| 5 | +===================== | |
| 6 | +Particulars for CALC1 | |
| 7 | +===================== | |
| 8 | + | |
| 9 | +.. hint:: | |
| 10 | + | |
| 11 | + You should skip the particulars passages, when you not interested in the technical details of this particular tool. | |
| 12 | + | |
| 13 | + | |
| 14 | +A product (start of the V) | |
| 15 | +========================== | |
| 16 | + | |
| 17 | +To define the :need:`CALC1` product the following is described: | |
| 18 | + | |
| 19 | +.. code-block:: rst | |
| 20 | + | |
| 21 | + .. demo:: Simple Calculator | |
| 22 | + :ID: CALC1 | |
| 23 | + | |
| 24 | + For this demo ... | |
| 25 | + | |
| 26 | +You can see this product has the ID ``CALC1`` and some text. No links are needed, they will be added automatically by | |
| 27 | +requirements, which are described “later”. | |
| 28 | + | |
| 29 | + | |
| 30 | +With requirements (one step down into the V) | |
| 31 | +-------------------------------------------- | |
| 32 | + | |
| 33 | +The requirement :need:`CALC_ADD` has an ID too, and a link to the products it is valid for; here `CALC1` and `CALC2`. | |
| 34 | + | |
| 35 | +.. code-block:: rst | |
| 36 | + :emphasize-lines: 2,3 | |
| 37 | + | |
| 38 | + .. req:: Generic Add | |
| 39 | + :ID: CALC_ADD | |
| 40 | + :links: CALC1;CALC2 | |
| 41 | + | |
| 42 | + All calculators ... able to sum ... | |
| 43 | + | |
| 44 | +All requirements are described in the same way, as well as each individual requirement can be linked to one or more | |
| 45 | +products (or product-variants). As this demo has (already) two products, and this requirement is valid for both; you see | |
| 46 | +them listed here. | |
| 47 | + | |
| 48 | + | |
| 49 | +And tests (the other side of the V) | |
| 50 | +----------------------------------- | |
| 51 | + | |
| 52 | +A test (-case) is also a ‘need’. It is defined in the same approach: a title, an ID and the links to all requirements that | |
| 53 | +are tested by this one. Here, that is only `CALC_ADD`. | |
| 54 | + | |
| 55 | +.. code-block:: rst | |
| 56 | + :emphasize-lines: 2 | |
| 57 | + | |
| 58 | + .. test:: Basic addition test | |
| 59 | + :id: CALC_TEST_ADD_1 | |
| 60 | + :links: CALC_ADD | |
| 61 | + | |
| 62 | + Sum two numbers and verify ... | |
| 63 | + | |
| 64 | +Again, the same construction is repeated for all tests. | |
| 65 | + | |
| 66 | + | |
| 67 | +Tracing the requirements | |
| 68 | +======================== | |
| 69 | + | |
| 70 | +Generaring the “requirements tree” as displayed :ref:`here <demo1_graph>` is very easy: | |
| 71 | + | |
| 72 | +.. code-block:: rst | |
| 73 | + :emphasize-lines: 1 | |
| 74 | + | |
| 75 | + .. needflow:: | |
| 76 | + :tags: demo1;general | |
| 77 | + | |
| 78 | +Likewise is showing the table overview: | |
| 79 | + | |
| 80 | +.. code-block:: rst | |
| 81 | + :emphasize-lines: 1 | |
| 82 | + | |
| 83 | + .. needtable:: | |
| 84 | + :tags: demo1;general | |
| 85 | + :style: table | |
| 86 | + :columns: id;type;title;incoming;outgoing | |
| 87 | + :sort: type | |
| 88 | + | |
| 89 | + | |
| 90 | +See the documentations of needs (https://sphinxcontrib-needs.readthedocs.io) for details on all options. |
| @@ -0,0 +1,102 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus 2020 | |
| 2 | + | |
| 3 | +.. _RT_Particulars_demo2: | |
| 4 | + | |
| 5 | +====================== | |
| 6 | + Particulars for CALC2 | |
| 7 | +====================== | |
| 8 | + | |
| 9 | +.. hint:: | |
| 10 | + | |
| 11 | + Again, you can skip the **particulars** passage when you have no curiosity in the technicalities of ‘needs’ itself. | |
| 12 | + | |
| 13 | + | |
| 14 | +Describing requirements | |
| 15 | +======================= | |
| 16 | + | |
| 17 | +The describing text of any requirement (in ‘needs’) is standard **rst** *(reStructuredText)*. So it can use hyperlinks, | |
| 18 | +forward-references to other needs and even warning-admonitions. | |
| 19 | +|BR| | |
| 20 | +The full textual definition of :need:`CALC2` is: | |
| 21 | + | |
| 22 | +.. code-block:: rst | |
| 23 | + :emphasize-lines: 6-7, 9-11 | |
| 24 | + | |
| 25 | + .. demo:: Exact Calculator | |
| 26 | + :ID: CALC2 | |
| 27 | + :tags: demo2 | |
| 28 | + :links: CALC1 | |
| 29 | + | |
| 30 | + This calculator should work with `Fractional Numbers <https://en.wikipedia.org/wiki/Fraction_(mathematics)>`_, and be | |
| 31 | + exact for very big numbers; as defined in :need:`CALC2_1000ND` | |
| 32 | + | |
| 33 | + .. warning:: | |
| 34 | + | |
| 35 | + This implies ``floats`` are not possible in the implementation | |
| 36 | + | |
| 37 | + | |
| 38 | +The added specification | |
| 39 | +======================= | |
| 40 | + | |
| 41 | +Like all other ‘needs’, the specification for :need:`CALC2_1000ND` is straightforward. It links to “earlier” | |
| 42 | +requirements. | |
| 43 | + | |
| 44 | +.. code-block:: rst | |
| 45 | + :emphasize-lines: 3 | |
| 46 | + | |
| 47 | + .. spec:: Big fractional numbers | |
| 48 | + :id: CALC2_1000ND | |
| 49 | + :links: CALC_ADD;CALC_SUB;CALC_MULT;CALC_DIV | |
| 50 | + :tags: demo2 | |
| 51 | + | |
| 52 | + The :need:`CALC2` ... | |
| 53 | + | |
| 54 | +.. tip:: | |
| 55 | + | |
| 56 | + * There is no *prescribed* order how the individual ‘needs’ can be linked. It kind of feels more natural to link to | |
| 57 | + “higher level” (in the V-model) ‘needs’, and to one that are described “earlier” (in project-time). But when you | |
| 58 | + can link them in any order. | |
| 59 | + | |
| 60 | + * Similar, a ‘need’ can link to any other ‘need’, independent of its type. | |
| 61 | + |BR| | |
| 62 | + Above we have used a `spec`, to add this requirement; but a normal `req` (requirement) is possible too. You can | |
| 63 | + configure any kind of ‘needs’, as you like. | |
| 64 | + | |
| 65 | + * You can even *export* ‘needs’ in one document and *import* them in another. For big projects with many levels of | |
| 66 | + modules, and so, specification-documents, this is typical behaviour. In this small calculator example tha is not | |
| 67 | + used. | |
| 68 | + | |
| 69 | +Tracing relations | |
| 70 | +================= | |
| 71 | + | |
| 72 | +To be able to trace whetter some test need to be adapted, we only have to add some “links” between the relevant test and the | |
| 73 | +additional (test) specification. | |
| 74 | + | |
| 75 | +In :need:`CALC2_1000ND` that is done by adding some (outgoing) links to the existing tests. You may have to open/click the see the details row. | |
| 76 | + | |
| 77 | +.. note:: | |
| 78 | + | |
| 79 | + The incoming links are added automatically. | |
| 80 | + | |
| 81 | +Inheriting links | |
| 82 | +---------------- | |
| 83 | + | |
| 84 | +Currently, there is no *inherit option*, One can’t specify that the requirements for `CALC1` are also valid for | |
| 85 | +`CALC2`. | |
| 86 | + | |
| 87 | +* By linking the two ``Demonstrators`` we get (almost) the same. | |
| 88 | +* Alternatively, you can just add the links manually. | |
| 89 | +* *(or you can use the export/import option and a simple script to modify the json file)* | |
| 90 | + | |
| 91 | +.. tip:: | |
| 92 | + | |
| 93 | + As ‘needs’ is an actively maintained open-source project, ‘inheriting’ may be added in a next release. | |
| 94 | + |BR| | |
| 95 | + Even by you:-) | |
| 96 | + | |
| 97 | +The hotfix | |
| 98 | +========== | |
| 99 | + | |
| 100 | +See :ref:`the notes about the forgotten test<about_forgotten_test>` for the particulars on how to :ref:`forget | |
| 101 | +<forgotten_test>` and :ref:`add <test_hotfix>` a test in one document. | |
| 102 | + |
| @@ -0,0 +1,11 @@ | ||
| 1 | +.. Copyright (C) ALbert Mietus & Sogeti.HT; 2020 | |
| 2 | + | |
| 3 | +------------------ | |
| 4 | +System Engineering | |
| 5 | +------------------ | |
| 6 | + | |
| 7 | +.. toctree:: | |
| 8 | + :maxdepth: 2 | |
| 9 | + :glob: | |
| 10 | + | |
| 11 | + */index |
| @@ -5,7 +5,9 @@ | ||
| 5 | 5 | Modern Engineering of Sovereign Software |
| 6 | 6 | **************************************** |
| 7 | 7 | |
| 8 | -See the :doc:`README` on :term:`Modern Engineering` of :term:`Sovereign Software`, and the :ref`copyright` | |
| 8 | +Also knows as: “**Modern Embedded Software Systems**” | |
| 9 | + | |
| 10 | +.. note:: See the :doc:`README` on what I mean with ‘:term:`Modern Engineering`’ and ‘:term:`Sovereign Software`’. And for the :ref:`copyright` | |
| 9 | 11 | |
| 10 | 12 | Table of Content |
| 11 | 13 | **************** |
| @@ -20,6 +22,7 @@ | ||
| 20 | 22 | :maxdepth: 2 |
| 21 | 23 | |
| 22 | 24 | * |
| 25 | + SystemEngineering/index | |
| 23 | 26 | SoftwareCompetence/index |
| 24 | 27 | pyMESS/index |
| 25 | 28 | blog/index |
Fork