(************************************************************************* * Copyright (C) * 2019 The University of Exeter * 2018-2019 The University of Paris-Saclay * 2018 The University of Sheffield * * License: * This program can be redistributed and/or modified under the terms * of the 2-clause BSD-style license. * * SPDX-License-Identifier: BSD-2-Clause *************************************************************************) (*<*) theory mini_odo imports "Isabelle_DOF.CENELEC_50128" "Isabelle_DOF.technical_report" begin declare[[strict_monitor_checking=true]] (*>*) title*[title::title]\The CENELEC 50128 Ontology\ subtitle*[subtitle::subtitle]\Case Study: An Odometer-Subsystem\ chapter*[casestudy::technical]\An Odometer-Subsystem\ text\ In our case study, we will follow the phases of analysis, design, and implementation of the odometry function of a train. This software processes data from an odometer to compute the position, speed, and acceleration of a train. This system provides the basis for many safety critical decisions, \eg, the opening of the doors. Due to its relatively small size, it is a manageable, albeit realistic target for a comprehensive formal development: it covers a physical model of the environment, the physical and architectural model of the odometer including the problem of numerical sampling, and the boundaries of efficient computations. The interplay between environment and measuring-device as well as the implementation problems on a platform with limited resources makes the odometer a fairly typical safety critical embedded system. Due to space reasons, we will focus on the analysis part of the integrated document; the design and code parts will only be outlined in a final resume. The \<^emph>\ontological embedding\, which represents a main contribution of this paper, will be presented in the next two sections. We start with the capture of a number of informal documents available at the beginning of the development. \ section\System Requirements as an \<^emph>\Integrated Source\\ text\Accurate information of a train's location along a track is in an important prerequisite to safe railway operation. Position, speed and acceleration measurement usually lies on a set of independent measurements based on different physical principles---as a way to enhance precision and availability. One of them is an \<^emph>\odometer\, which allows estimating a relative location while the train runs positions established by other measurements. \ subsection\Capturing ``Basic Principles of Motion and Motion Measurement.''\ text\ A rotary encoder measures the motion of a train. To achieve this, the encoder's shaft is fixed to the trains wheels axle. When the train moves, the encoder produces a signal pattern directly related to the trains progress. By measuring the fractional rotation of the encoders shaft and considering the wheels effective ratio, relative movement of the train can be calculated. \begin{wrapfigure}[8]{l}{4.6cm} \centering \vspace{-.5cm} \includegraphics[width=3.4cm]{figures/wheel-df} \caption{Motion sensing via an odometer.} \label{wheel-df} \end{wrapfigure} \autoref{wheel-df} shows that we model a train, seen from a pure kinematics standpoint, as physical system characterized by a one-dimensional continuous distance function, which represents the observable of the physical system. Concepts like speed and acceleration were derived concepts defined as their (gradient) derivatives. We assume the use of the meter, kilogram, and second (MKS) system. This model is already based on several fundamental assumptions relevant for the correct functioning of the system and for its integration into the system as a whole. In particular, we need to make the following assumptions explicit:\vspace{-.3cm} \<^item> that the wheel is perfectly circular with a given, constant radius, \<^item> that the slip between the trains wheel and the track negligible, \<^item> the distance between all teeth of a wheel is the same and constant, and \<^item> the sampling rate of positions is a given constant. These assumptions have to be traced throughout the certification process as \<^emph>\derived requirements\ (or, in CENELEC terminology, as \<^emph>\exported constraints\), which is also reflected by their tracing throughout the body of certification documents. This may result in operational regulations, \eg, regular checks for tolerable wheel defects. As for the \<^emph>\no slip\-assumption, this leads to the modeling of constraints under which physical slip can be neglected: the device can only produce reliable results under certain physical constraints (speed and acceleration limits). Moreover, the \<^emph>\no slip\-assumption motivates architectural arrangements for situations where this assumption cannot be assured (as is the case, for example, of an emergency breaking) together with error-detection and error-recovery. \ subsection\Capturing ``System Architecture.''\ text\ \begin{figure} \centering \includegraphics[width=.70\textwidth]{figures/three-phase-odo} \begin{picture}(0,0) \put(-112,44){\includegraphics[width=.30\textwidth]{figures/odometer}} \end{picture} \caption{An odometer with three sensors \inlineisar{C1}, \inlineisar{C2}, and \inlineisar{C3}.}\label{three-phase} \end{figure} The requirements analysis also contains a sub-document \<^emph>\system architecture description\ (CENELEC notion) that contains technical drawing of the odometer, a timing diagrams (see \autoref{three-phase}), and tables describing the encoding of the position for the possible signal transitions of the sensors \inlineisar{C1}, \inlineisar{C2}, and $C3.$ \ subsection\Capturing ``System Interfaces.''\ text\ The requirements analysis also contains a sub-document \<^emph>\functions and interfaces\ (CENELEC notion) describing the technical format of the output of the odometry function. This section, \eg, specifies the output \<^emph>\speed\ as given by a \<^verbatim>\int_32\ to be the ``Estimation of the speed (in mm/sec) evaluated over the latest $N_{\text{avg}}$ samples'' where the speed refers to the physical speed of the train and $N_{\text{avg}}$ a parameter of the sub-system configuration. \ (*<*) declare_reference*["df-numerics-encshaft"::figure] (*>*) subsection\Capturing ``Required Performances.''\ text\ The given analysis document is relatively implicit on the expected precision of the measurements; however, certain interface parameters like \inlineisar*Odometric_Position_TimeStamp* (a counter on the number of samplings) and \inlineisar*Relative_Position* are defined by as unsigned 32 bit integer. These definitions imply that exported constraints concerning the acceptable time of service as well the maximum distance before a necessary reboot of the subsystem. For our case-study, we assume maximum deviation of the \inlineisar*Relative_Position* to the theoretical distance. The requirement analysis document describes the physical environment, the architecture of the measuring device, and the required format and precision of the measurements of the odometry function as represented (see @{figure (unchecked) "df-numerics-encshaft"}).\ figure*["df-numerics-encshaft"::figure,relative_width="76",src="''figures/df-numerics-encshaft''"] \Real distance vs. discrete distance vs. shaft-encoder sequence\ subsection\Capturing the ``Software Design Spec'' (Resume).\ text\ \enlargethispage{\baselineskip} The design provides a function that manages an internal first-in-first-out buffer of shaft-encodings and corresponding positions. Central for the design is a step-function analyzing new incoming shaft encodings, checking them and propagating two kinds of error-states (one allowing recovery, another one, fatal, signaling, \eg, a defect of the receiver hardware), calculating the relative position, speed and acceleration. \ subsection\Capturing the ``Software Implementation'' (Resume).\ text\ While the design is executable on a Linux system, it turns out that the generated code from an Isabelle model is neither executable on resource-constraint target platform, an ARM-based Sabre-light card, nor certifiable, since the compilation chain via ML to C implies the inclusion of a run-time system and quite complex libraries. We adopted therefore a similar approach as used in the seL4 project~@{cite "Klein2014"}: we use a hand-written implementation in C and verify it via AutoCorres~@{cite "greenaway.ea:bridging:2012"} against the design model. The hand-written C-source is integrated into the Isabelle/HOL technically by registering it in the build-configuration and logically by a trusted C-to-HOL compiler included in AutoCorres. \ section\Formal Enrichment of the Software Requirements Specification\ text\ After the \<^emph>\capture\-phase, where we converted/integrated existing informal analysis and design documents as well as code into an integrated Isabelle document, we entered into the phase of \formal enrichment\. For example, from the assumptions in the architecture follow the definitions: \begin{isar} definition teeth_per_wheelturn::nat ("tpw") where "tpw \ SOME x. x > 0" definition wheel_diameter::real ("w$_d$") where "w$_d$ \ SOME x. x > 0" definition wheel_circumference::real ("w$_{\text{circ}}$") where "w$_{\text{circ}}$ \ pi * w$_d$" definition \s$_{\text{res}}$::real where "\s$_{\text{res}}$ \ w$_{\text{circ}}$ / (2 * 3 * tpw)" \end{isar} Here, \inlineisar{real} refers to the real numbers as defined in the HOL-Analysis library, which provides concepts such as Cauchy Sequences, limits, differentiability, and a very substantial part of classical Calculus. \inlineisar{SOME} is the Hilbert choice operator from HOL; the definitions of the model parameters admit all possible positive values as uninterpreted constants. Our perfect-wheel assumption is translated into a calculation of the circumference of the wheel, while \inlineisar{\sres}, the resolution of the odometer, can be calculated from the these parameters. HOL-Analysis permits to formalize the fundamental physical observables: \begin{isar} type_synonym distance_function = "real\real" definition Speed::"distance_function\real\real" where "Speed f \ deriv f" definition Accel::"distance_function\real\real" where "Accel f \ deriv (deriv f)" \end{isar} which permits to constrain the central observable \inlineisar|distance_function| in a way that they describe the space of ``normal behavior'' where we expect the odometer to produce reliable measurements over a \inlineisar|distance_function df|. The essence of the physics of the train is covered by the following definition: \begin{isar} definition normally_behaved_distance_function :: "(real \ real) \ bool" where normally_behaved_distance_function df = ( \ t. df(t) \ \$_{\ge 0}$ \ (\ t \ \$_{\le 0}$. df(t) = 0) \ df differentiable on$_{\text{R}}$ \ (Speed df)differentiable on$_{\text{R}}$ \ (Accel df)differentiable on$_{\ensuremath{R}}$ \ (\ t. (Speed df) t \ {-Speed$_{\text{Max}}$ .. Speed$_{\text{Max}}$}) \ (\ t. (Accel df) t \ {-\Accel$_{\text{Max}}$\ .. \Accel$_{\text{Max}}$\})) \end{isar} which constrains the distance functions in the bounds described of the informal descriptions and states them as three-fold differentiable function in certain bounds concerning speed and acceleration. Note that violations, in particular of the constraints on speed and acceleration, \<^emph>\do\ occur in practice. In such cases, the global system adapts recovery strategies that are out of the scope of our model. Concepts like \inlineisar+shaft_encoder_state+ (a triple with the sensor values \inlineisar{C1}, \inlineisar{C2}, \inlineisar{C3}) were formalized as types, while tables were defined as recursive functions: \enlargethispage{2\baselineskip}\begin{isar} fun phase$_0$ :: "nat \ shaft_encoder_state" where "phase$_0$ (0) = \ C1 = False, C2 = False, C3 = True \" |"phase$_0$ (1) = \ C1 = True, C2 = False, C3 = True \" |"phase$_0$ (2) = \ C1 = True, C2 = False, C3 = False\" |"phase$_0$ (3) = \ C1 = True, C2 = True, C3 = False\" |"phase$_0$ (4) = \ C1 = False, C2 = True, C3 = False\" |"phase$_0$ (5) = \ C1 = False, C2 = True, C3 = True \" |"phase$_0$ x = phase$_0$(x - 6)" definition Phase ::"nat\shaft_encoder_state" where Phase(x) = phase$_0$(x-1) \end{isar} We now define shaft encoder sequences as translations of distance functions: \begin{isar} definition encoding::"distance_function\nat\real\shaft_encoder_state" where "encoding df init$_{\text{pos}}$ \ \x. Phase(nat\df(x) / \s$_{\text{res}}$\ + init$_{\text{pos}}$)" \end{isar} where \inlineisar+init$_{\text{pos}}$+ is the initial position of the wheel. \inlineisar+sampling+'s were constructed from encoding sequences over discretized time points: \begin{isar} definition $\!\!$sampling::"distance$\!$_function\nat\real\nat\shaft$\!$_encoder$\!$_state" where "sampling df init$_{\text{pos}}$ \t \ \n::nat. encoding df init$_{\text{pos}}$ (n * \t)" \end{isar} The sampling interval \inlineisar+\t+ (the inverse of the sampling frequency) is a critical parameter of the configuration of a system. Finally, we can formally define the required performances. From the interface description and the global model parameters such as wheel diameter, the number of teeth per wheel, the sampling frequency etc., we can infer the maximal time of service as well the maximum distance the device can measure. As an example configuration, choosing 1m for \inlineisar+w$_d$+, 100 for \inlineisar+tpw+, 80km/h \inlineisar+Speed$_{\text{Max}}$+, and 14400Hz for the sampling frequency, results in an odometer resolution of 2.3mm, a maximum distance of 9878km, and a maximal system up-time of 123.4 hours. The required precision of an odometer can be defined by a constant describing the maximally allowed difference between \inlineisar+df(n*\t)+ and \inlineisar+sampling df init$_{\text{pos}}$ \t n+ for all \inlineisar+init$_{\text{pos}}$ \{0..5}+. \ (*<*) ML\val two_thirty2 = 1024 * 1024 * 1024 * 4; val dist_max = 0.0023 * (real two_thirty2) / 1000.0; val dist_h = dist_max / 80.0\ (*>*) section*[verific::technical]\Verification of the Software Requirements Specification\ text\The original documents contained already various statements that motivate certain safety properties of the device. For example, the \inlineisar+Phase+-table excludes situations in which all sensors \inlineisar{C1}, \inlineisar{C2}, and \inlineisar{C3} are all ``off'' or situations in which sensors are ``on,'' reflecting a physical or electrical error in the odometer. It can be shown by a very small Isabelle case-distinction proof that this safety requirement follows indeed from the above definitions: \begin{isar} lemma Encoder_Property_1:(C1(Phase x) \ C2(Phase x) \ C3(Phase x))=False proof (cases x) case 0 then show ?thesis by (simp add: Phase_def) next case (Suc n) then show ?thesis by(simp add: Phase_def,rule_tac n = n in cycle_case_split,simp_all) qed \end{isar} for all positions \inlineisar+x+. Similarly, it is proved that the table is indeed cyclic: \inlineisar+ phase$_0$ x = phase$_0$(x mod 6)+ and locally injective: \inlineisar+\x<6. \y<6. phase$_0$ x = phase$_0$ y \ x = y+. These lemmas, building the ``theory of an odometer,'' culminate in a theorem that we would like to present in more detail. \begin{isar} theorem minimal_sampling : assumes * : normally_behaved_distance_function df and ** : \t * Speed$_{\text{Max}}$ < \s$_{\text{res}}$ shows \ \X\\t. 0<\X \ \f. retracting (f::nat\nat) \ sampling df init$_{\text{pos}}$ \X = (sampling df init$_{\text{pos}}$ \t) o f \end{isar} This theorem states for \inlineisar+normally_behaved_distance_function+s that there is a minimal sampling frequency assuring the safety of the measurements; samplings on some \inlineisar$df$ gained from this minimal sampling frequency can be ``pumped up'' to samplings of these higher sampling frequencies; they do not contain more information. Of particular interest is the second assumption, labelled ``\inlineisar|**|,'' which establishes a lower bound from \inlineisar+w$_{\text{circ}}$+, \inlineisar+tpw+, \inlineisar+Speed$_{\text{Max}}$+ for the sampling frequency. Methodologically, this represents an exported constraint that can not be represented \<^emph>\inside\ the design model: it means that the computations have to be fast enough on the computing platform in order to assure that the calculations are valid. It was in particular this exported constraint that forced us to give up the original plan to generate the code from the design model and to execute this directly on the target platform. For our example configuration (1m diameter, 100 teeth per wheel, 80km/h max), this theorem justifies that 14,4 kHz is indeed enough to assure valid samplings. Such properties are called ``internal consistency of the software requirements specification'' in the CENELEC standard~@{cite "bsi:50128:2014"}, 7.2.4.22 and are usually addressed in an own report. \ chapter*[ontomodeling::text_section]\The CENELEC 50128 Ontology\ text\ Modeling an ontology from a semi-formal text such as~@{cite"bsi:50128:2014"} is, like any other modeling activity, not a simple one-to-one translation of some concepts to some formalism. Rather, implicit and self-understood principles have to be made explicit, abstractions have to be made, and decisions about the kind of desirable user-interaction may have an influence similarly to design decisions influenced by strengths or weaknesses of a programming language. \ section*[lhf::text_section] \Tracking Concepts and Definitions\ text\ \isadof is designed to annotate text elements with structured meta-information and to reference these text elements throughout the integrated source. A classical application of this capability is the annotation of concepts and terms definitions---be them informal, semi-formal or formal---and their consistent referencing. In the context of our CENELEC ontology, \eg, we can translate the third chapter of @{cite "bsi:50128:2014"} ``Terms, Definitions and Abbreviations'' directly into our Ontology Definition Language (ODL). Picking one example out of 49, consider the definition of the concept ``traceability'' in paragraphs 3.1.46 (a notion referenced 31 times in the standard), which we translated directly into: \begin{isar} Definition*[traceability::concept] degree to which relationship can be established between two or more products of a development process, especially those having a predecessor/successor or master/subordinate relationship to one another. \end{isar} In the integrated source of the odometry study, we can reference in a text element to this concept as follows: \begin{isar} text*[...] ... to assure <@>{concept traceability} for <@>{requirement bitwiseAND}, we prove ... \end{isar} The presentation of this document element inside \isadof is immediately hyperlinked against the \inlineisar+Definition*+ element shown above; this serves as documentation of the standard for the development team working on the integrated source. The PDF presentation of such links depends on the actual configurations for the document generation; We will explain this later. CENELEC foresees also a number of roles, phases, safety integration levels, etc., which were directly translated into HOL enumeration types usable in ontological concepts of ODL. \begin{isar} datatype role = PM (* Program Manager *) | RQM (* Requirements Manager *) | DES (* Designer *) | IMP (* Implementer *) | | VER (* Verifier *) | VAL (* Validator *) | ... datatype phase = SYSDEV_ext (* System Development *) | SPl (* Software Planning *) | SR (* Software Requirement *) | SA (* Software Architecture *) | SDES (* Software Design *) | ... \end{isar} Similarly, we can formalize the Table A.5: Verification and Testing of @{cite "bsi:50128:2014"}: a classification of \<^emph>\verification and testing techniques\: \begin{isar} datatype vnt_technique = formal_proof "thm list" | stat_analysis | dyn_analysis dyn_ana_kind | ... \end{isar} In contrast to the standard, we can parameterize \inlineisar+formal_proof+ with a list of theorems, an entity known in the Isabelle kernel. Here, \isadof assures for text elements annotated with theorem names, that they refer indeed to established theorems in the Isabelle environment. Additional checks could be added to make sure that these theorems have a particular form. While we claim that this possibility to link to theorems (and test-results) is unique in the world of systems attempting to assure traceability, referencing a particular (proven) theorem is definitively not sufficient to satisfy the claimed requirement. Human evaluators will always have to check that the provided theorem \adequately\ represents the claim; we do not in the slightest suggest that their work is superfluous. Our framework allows to statically check that tests or proofs have been provided, at places where the ontology requires them to be, and both assessors and developers can rely on this check and navigate through related information easily. It does not guarantee that intended concepts for, \eg, safety or security have been adequately modeled. \ section*[moe::text_section] \Major Ontological Entities: Requirements and Evidence\ text\ We introduce central concept of a \<^emph>\requirement\ as an ODL \inlineisar*doc_class* based on some generic basic library \inlineisar*text_element* providing basic layout attributes. \begin{isar} doc_class requirement = text_element + long_name :: "string option" is_concerned :: "role set" \end{isar} where the \inlineisar*roles* are exactly the ones defined in the previous section and represent the groups of stakeholders in the CENELEC process. Therefore, the \inlineisar+is_concerned+-attribute allows expressing who ``owns'' this text-element. \isadof supports a role-based presentation, \eg, different presentation styles of the integrated source may decide to highlight, to omit, to defer into an annex, text entities according to the role-set. Since ODL supports single inheritance, we can express sub-requirements and therefore a style of requirement decomposition as advocated in GSN~@{cite "kelly.ea:goal:2004"}: \begin{isar} doc_class sub_requirement = decomposes :: "requirement" relates_to :: "requirement set" \end{isar}\ section*[claimsreqevidence::text_section]\Tracking Claims, Derived Requirements and Evidence\ text\An example for making explicit implicit principles, consider the following statement @{cite "bsi:50128:2014"}, pp. 25.:\vspace{-1.5mm} \begin{quote}\small The objective of software verification is to examine and arrive at a judgment based on evidence that output items (process, documentation, software or application) of a specific development phase fulfill the requirements and plans with respect to completeness, correctness and consistency. \end{quote}\vspace{-1.5mm} The terms \<^emph>\judgment\ and \<^emph>\evidence\ are used as a kind of leitmotif throughout the CENELEC standard, but they are neither explained nor even listed in the general glossary. However, the standard is fairly explicit on the \<^emph>\phase\s and the organizational roles that different stakeholders should have in the process. Our version to express this key concept of judgment, \eg, by the following concept: \begin{isar} doc_class judgement = refers_to :: requirement evidence :: "vnt_technique list" status :: status is_concerned :: "role set" <= "{VER,ASR,VAL}" \end{isar} As one can see, the role set is per default set to the verification team, the assessors and the validation team. There are different views possible here: an alternative would be to define \inlineisar+evidence+ as ontological concept with \inlineisar+vnt_technique+'s (rather than an attribute of judgement) and consider the basis of judgments as a relation between requirements and relation: \begin{isar} doc_class judgement = based_on :: "(requirement \ evidence) set" status :: status is_concerned :: "role set" <= "{VER,ASR,VAL}" \end{isar} More experimentation will be needed to find out what kind of ontological modeling is most adequate for developers in the context of \isadof. \ section*[ontocontrol::text_section]\Ontological Compliance\ text\From the variety of different possibilities for adding CENELEC annotations to the integrated source, we will, in the following, point out three scenarios.\ subsection\Internal Verification of Claims in the Requirements Specification.\ text\In our case, the SR-team early on detected a property necessary for error-detection of the device (c.f. @{technical verific}): \enlargethispage{2\baselineskip}\begin{isar} text*[encoder_props::requirement] The requirement specification team ... C1 & C2 & C3 = 0 (bitwise logical AND operation) C1 | C2 | C3 = 1 (bitwise logical OR operation) \end{isar} After the Isabelle proofs shown in @{technical verific}, we can either register the theorems directly in an evidence statement: \begin{isar} text*[J1::judgement, refers_to="<@>{docitem encoder_props}", evidence="[formal_proof[<@>{thm Encoder_Property_1}, <@>{thm Encoder_Property_2}]]"] The required encoder properties are in fact verified to be consistent with the formalization of <@>{term "phase$_0$"}. \end{isar} The references \inlineisar|<@>{...}|, called antiquotation, allow us not only to reference to formal concepts, they are checked for consistency and there are also antiquotations that print the formally checked content (\eg, the statement of a theorem). \ subsection\Exporting Claims of the Requirements Specification.\ text\By definition, the main purpose of the requirement specification is the identification of the safety requirements. As an example, we state the required precision of an odometric function: for any normally behaved distance function \inlineisar+df+, and any representable and valid sampling sequence that can be constructed for \inlineisar+df+, we require that the difference between the physical distance and distance calculable from the @{term Odometric_Position_Count} is bound by the minimal resolution of the odometer. \begin{isar} text*[R5::safety_requirement]We can now state ... definition Odometric_Position_Count_precise::(shaft_encoder_state list\output)\bool where Odometric_Position_Count_precise odofunction \ (\ df. \S. normally_behaved_distance_function df \ representable S \ valid_sampling S df \ (let pos = uint(Odometric_Position_Count(odofunction S)) in \df((length S - 1)*\t$_{\text{odo}}$) - (\s$_{\text{res}}$ * pos)\ \ \s$_{\text{res}}$)) update_instance*[R5::safety_requirement, formal_definition:="[<@>{thm Odometric_Position_Count_precise_def}]"] \end{isar} By \inlineisar+update_instance*+, we book the property \inlineisar+Position_Count_precise_def+ as \inlineisar+safety_requirement+, a specific sub-class of \inlineisar+requirement+s requesting a formal definition in Isabelle.\ subsection\Exporting Derived Requirements.\ text\Finally, we discuss the situation where the verification team discovered a critical side-condition for a major theorem necessary for the safety requirements; this was in our development the case for the condition labelled ``\inlineisar|**|'' in @{docitem verific}. The current CENELEC standard clearly separates ``requirement specifications'' from ``verification reports,'' which is probably motivated by the overall concern of organizational separation and of document consistency. While this document organization is possible in \isadof, it is in our experience often counter-productive in practice: organizations tend to defend their documents because the impact of changes is more and more difficult to oversee. This effect results in a dramatic development slow-down and an increase of costs. Furthermore, these barriers exclude situations where developers perfectly know, for example, invariants, but can not communicate them to the verification team because the precise formalization is not known in time. Rather than advocating document separation, we tend to integrate these documents, keep proof as close as possible to definitions, and plead for consequent version control of the integrated source, together with the proposed methods to strengthen the links between the informal and formal parts by anti-quotations and continuous ontological checking. Instead of separation of the documents, we would rather emphasize the \<^emph>\separation of the views\ of the different document representations. Such views were systematically generated out of the integrated source in different PDF versions and for each version, document specific consistency guarantees can be automatically enforced. In our case study, we define this condition as predicate, declare an explanation of it as \inlineisar+SRAC+ (CENELEC for: safety-related application condition; ontologically, this is a derived class from \inlineisar+requirement+.) and add the definition of the predicate into the document instance as described in the previous section.\ text\\appendix\ chapter\Appendix\ text\ \<^item> \inlineisar|<@>{thm refl}|: @{thm refl} \<^item> \inlineisar|<@>{thm [source] refl}|: @{thm [source] refl} \<^item> \inlineisar|<@>{thm[mode=Rule] conjI}|: @{thm[mode=Rule] conjI} \<^item> \inlineisar|<@>{file "mini_odo.thy"}|: @{file "mini_odo.thy"} \<^item> \inlineisar|<@>{value "3+4::int"}|: @{value "3+4::int"} \<^item> \inlineisar|<@>{const hd}|: @{const hd} \<^item> \inlineisar|<@>{theory HOL.List}|: @{theory HOL.List} \<^item> \inlineisar|<@>{term "3"}|: @{term "3"} \<^item> \inlineisar|<@>{type bool}|: @{type bool} \<^item> \inlineisar|<@>{term [show_types] "f x = a + x"}|: @{term [show_types] "f x = a + x"} \ text\Examples for declaration of typed doc-items "assumption" and "hypothesis", concepts defined in the underlying ontology @{theory "Isabelle_DOF.CENELEC_50128"}. \ text*[ass2::assumption, long_name="Some ''assumption one''"] \ The subsystem Y is safe. \ text*[hyp1::hypothesis] \ P not equal NP \ text\A real example fragment from a larger project, declaring a text-element as a "safety-related application condition", a concept defined in the @{theory "Isabelle_DOF.CENELEC_50128"} ontology:\ text*[hyp2::hypothesis]\Under the assumption @{assumption \ass2\} we establish the following: ... \ text*[ass122::SRAC, long_name="Some ''ass122''"] \ The overall sampling frequence of the odometer subsystem is therefore 14 khz, which includes sampling, computing and result communication times... \ text*[ass123::SRAC] \ The overall sampling frequence of the odometer subsystem is therefore 14 khz, which includes sampling, computing and result communication times... \ text*[ass124::EC, long_name="Some ''ass124''"] \ The overall sampling frequence of the odometer subsystem is therefore 14 khz, which includes sampling, computing and result communication times... \ text*[t10::test_result] \ This is a meta-test. This could be an ML-command that governs the external test-execution via, eg., a makefile or specific calls to a test-environment or test-engine. \ text\Finally some examples of references to doc-items, i.e. text-elements with declared meta-information and status. \ text \ As established by @{test_result (unchecked) \t10\}, @{test_result (define) \t10\} \ text \ the @{test_result \t10\} as well as the @{SRAC \ass122\}\ text \ represent a justification of the safety related applicability condition @{SRAC \ass122\} aka exported constraint @{EC \ass122\}.\ (* due to notational conventions for antiquotations, one may even write: *) (* CRASHES WITH LaTeX backend error. *) text \ represent a justification of the safety related applicability condition \<^SRAC>\ass122\ aka exported constraint \<^EC>\ass122\.\ (*<*) end (*>*)