Lecture Notes in Computer Science 3472

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110 Angelo Gargantini of any kind, while the UIO method may miss some faults. The W, Wp, and DS method with an adaptive distinguishing sequence produce checking sequences of length O(pn 3 )withcostO(pn 3 ). The others have greater cost. • If even a reset message is not available, but a machine has a distinguishing sequence, the method presented in Section 4.5 uses transfer sequences instead of reset, produces checking sequences of length O(pn 3 ) and has cost O(pn 3 ) when used in conjunction with adaptive distinguishing sequences. • If the machine has not even a distinguishing sequence nor UIOs, the identifying sequences (IS) method, presented in Section 4.6, still works. The IS method uses only the assumptions that the implementation does not add states and that the machines are minimized and therefore they have separating sequences. It produces exponentially long checking sequences. • The problem of testing finite state machines with extra states is discussed more in general in Section 4.7, where the method originally presented by Chow [Cho78] is introduced. It is of practical interest to compare the fault detection capability of the methods when the assumptions under which they should be applied, do not hold [SL88, ZC93]. Indeed, assumptions like the equal number of states for implementation may be not verifiable in practice. The assumption of the existence of a reset message is more meaningful, but empirical studies suggest to avoid the use of the methods using reset messages for the following reason. As shown in Section 4.7, faults in extra states are more likely to be discovered when using long input sequences. The use of a reset message may prevent the implementation to reach such extra states where the faults are present. For this reason methods like UIO or DS method without reset are better in practice than the UIOv method or the DS method with reset. Although the study presented in this chapter is rather theoretical, we can draw some useful guidelines for practice testing for FSMs or for parts of models that behave like finite state machine and the reader should be aware that many ideas presented in this chapter are the basics for tools and case studies presented in Chapters 14 and 15. Such practical suggestions can improve the fault detection capability of the testing activity. • Visiting each state in a FSM (like a statement coverage) using a ST method, should not be considered enough. One should at least visit every transition using a transition tour (TT) method, that can be considered as a branch coverage. • Transition coverage should be used in conjunction of a status message to really check that the end state of every transition is the one expected. The presence of a status message in digital circuits is often required by the tester because it is of great help to uncover faults. If a status message may be not reliable, a double application of it helps to discover when it fails to reveal the correct state. • If a status message is not available (very often in software black box testing), one should use some extra inputs to verify the states. Such inputs should be unique, like in Wp, UIO and DS.
4 Conformance Testing 111 • If one suspects that the implementation has more states than the implementation, he/she should prefer methods that produce long input sequences, like the DS and the IS method. However, only methods like the W method with extra states [Cho78], that add some extra inputs after visiting the transition and before checking the state identity, can guarantee to detect faults in this case.
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Lecture Notes in Computer Science 3
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Volume Editors Manfred Broy Martin
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VI Preface The last part of the boo
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VIII Contents 13 Real-Time and Hybr
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2 Part I. Testing of Finite State M
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1 Homing and Synchronizing Sequence
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s2 a/1 1 Homing and Synchronizing S
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1.3.2 Computing Synchronizing Seque
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A1 A2 Bad 1 Homing and Synchronizin
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36 Moez Krichen b/1 a/0 s1 b/1 a/1
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38 Moez Krichen Now, even for minim
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40 Moez Krichen the algorithms for
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42 Moez Krichen ∀ s, s ′ ∈ S
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44 Moez Krichen In this proposition
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46 Moez Krichen Proposition 2.6. If
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48 Moez Krichen Algorithm 5 Checkin
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50 Moez Krichen (5) Edges emanating
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52 Moez Krichen graph of this machi
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54 Moez Krichen v12 v6 v11 1 I = {s
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56 Moez Krichen B of π, a is a-val
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Page 91 and 92: 4 Conformance Testing Angelo Gargan
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Page 129 and 130: 5 Preorder Relations 127 Definition
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164 Valéry Tschaen and B2 are LOTO
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166 Valéry Tschaen 6.4.2 The CO-OP
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168 Valéry Tschaen a τ q0 τ τ q
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170 Valéry Tschaen Concerning the
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7 I/O-automata Based Testing Machie
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7 I/O-automata Based Testing 175 th
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7 I/O-automata Based Testing 177 in
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7 I/O-automata Based Testing 179 sp
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7 I/O-automata Based Testing 181 na
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7 I/O-automata Based Testing 183 Un
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7 I/O-automata Based Testing 185 We
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7 I/O-automata Based Testing 187 fa
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7 I/O-automata Based Testing 189 Th
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7 I/O-automata Based Testing 191 Ac
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7 I/O-automata Based Testing 193 vi
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7 I/O-automata Based Testing 195 De
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7 I/O-automata Based Testing 197 To
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7 I/O-automata Based Testing 199 In
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8 Test Derivation from Timed Automa
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s0 on, true, {c} off , c =5, ∅ 8
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8.3 Testing Event Recording Automat
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[s1, z], z = con < 5, 8 Test Deriva
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Ψ(S ′ )={PE ′ | E ′ ∈ 2E(S
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{s0}, p0 p0 : tt 8 Test Derivation
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s0 c = ∞ 8 Test Derivation from T
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Example. The Light Switch can be de
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��s0� ,c=0.0 s0 en, on, {c :=
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��s0� ,c=0 s0 8 Test Derivati
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234 Verena Wolf to probabilistic tr
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236 Verena Wolf • A finite trace
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238 Verena Wolf (a, 0.2) v1 sP (a,
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240 Verena Wolf 1 2 sP a b µ λ 1
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242 Verena Wolf (a, 1 4 ) (a, 1 4 )
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244 Verena Wolf 9.6 Test Processes
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246 Verena Wolf We present two appr
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248 Verena Wolf specification proce
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250 Verena Wolf sP (τ, 1 1 ) (c, 3
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252 Verena Wolf sP (a, 1 1 ) (a, 2
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254 Verena Wolf v1 u1 w1 1 2 sP λ
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256 Verena Wolf • P ⊑ must JY Q
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258 Verena Wolf u1 s M ′ 1 (a, r1
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260 Verena Wolf Proposition 9.22. L
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262 Verena Wolf Now let Q min be th
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264 Verena Wolf (8) (⊑BC , ⊑CH
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266 Verena Wolf is that an action a
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268 Verena Wolf can perform τ-tran
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270 Verena Wolf T np,re seq ⊑ tr
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272 Verena Wolf t2 t4 a sT t1 b b t
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274 Verena Wolf model test processe
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Part III Model-Based Test Case Gene
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Part III. Model-Based Test Case Gen
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282 Alexander Pretschner and Jan Ph
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11 Evaluating Coverage Based Testin
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12 Technology of Test-Case Generati
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Increment ∆Counter 12 Technology
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(12.4) ✟ nat(X ′ ) {A/0, B/X
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a: b: (6) α1+1−α2 α2 a: b: PC:
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12.5 Summary 12 Technology of Test-
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13 Real-Time and Hybrid Systems Tes
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Test Driver SUT 13 Real-Time and Hy
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fitness 13 Real-Time and Hybrid Sys
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13.5 Summary 13 Real-Time and Hybri
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390 Part IV. Tools and Case Studies
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392 Axel Belinfante, Lars Frantzen,
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440 Wolfgang Prenninger, Mohammad E
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Part V Standardized Test Notation a
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466 George Din inter-operability te
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468 George Din • Tabular Presenta
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470 George Din 16.3.1 Test Building
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472 George Din Abstract Test System
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474 George Din field can be marked
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476 George Din • omit: the value
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478 George Din altstep Default() ru
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480 George Din alt { [] httpPort.re
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482 George Din • Test Management
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484 George Din Value Type getType()
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486 George Din This task is rather
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488 George Din hosts, of preparing
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490 George Din A B C D MEM = 256 MB
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492 George Din A hardware load moni
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494 George Din ptcType2 ptcType3
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496 George Din communicate with the
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498 Zhen Ru Dai U2TP document is no
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500 Zhen Ru Dai state machines, sta
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502 Zhen Ru Dai TestResult TestCase
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504 Zhen Ru Dai can be mapped to JU
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506 Zhen Ru Dai 17.4 Test Developme
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508 Zhen Ru Dai Slave: Master: SRI
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510 Zhen Ru Dai sa: Slave− Appli
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512 Zhen Ru Dai sdConnect_To_Master
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514 Zhen Ru Dai BluetoothUnitTest
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516 Zhen Ru Dai is returned to the
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518 Zhen Ru Dai (1) /* test configu
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520 Zhen Ru Dai (1) /* test case */
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Part VI Beyond Testing This last pa
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526 Séverine Colin and Leonardo Ma
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19 Model Checking Therese Berg 1 an
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19 Model Checking 559 The first sta
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19 Model Checking 561 function I :
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coffee coin tea 19 Model Checking 5
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AX (φ) :=¬EX (¬φ) AF (φ) :=Atr
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19 Model Checking 567 Another appro
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19 Model Checking 569 has a transit
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19 Model Checking 571 The alternati
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19 Model Checking 573 Obviously the
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19 Model Checking 575 purposes ther
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19 Model Checking 577 otherwise it
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19 Model Checking 579 Expanding a P
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19 Model Checking 581 We conduct an
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• SA ⊆ Σ ∗ is a nonempty fin
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19 Model Checking 585 When OT is cl
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19 Model Checking 587 • se = s
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19 Model Checking 589 the new colum
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19 Model Checking 591 Henceforth th
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19 Model Checking 593 DT , the tran
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19 Model Checking 595 queries. At t
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19 Model Checking 597 Assistant 4.
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19 Model Checking 599 have created
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19 Model Checking 601 Logic (see Se
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19 Model Checking 603 linear time l
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20 Model-Based Testing - A Glossary
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20 Model-Based Testing - A Glossary
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612 Bengt Jonsson a/0 b/0 b/1 s2 s4
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614 Bengt Jonsson of input symbols
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616 Joost-Pieter Katoen The followi
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618 Literature [AFH94] Rajeev Alur,
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620 Literature [BCMD90] J. R. Burch
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622 Literature [BRV95] Ed Brinksma,
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624 Literature [CL97a] Duncan Clark
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626 Literature [DGNP04] Z. R. Dai,
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628 Literature [FHP02] Eitan Farchi
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630 Literature [GL02] Hubert Garave
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632 Literature [Hib61] Thomas N. Hi
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634 Literature [HR01b] Klaus Havelu
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636 Literature [KKL + 01] M. Kim, S
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638 Literature [LPY97] Kim Guldstra
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640 Literature [Müh97] H. Mühlenb
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642 Literature [Pha93] M. Phalippou
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644 Literature [RdBJ00] V. Rusu, L.
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646 Literature [Sch00] Johann M. Sc
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648 Literature [SVG02] S. Schulz an
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650 Literature [Vas73] M. P. Vasile
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Index =⇒ , 175 ioco, 187 ioconf,
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homing sequence, 8 - adaptive, 8, 2
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eset sequence, see synchronizing se
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timed transition system, 223, 360,
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