Applicability of generalized test tables: a case study using the manufacturing system demonstrator xPPU

Suhyun Cha; Alexander Weigl; Mattias Ulbrich; Bernhard Beckert; Birgit Vogel-Heuser

doi:10.1515/auto-2018-0028

Published by De Gruyter (O) October 17, 2018

Applicability of generalized test tables: a case study using the manufacturing system demonstrator xPPU

Anwendbarkeit von Generalized Test Tables: Eine Fallstudie anhand des xPPU-Demonstrators

Suhyun Cha
Suhyun Cha, M. Sc., is a research assistant at the Institute of Automation and Information Systems at the Technical University of Munich. Her main research interest focuses on software engineering for quality assurance of automated production systems especially using formal methods.
, Alexander Weigl
Alexander Weigl is a PhD researcher in the group Application-oriented Formal Verification at the Karlsruhe Institute of Technology (KIT). He received the M.Sc. from the KIT in 2015 and the B.Sc. from the University of Applied Science Trier in 2012. His research interest is the functional and relational verification of automated production system and writing biographies for papers’ appendices.
, Mattias Ulbrich
Mattias Ulbrich is a researcher in the group Application-oriented Formal Verification at the Karlsruhe Institute of Technology (KIT). He received his Ph.D. from KIT in 2013. His main research focus is the specification and deductive verification of programs, in particular the verification of relational system properties.
, Bernhard Beckert
Bernhard Beckert is a full professor at the Karlsruhe Institute of Technology, where he founded and leads the Research Group on Application-oriented Formal Verification. After receiving his doctoral degree from the University of Karlsruhe in 1998, he was Assistand and Associate Professor at the University of Koblenz-Landau. His research focuses on formal, logic-based methods for the specification and verification of software, in particular for the application areas software dependability, IT security, relational software evolution, and social choice theory.
and Birgit Vogel-Heuser
Prof. Dr.-Ing. Birgit Vogel-Heuser graduated in electrical engineering and received the Ph. D. in mechanical engineering from the RWTH Aachen in 1991. She worked for nearly ten years in industrial automation in the machine and plant manufacturing industry. After holding different chairs of automation she has been head of the Institute of Automation and Information Systems at the Technical University of Munich since 2009. Her research work is focused on modeling and education in automation engineering for distributed and intelligent systems.

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https://doi.org/10.1515/auto-2018-0028

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Abstract

With recent trends in manufacturing automation, control software in automated production systems becomes more complex and has more variability to keep pace with customer and market requirements. Quality assurance also becomes more and more important to ensure that the systems live up to expectations. However, correctness of automation software is rarely verified using formal techniques in spite of their high coverage. One of the main reasons is the lack of specification languages suitable for this application area that are both comprehensible and sufficiently expressive. Generalized test tables (GTTs), which are a specification language for reactive systems, were presented recently as an accessible representation for application engineers. This formalism achieves both the comprehensibility of concrete test tables and the coverage of formal methods. In our approach, the specification provided by GTTs is used for formal verification, especially model checking. In this paper, we present four new features for GTTs: the progression flag, strong repetition, row grouping, and specification on internal variables. We demonstrate the applicability and evaluate the comprehensibility of GTT-based specification and verification using a range of diverse scenarios from the community demonstrator, the extended Pick & Place Unit.

Zusammenfassung

Steigende Kunden- und Marktanfordungen in der Fertigungsautomatisierung erfordern komplexere Steuerungssoftware und kürzere Entwicklungszyklen. Um zukünftig Korrektheit und Zuverlässigkeit sicherstellen zu können, ist eine Anpassung an der Qualitätssicherung erforderlich. Formale Methoden können hierfür nachprüfbare Garantien bieten, aber obwohl Automatisierungstechnik in unternehmenskritischen Bereichen eingesetzt wird, werden formale Methoden dort selten verwendet. Einer der Gründe ist der Mangel an geeigneten Spezifikationssprachen für die Automatisierungsdomäne, die sowohl nachvollziehbar als auch ausreichend aussagekräftig sind. Generalized Test Tables (GTTs) sind eine formale tabellen-basierte Spezifikationssprache für reaktive Systeme für den Entwicklungsingenieur. GTTs erhöhen die Aussagemächtigkeit und Testabdeckung konkreter Testtabellen unter Beibehaltung ihrer Verständlichkeit. In diesem Beitrag analysieren wir die Anwendbarkeit und Verständlichkeit von GTTs. Dazu spezifizieren wir Teile des Anlagenverhaltens diverser Szenarien aus dem Community Demonstrator Pick&Place-Unit (PPU).

Keywords: formal verification; formal specification; functional specification; software engineering; manufacturing system engineering

Schlagwörter: formale Verifikation; formale Spezifikation; funktionale Spezifikation; Software-Engineering; Fertigungssystem-Engineering

Funding source: Deutsche Forschungsgemeinschaft

Award Identifier / Grant number: VO 937/28-2

Award Identifier / Grant number: BE 2334/7-2

Award Identifier / Grant number: UL 433/1-2

Funding statement: Research supported by the DFG (German Research Foundation) in Priority Programme SPP1593: Design for Future – Managed Software Evolution (VO 937/28-2, BE 2334/7-2, and UL 433/1-2).

About the authors

Suhyun Cha

Suhyun Cha, M. Sc., is a research assistant at the Institute of Automation and Information Systems at the Technical University of Munich. Her main research interest focuses on software engineering for quality assurance of automated production systems especially using formal methods.

Alexander Weigl

Alexander Weigl is a PhD researcher in the group Application-oriented Formal Verification at the Karlsruhe Institute of Technology (KIT). He received the M.Sc. from the KIT in 2015 and the B.Sc. from the University of Applied Science Trier in 2012. His research interest is the functional and relational verification of automated production system and writing biographies for papers’ appendices.

Mattias Ulbrich

Mattias Ulbrich is a researcher in the group Application-oriented Formal Verification at the Karlsruhe Institute of Technology (KIT). He received his Ph.D. from KIT in 2013. His main research focus is the specification and deductive verification of programs, in particular the verification of relational system properties.

Bernhard Beckert

Bernhard Beckert is a full professor at the Karlsruhe Institute of Technology, where he founded and leads the Research Group on Application-oriented Formal Verification. After receiving his doctoral degree from the University of Karlsruhe in 1998, he was Assistand and Associate Professor at the University of Koblenz-Landau. His research focuses on formal, logic-based methods for the specification and verification of software, in particular for the application areas software dependability, IT security, relational software evolution, and social choice theory.

Birgit Vogel-Heuser

Prof. Dr.-Ing. Birgit Vogel-Heuser graduated in electrical engineering and received the Ph. D. in mechanical engineering from the RWTH Aachen in 1991. She worked for nearly ten years in industrial automation in the machine and plant manufacturing industry. After holding different chairs of automation she has been head of the Institute of Automation and Information Systems at the Technical University of Munich since 2009. Her research work is focused on modeling and education in automation engineering for distributed and intelligent systems.

Appendix A Definition for the new features

In this section we present the updated definitions for the structure of GTT ([3, Def. 3]), and the definition of unrolled instances (D1(T) cf. [3, Def. 3]).

In earlier version the duration interval is an interval [m,n], where m∈N and n∈N∪{⊥}.

In the previous work, the structure of a GTT is defined as a sequence of triples (input, output and duration constraint). Strong repetition and progress flag requires extension on the domain of the duration constraints τ:

Definition 1 (Duration interval τ).

A duration interval is either ω (strong repetition), an (top-open) interval[m,n]with or without the progress flag:

τ∈{ω}∪{[m,n]p∣m∈N,n∈N∞}∪{[m,n]p∣m∈N,n∈N∞}

withN∞=N∪{∞}.

We define a function val(τ) that evaluates a duration constraint into a set of possible repetitions.

Definition 2 (val(τ)).

(1)val:τ↦{ω}τ=ω{x∣n≥x}τ=[n,∞]∨τ=[n,∞]p{x∣n≤x≤m}τ=[n,m]∨τ=[n,m]p

With the introduction of nested blocks, this sequential structure becomes obsolete. The new mathematical structure is defined inductively to capture the recursive nature of GTTs.

Definition 3 (GTTs as a Tree of Constraints).

LetInVarbe the set of input variables,OutVarbe the set of output variables, andGVarbe the set of global variables; then the set of all GTTsTΣover signatureΣ=InVar∪OutVar∪GVar. is defined as

base

The empty table ϵ and a single row(ϕ,ψ,τ)are GTTs (ϵ,(ϕ,ψ,τ)∈T, ϕ is the conjunction of all input column constraints of a row, resp. ψ for the output columns and τ defines the duration interval).

step

LetT∈Ta GTT, then

seq: the sequential composition⟨T,T′⟩∈Tis also a GTT, whereT,T′∈T.
nest: the repetition of a GTT T is also a GTT:[T,τ]∈Twith an arbitrary duration interval τ andT∈T.

The set InVar and OutVar also includes the categorized state variables. The constraints formulas ϕ and ψ are Boolean formulas over the signature Σ. The sequential composition with the empty table cover the GTTs as defined in [3]. We use angle brackets to denote the sequence, and parentheses to denote a row. ϵ denotes the empty table. The nest rule creates the nested row groups, denoted by brackets.

Example 1.

The GTT in Fig. 4is represented by the following structure for a cycle of 100 ms.

[(¬WP∨ERR,true,—p),(WP∧¬ERR,MOVE=Stop,[1,∞])[(¬WP∧¬ERR,MOVE=Fwd,[50,60]),[0,1]][⟨[(ERR,MOVE=Fwd,[10,10])(ERR,MOVE=Rwd,[10,10])(WP∧ERR,MOVE=Stop,[5,5]),[0,3]],(WP∧¬ERR,MOVE=Stop,[1,1])⟩,[0,1]],ω]

The game [3, Fig. 4] maintains the set S=D1(T), which represents the possible remaining test table. D1(T) defines a infinite language over the alphabet Σ=FmlΣ×FmlΣ, where FmlΣ is the set of all Boolean formulas over signature Σ. We define D1′(T)—a version for GTTs after Def. 3. D1′(T) transform the recursive data structure into an (infinite) set of (in)finite words.

(2)D1′(T)=def{ϵ}ifT=ϵ(ϕ,ψ)τifT=(ϕ,ψ,τ)D1′(T′)·D1′(T″)ifT=⟨T′;T″⟩D1′(T′)τifT=[T′,τ]⟩

Note, ϵ denotes the empty word, and Lτ=⋃k∈val(τ)Lk. With D1′(T) we are back into the framework given in [3] with one exception: D1′(T) could contain infinite words. The game remains applicable, but an infinite word in D1′(T) prevents the win of the system by reaching the table end.

Appendix B Semantic impact: No strict conformance

The following proposition rephrase the termination of the game:

Proposition 1.

Termination of the game [3, Fig. 4] The game terminates in roundk>0

ifS=∅after the turn of the challenger (System wins, Line 13)
ifS=∅after the turn of the system (Challenger wins, Line 17)
if the end of the table is reached∃D∈S.|D|=k(System wins, Line 21).

S denotes the set of the currently remaining valid unwound GTTs.

The next proposition is generalization of the statement, that a strong repetition prevents strict conformance.

Proposition 2.

LetSkbe set of remaining test tables in round k. If all remaining test tables are infinite∀w∈Sk.|w|=ωthen the system can not win by Line 21 (end of table).

Proof.

The first implication is a direct consequence that k is always finite: k∈N and ∀n∈N.n<ω. □

Moreover for the prevention, we need to require the existence of a challenger that can survive infinitely long. Therefore all input constraints ϕ, especially these the strong repeated rows, need always be satisfiable.

Proposition 3.

If there exist infinite valid challenger stimuliin, i. e.

∃w∈Sk.∀k∈N.in[k]⊧ϕ[k]

then there does not exists a strict conform system.ϕ[k]is the input constraint givenw[k].

Proof.

Let there be a strict conform system. Also, the system wins against every challenger. The win by end-of-table is disabled and there exists a challenger which has a never-ending valid play. The system can not win. Contradiction! □

Appendix C Proof: Strong repetition does not extend the expressiveness

After defining the structure in Def. 3. We can define the transformation of T∞ to T∗ formally.

Definition 4 (Construction ofT∗).

T∗for a given GTTT∞is constructed by the following recursive functiontrans(T∞):

(3)trans(T)=def

(4)ϵifT=ϵ⟨(ϕ,ψ,τ),trans(T′)⟩ifT=⟨(ϕ,ψ,τ),T′⟩∧τ≠—∞[trans(T′),τ]ifT=[T′,τ]∧τ≠—∞⟨(ϕ,ψ,—),(ϕ,false,1),trans(T′)⟩ifT=⟨(ϕ,ψ,—∞),T′⟩⟨[trans(T′),—],(Φ(T′),false,1)⟩ifT=[T′,—∞]

Φ(T)is defined by the disjunction⋁(ϕ,ψ,τ)∈succ(0)ϕof all immediately reachable rowssucc(0)in T from the start (cf. functionsuccin [3]).

We introduce I and O as finite sets that denote the value domain of the input and output variables of the reactive system, determined by the system’s interface (variable type).

Our goal is to prove the equal weak and strict conformance.

Proposition 4 (Equal Conformance).

A reactive system is weak conform toT∞iff it is conform toT∗, analog for strict conform.

The conformance of a test table is based on the outcome of all possible plays, i. e. a system is strict conform iff it is a winning strategy and weak conform iff its strategy never loss.

The next lemma reduces the equal conformance on equal game outcome on all plays.

Lemma 1.

Two GTTT,T′have equal conformance if the game outcome for all possible plays is equal.

In rest of the proof for Prop. 4, we need to show that for an arbitrary play, without assumption on the table or the system, the outcome (winner and loser) is equal on T∗ and T∞. The outcome is determined by the algorithm [3, Fig. 4]. We show that by defining a coupling between both run of the algorithm for T∗ and T∞. More formally, the algorithm based on a set S (cf. Lemma 1), that holds the remaining possible unwound GTT. S is determined by D1′(T) in the beginning. The outcome is decided within one round of the game, especially if S becomes empty. We established a coupling relation between the set S from the run over T∞ and T∗: S∞k and S∗k for round 0<k. The coupling relation established a bisimulation.

To define the coupling relation, we need following property on the structure of S∞k and S∗k.

Lemma 2 (Structure ofSk).

In every roundk≥0,S∞kandS∗kcan be separated:

(5)S∞k=Lfin∪⋃lαl·βlω

(6)S∗k=Lfin∪⋃lαl·βl∗(Φ,false)

for a languageαlandβl.

Lfin contains the finite words defined of a test tables, e. g., if a strong repetition is avoidable. It is also possible to select a separation, s. t. αl is the path into an strong repetition, and βl is the strong repetition. There are only a finite amount of strong repetition, the set union is finite. Moreover in the separation Sk, β represents the block (or row), that is strong repeated, which is implicitly described in Lemma 3. This connects the βl with the construction T∗, especially Φl.

Further, we define the languages VC,VS⊆Sk, that represent the words in Sk that are violated by turns of the challenger or the system.

Definition 5.

Let S be language of(ϕ,ψ),p∈(I,O)∗a play, andk>0:

(7)VC(S,p,k)={w∈Sk∣(ϕ,ψ)=w[k−1]∧p⊭ϕ}

(8)VS(S,p,k)={w∈Sk∣(ϕ,ψ)=w[k−1]∧p⊭ϕ∧ψ}

(Proof by induction over k).

For k=0, the separation follows immediately from the Definition of D1′, S0 is actually regular.

For k>0, in every round Sk is filtered by the current play p with |p|=k, formally Sk=(Lfin∪Sk−1)∖VS(S,p,k). From induction hypotheses, we know that Sk−1 can be separated and by definition of the game the words in Sk−1 have at least the length k, otherwise the game has terminated. Assume w. l. g. that every αl in the separation of Sk−1 contains only words with length k, otherwise we would unwind β as many times as needed.

(9)S∞k=(Lfin∖VS(S,p,k))∪⋃l(αl∖VS(S,p,k))·βlω

(10)S∗k=(Lfin∖Lk(v))∪⋃l(αl∖VS(S,p,k))·βl∗(Φl,false)

□

We established a relation between both sets, which follows from the Def. 4.

Lemma 3 (Coupling ofS∞k and S∗k).

There exists a separation ofS∞kandS∗k, s. t. bothLfinare equal and for

∀l.αl·βlω∈S∞k⇔αl·βl∗(Φ,false),

We show the coupling between both sets are maintain after each, additionally prove a little bit more: The coupling is maintained after the choice of the challenger and the system.

(Proof by induction over k).

The lemma is immediately valid for k=0.

Let S∞k−1 and S∗k−1 are be coupled, we need to show that the coupling ensured after the round k for S∞k and S∗k. We also assume an arbitrary play p∈(I,O) s. t. p=p′·(a,b)∧|p|=k and there is no winner of the play in all rounds k′<|p|, otherwise the game would have terminated (both sets are empty and the coupling relation would immediately hold).

The coupling is stable under set difference: Stable means, that the a coupled αlβlω and αlβl∗(Φl,false) will stay coupled in all rounds.

In detail: By induction hypotheses the languages of the finite words in D1′(T∞) are coupled, hence L∞fin,k−1=L∗fin,k−1. Applying the set difference keeps equivalence:

L∞fin,k−1∖Vk,ξ=L∞fin,k=L∗fin,k=L∗fin,k−1∖Vk,ξ.

The same holds for any coupled αlβlω and αlβ∗(Φl,false) of the separation. W. l. g. we can pump up αl with βl s. t. all words w∈(αl·βl) are at least greater or equals to k.

Leaving one open case, αl(Φ,false) (we choose ϵ∈β∗). Obviously, this word is removed by subtracting with VS(S,p,k) (ψ in position k is false), but this is not valid VC(S,p,k). Here it is possible, that αlβlω⊆VC(S∞k−1,p,k), but αl(Φl,false)⊈Vc(S∗k−1,p,k). Note, βl represents the corresponding block for which Φl is built for. By definition, Φl is the disjunction of all ϕ of the first symbols in βl. Therefore, the play p violates Φl iff it violates all first ϕ in β. □

Prop.4. From coupling in Lemma 3 it follows that S∞k=∅⇔S∗k=∅. (Proof in contraposition) □

Example 2.

For a better auditability, we show the equal conformance on the special case with

(11)T∞=(ϕ,ψ,—∞)T∗=⟨(ϕ,ψ,—),(ϕ,false,1)⟩.

The row(ϕ,false,1)prevents the strict conformance of the system—the system cannot fulfillfalse, the same holds for the strong repetition inT∞. Therefore, we only need to consider weak conformance. Letp∈(I,O)∗be an arbitrary play. The system wins inT∞ifp⊭ϕ. At the same time it would win inT∗, as p is not allowed in both rows. Otherwise, the system loses inT∞(p⊧ϕandp⊭ψ) iff it also violatesT∗as none of both rows is adhered (p⊭ψ∨p⊭false).

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Received: 2018-03-05

Accepted: 2018-07-30

Published Online: 2018-10-17

Published in Print: 2018-10-25

Applicability of generalized test tables: a case study using the manufacturing system demonstrator xPPU

Abstract

Zusammenfassung

About the authors

Appendix A Definition for the new features

Definition 1 (Duration interval τ).

Definition 2 (val(τ)).

Definition 3 (GTTs as a Tree of Constraints).

Example 1.

Appendix B Semantic impact: No strict conformance

Proposition 1.

Proposition 2.

Proof.

Proposition 3.

Proof.

Appendix C Proof: Strong repetition does not extend the expressiveness

Definition 4 (Construction ofT∗).

Proposition 4 (Equal Conformance).

Lemma 1.

Lemma 2 (Structure ofSk).

Definition 5.

(Proof by induction over k).

Lemma 3 (Coupling ofS∞k and S∗k).

(Proof by induction over k).

Example 2.

References

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