Lecture Notes in Computer Science 3472

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State state ←{}; bool pre[0 ...6]; bool now[0 ...6]; Input: tracet = e1e2 ...en; /* Initialization of state and pre */ state ← update(state, e1); pre[6] ← is flashing(state); pre[5] ← false pre[4] ← is closing(state) pre[3] ← pre[4] and not pre[5] pre[2] ← is opening(state) pre[1] ← false pre[0] ← not pre[1] or pre[3]; /* Event interpretation loop */ for i =2to n do { state ← update(state, ei) now[6] ← is flashing(state); now[5] ← not now[6] and pre[6] now[4] ← is closing(state) now[3] ← (pre[3] or now[4]) and not now[5] now[2] ← is opening(state) now[1] ← now[2] and not pre[2] now[0] ← not now[1] or now[3]; if now[0] = false then output(“property violated”); pre ← now; }; 18 Run-Time Verification 541 Fig. 18.7. The algorithm generated by PathExplorer for the formula ↑ is opening ⇒ [is closing, ↓ is flashing)S the state are false at initialization. In the example, both formulas ↑ is opening and ↓ is flashing, that correspond to indexes 5 and 1, are false. The loop sequentially considers all events, and for each event the current state is first updated, then the now array is computed (meaning that the formula is evaluated), and finally the now array is copied into the pre array (since at next step the current array will be the previous array). If at any step now[0] is false, the formula has been violated. Note that for the way enumeration has been performed now[0] represents the truth value of the whole formula. Figure 18.8 shows the evaluation progress for the formula ↑ is opening ⇒ [is closing, ↓ is flashing)S on the trace flashing, closing, closed, opening, open, off. The content of the pre array at the end of the loop is reported below each abstract state with the exception of the array of boolean values reported on the first abstract state that denotes the content of pre after initialization. We can immediately observe that the trace satisfies the formula ↑ is opening ⇒ [is closing, ↓ is flashing)S because pre[0] is true at all steps. Exercise 18.3 (Algorithm Application). Verify that the execution trace open, off,
542 Séverine Colin and Leonardo Mariani gate=open light=off flashing gate=open light=flashing closing gate=closing light=flashing [1000000] [1000001] [1001101] gate=open light=off [1000010] off gate=open light=flashing [1001001] open gate=opening light=flashing [1111001] closed gate=closed light=flashing [1001001] opening Fig. 18.8. Progress of the algorithm in Figure 18.7 for the trace flashing, closing, closed, opening, open, off. The content of the pre array is reported below each abstract state. Note that 0 is used for false and 1 for true. flashing, closing, closed, off, opening, open violates the formula ↑ is opening ⇒ [is closing, ↓ is flashing)S by simulating the execution of the program shown in Figure 18.7. Analyzing a fixed past time LTL formula by the PathExplorer dynamically generated algorithm is straightforward, its time complexity is Θ(n)wheren is the length of the input trace, and the required memory is constant since the length of the two arrays is equal to the size of the past time LTL formula. However, if you include the size m of the formula in the analysis, the time complexity is Θ(n · m), while the required memory is 2 · (m + 1) bits. The procedure for enumerating a given formula is linear, thus the algorithm which synthesizes a dynamic programming algorithm from a past LTL formula is linear with the size of the formula. PathExplorer Architecture PathExplorer can be regarded as consisting of three main modules: an instrumentation module, an observer module, and an interaction module. The instrumentation module performs a script-driven automated instrumentation of the program that must be observed by using the Jtrek Java byte-code engineering tool [Coh]. The instrumented program emits events to the interaction module, which forwards them further to the observation module. If the observer runs on a different computer, events are transmitted over sockets. 18.5.3 Monitoring and Checking (MaC) Method The Monitoring and Checking (MaC) method [LKK + 99, KKL + 01] that has been developed at the University of Pennsylvania ensures that a system is behaving
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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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58 Moez Krichen I = {s1, s2, s3, s4
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60 Moez Krichen Definition 2.19. A
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62 Moez Krichen Algorithm 7 Computi
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64 Moez Krichen Algorithm 8 Computi
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66 Moez Krichen The two authors als
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3 State Verification Henrik Björkl
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a/1 s1 s3 b/1 a/1 b/1 a/0 s2 s4 3 S
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3 State Verification 73 Thus (s, Q)
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3 State Verification 75 0, and x ca
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s1 s3 a/0 b/0 a/1 s2 s4 3 State Ver
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3.4.2 Naik’s Algorithm 3 State Ve
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s1 s2 s3 s1 s3 s3 a/0 a/0 s1 s2 s3
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3 State Verification 83 Since the m
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3 State Verification 85 x = a1a2 ..
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4 Conformance Testing Angelo Gargan
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4 Conformance Testing 89 the test u
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4 Conformance Testing 91 state. For
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4 Conformance Testing 93 This check
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s1 s1 a b s2 s2 a b s3 4 Conformanc
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4 Conformance Testing 97 Using a Q
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4 Conformance Testing 99 this case
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4.4.5 Cost and Length 4 Conformance
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t τ (t,si−1) x τti−1 ,si si
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si 1 2 w1 t i w 2 3 a: in MS si 1 w
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4 Conformance Testing 107 ti = δ(s
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4 Conformance Testing 109 Example.
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4 Conformance Testing 111 • If on
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114 Part II. Testing of Labeled Tra
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5 Preorder Relations ∗ Stefan D.
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5 Preorder Relations 119 power of r
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5 Preorder Relations 121 To summari
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5 Preorder Relations 123 Two import
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∧ ⊥⊤ ⊥ ⊥⊥ ⊤ ⊥⊤
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5 Preorder Relations 127 Definition
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5 Preorder Relations 129 For one th
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5 Preorder Relations 131 We close t
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s a b t 5 Preorder Relations 133 y
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5 Preorder Relations 135 (1) p ⊑m
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a p ′ τ b p ′′ τ τ a a b 5
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5 Preorder Relations 139 It should
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coin coin e c coin coin τ 5 Preord
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5 Preorder Relations 143 for free.
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5 Preorder Relations 145 condition
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5 Preorder Relations 147 ⊑←→
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5 Preorder Relations 149 The utilit
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152 Valéry Tschaen The labels repr
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154 Valéry Tschaen Intuitively, th
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156 Valéry Tschaen Definition 6.2.
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158 Valéry Tschaen By this theorem
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160 Valéry Tschaen The test suite
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162 Valéry Tschaen each sequence (
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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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Page 499 and 500: 506 Zhen Ru Dai 17.4 Test Developme
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Page 515 and 516: Part VI Beyond Testing This last pa
Page 517 and 518: 526 Séverine Colin and Leonardo Ma
Page 531: 540 Séverine Colin and Leonardo Ma
Page 547 and 548: 19 Model Checking Therese Berg 1 an
Page 549 and 550: 19 Model Checking 559 The first sta
Page 551 and 552: 19 Model Checking 561 function I :
Page 553 and 554: coffee coin tea 19 Model Checking 5
Page 555 and 556: AX (φ) :=¬EX (¬φ) AF (φ) :=Atr
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Page 569 and 570: 19 Model Checking 579 Expanding a P
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Page 577 and 578: 19 Model Checking 587 • se = s
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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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