Lecture Notes in Computer Science 3472

More documents

Recommendations

Info

Summary 14 Tools for Test Case Generation 433 AutoLink is an (industrial strength) test generator to generate (readable) TTCN test suites from SDL specifications. The test suite generation is guided by test purposes that can be supplied by the user, or also generated fully automatically. Unfortunately, a theoretical underpinning of the algorithms used in AutoLink was not present in the papers we studied. Fortunately, it turned out to be possible to reverse engineer the conformance relation definition for AutoLink [Gog01]. AutoLink has been used in a number of case studies. Related Papers • Tool Overview: [KGHS98, SEG00] • Related Tools: [GSDH97] • Underlying Theory: [Gog01] 14.3 Comparison Many aspects can be addressed when comparing tools. Below we name just a few, grouped by separating theoretical aspects from more practical ones. • Theoretical aspects – Are the test generation algorithms based on a sound theory? How do these theories relate to each other? – Which error-detecting power can be achieved theoretically? – What is the time/space complexity of the underlying algorithms? – Is the theory suited for compositional issues? Can models be congruently composed? – Is the theory suited for distributed issues? Is it possible to generate several distributed testers or is only a monolithic one possible? – How is data handled by the formalisms? Is the theory restricted to simple sets of actions or is there support for complex/symbolic data, e.g. infinite domains? How is this handled? – Is there a notion of time? Is it possible to guarantee time constraints during the test execution (which is necessary for real time systems)? – Can it deal with nondeterministic SUTs, or only with deterministic ones? – Can it deal with non nondeterministic specifications? • Practical aspects – Which error-detecting power can be achieved practically (case studies)? – Is it only possible to generate test suites or also to execute them on a real SUT? – How user-friendly is the tool? Is there a GUI facilitating the usage? Are graphical models used (e.g. UML)? – Which are the supported test case specifications? – How difficult is it to create a suitable input (e.g. defining test purposes)? Are many parameters needed and does the tool help in setting them?
434 Axel Belinfante, Lars Frantzen, and Christian Schallhart – Are the interfaces open or proprietary? Are widely accepted standards used? – To which operational environment is the tool restricted? – What practical experience is there (what test cases are performed) with the tool? We will focus on two comparison approaches that we found in the literature: theoretical analysis and benchmarking. In a theoretical analysis, one compares the test generation algorithms implemented in the tools, and tries to deduce conclusions from that. In benchmarking, one does a controlled experiment, in which one actually uses the tools to find errors, and tries to deduce conclusions from that. Below we discuss each of the approaches in more detail. In the discussion we will mainly focus on theoretical and practical error-detecting power. Regarding the other aspects, we have tried to give as much information as possible in the individual tool descriptions, and leave it to the interested reader to follow the references. 14.3.1 Theoretical Analysis Goga analyzes the theory underlying the tools TorX, TGV, AutoLink and PHACT [Gog01]. For PHACT, the theory underlying the Conformance Kit is analyzed; it implements a UIO test generation algorithm. Goga maps the algorithms used in the tools onto a common theory in order to compare the conformance relations that they use. To be able to do so, he also constructs the conformance relation for AutoLink. Then, by comparing their conformance relations, he can compare their error-detecting power. The rough idea is that, the finer the distinction is that the conformance relation can make, the more subtle the differences are that the tool can see, and thus, the better its error-detection power is. For the details we refer to [Gog01]. The result of this comparison is the following (here we quote/paraphrase [Gog01]). TorX and TGV have the same error-detection power. AutoLink has less detection power because it implements a less subtle relation than the first two (for certain kinds of errors TGV and TorX can detect an erroneous implementation and AutoLink can not).UIO algorithms (PHACT) have in practice less detection power than AutoLink, TGV and TorX. In theory, if the assumptions hold on which UIOv is based, it has the same detection power as the algorithms of the other three tools. These assumptions are: A) the specification FSM is connected B) the specification FSM is minimal C) the number of states of the implementation is less than or equal to the number of states of the specification. Because in practice assumption C) rarely holds, we conclude that in practice the three other algorithms are in general more powerful than UIOv algorithms.
Page 1 and 2:
Lecture Notes in Computer Science 3
Page 3 and 4:
Volume Editors Manfred Broy Martin
Page 5 and 6:
VI Preface The last part of the boo
Page 7 and 8:
VIII Contents 13 Real-Time and Hybr
Page 9 and 10:
2 Part I. Testing of Finite State M
Page 11 and 12:
1 Homing and Synchronizing Sequence
Page 13 and 14:
Page 15 and 16:
Page 17 and 18:
s2 a/1 1 Homing and Synchronizing S
Page 19 and 20:
Page 21 and 22:
1.3.2 Computing Synchronizing Seque
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
A1 A2 Bad 1 Homing and Synchronizin
Page 37 and 38:
Page 39 and 40:
Page 41 and 42:
36 Moez Krichen b/1 a/0 s1 b/1 a/1
Page 43 and 44:
38 Moez Krichen Now, even for minim
Page 45 and 46:
40 Moez Krichen the algorithms for
Page 47 and 48:
42 Moez Krichen ∀ s, s ′ ∈ S
Page 49 and 50:
44 Moez Krichen In this proposition
Page 51 and 52:
46 Moez Krichen Proposition 2.6. If
Page 53 and 54:
48 Moez Krichen Algorithm 5 Checkin
Page 55 and 56:
50 Moez Krichen (5) Edges emanating
Page 57 and 58:
52 Moez Krichen graph of this machi
Page 59 and 60:
54 Moez Krichen v12 v6 v11 1 I = {s
Page 61 and 62:
56 Moez Krichen B of π, a is a-val
Page 63 and 64:
58 Moez Krichen I = {s1, s2, s3, s4
Page 65 and 66:
60 Moez Krichen Definition 2.19. A
Page 67 and 68:
62 Moez Krichen Algorithm 7 Computi
Page 69 and 70:
64 Moez Krichen Algorithm 8 Computi
Page 71 and 72:
66 Moez Krichen The two authors als
Page 73 and 74:
3 State Verification Henrik Björkl
Page 75 and 76:
a/1 s1 s3 b/1 a/1 b/1 a/0 s2 s4 3 S
Page 77 and 78:
3 State Verification 73 Thus (s, Q)
Page 79 and 80:
3 State Verification 75 0, and x ca
Page 81 and 82:
s1 s3 a/0 b/0 a/1 s2 s4 3 State Ver
Page 83 and 84:
3.4.2 Naik’s Algorithm 3 State Ve
Page 85 and 86:
s1 s2 s3 s1 s3 s3 a/0 a/0 s1 s2 s3
Page 87 and 88:
3 State Verification 83 Since the m
Page 89 and 90:
3 State Verification 85 x = a1a2 ..
Page 91 and 92:
4 Conformance Testing Angelo Gargan
Page 93 and 94:
4 Conformance Testing 89 the test u
Page 95 and 96:
4 Conformance Testing 91 state. For
Page 97 and 98:
4 Conformance Testing 93 This check
Page 99 and 100:
s1 s1 a b s2 s2 a b s3 4 Conformanc
Page 101 and 102:
4 Conformance Testing 97 Using a Q
Page 103 and 104:
4 Conformance Testing 99 this case
Page 105 and 106:
4.4.5 Cost and Length 4 Conformance
Page 107 and 108:
t τ (t,si−1) x τti−1 ,si si
Page 109 and 110:
si 1 2 w1 t i w 2 3 a: in MS si 1 w
Page 111 and 112:
4 Conformance Testing 107 ti = δ(s
Page 113 and 114:
4 Conformance Testing 109 Example.
Page 115 and 116:
4 Conformance Testing 111 • If on
Page 117 and 118:
114 Part II. Testing of Labeled Tra
Page 119 and 120:
5 Preorder Relations ∗ Stefan D.
Page 121 and 122:
5 Preorder Relations 119 power of r
Page 123 and 124:
5 Preorder Relations 121 To summari
Page 125 and 126:
5 Preorder Relations 123 Two import
Page 127 and 128:
∧ ⊥⊤ ⊥ ⊥⊥ ⊤ ⊥⊤
Page 129 and 130:
5 Preorder Relations 127 Definition
Page 131 and 132:
5 Preorder Relations 129 For one th
Page 133 and 134:
5 Preorder Relations 131 We close t
Page 135 and 136:
s a b t 5 Preorder Relations 133 y
Page 137 and 138:
5 Preorder Relations 135 (1) p ⊑m
Page 139 and 140:
a p ′ τ b p ′′ τ τ a a b 5
Page 141 and 142:
5 Preorder Relations 139 It should
Page 143 and 144:
coin coin e c coin coin τ 5 Preord
Page 145 and 146:
5 Preorder Relations 143 for free.
Page 147 and 148:
5 Preorder Relations 145 condition
Page 149 and 150:
5 Preorder Relations 147 ⊑←→
Page 151 and 152:
5 Preorder Relations 149 The utilit
Page 153 and 154:
152 Valéry Tschaen The labels repr
Page 155 and 156:
154 Valéry Tschaen Intuitively, th
Page 157 and 158:
156 Valéry Tschaen Definition 6.2.
Page 159 and 160:
158 Valéry Tschaen By this theorem
Page 161 and 162:
160 Valéry Tschaen The test suite
Page 163 and 164:
162 Valéry Tschaen each sequence (
Page 165 and 166:
164 Valéry Tschaen and B2 are LOTO
Page 167 and 168:
166 Valéry Tschaen 6.4.2 The CO-OP
Page 169 and 170:
168 Valéry Tschaen a τ q0 τ τ q
Page 171 and 172:
170 Valéry Tschaen Concerning the
Page 173 and 174:
7 I/O-automata Based Testing Machie
Page 175 and 176:
7 I/O-automata Based Testing 175 th
Page 177 and 178:
7 I/O-automata Based Testing 177 in
Page 179 and 180:
7 I/O-automata Based Testing 179 sp
Page 181 and 182:
7 I/O-automata Based Testing 181 na
Page 183 and 184:
7 I/O-automata Based Testing 183 Un
Page 185 and 186:
7 I/O-automata Based Testing 185 We
Page 187 and 188:
7 I/O-automata Based Testing 187 fa
Page 189 and 190:
7 I/O-automata Based Testing 189 Th
Page 191 and 192:
7 I/O-automata Based Testing 191 Ac
Page 193 and 194:
7 I/O-automata Based Testing 193 vi
Page 195 and 196:
7 I/O-automata Based Testing 195 De
Page 197 and 198:
7 I/O-automata Based Testing 197 To
Page 199 and 200:
7 I/O-automata Based Testing 199 In
Page 201 and 202:
8 Test Derivation from Timed Automa
Page 203 and 204:
s0 on, true, {c} off , c =5, ∅ 8
Page 205 and 206:
8.3 Testing Event Recording Automat
Page 207 and 208:
[s1, z], z = con < 5, 8 Test Deriva
Page 209 and 210:
Ψ(S ′ )={PE ′ | E ′ ∈ 2E(S
Page 211 and 212:
{s0}, p0 p0 : tt 8 Test Derivation
Page 213 and 214:
Page 215 and 216:
s0 c = ∞ 8 Test Derivation from T
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
Page 223 and 224:
Example. The Light Switch can be de
Page 225 and 226:
��s0� ,c=0.0 s0 en, on, {c :=
Page 227 and 228:
��s0� ,c=0 s0 8 Test Derivati
Page 229 and 230:
Page 231 and 232:
Page 233 and 234:
234 Verena Wolf to probabilistic tr
Page 235 and 236:
236 Verena Wolf • A finite trace
Page 237 and 238:
238 Verena Wolf (a, 0.2) v1 sP (a,
Page 239 and 240:
240 Verena Wolf 1 2 sP a b µ λ 1
Page 241 and 242:
242 Verena Wolf (a, 1 4 ) (a, 1 4 )
Page 243 and 244:
244 Verena Wolf 9.6 Test Processes
Page 245 and 246:
246 Verena Wolf We present two appr
Page 247 and 248:
248 Verena Wolf specification proce
Page 249 and 250:
250 Verena Wolf sP (τ, 1 1 ) (c, 3
Page 251 and 252:
252 Verena Wolf sP (a, 1 1 ) (a, 2
Page 253 and 254:
254 Verena Wolf v1 u1 w1 1 2 sP λ
Page 255 and 256:
256 Verena Wolf • P ⊑ must JY Q
Page 257 and 258:
258 Verena Wolf u1 s M ′ 1 (a, r1
Page 259 and 260:
260 Verena Wolf Proposition 9.22. L
Page 261 and 262:
262 Verena Wolf Now let Q min be th
Page 263 and 264:
264 Verena Wolf (8) (⊑BC , ⊑CH
Page 265 and 266:
266 Verena Wolf is that an action a
Page 267 and 268:
268 Verena Wolf can perform τ-tran
Page 269 and 270:
270 Verena Wolf T np,re seq ⊑ tr
Page 271 and 272:
272 Verena Wolf t2 t4 a sT t1 b b t
Page 273 and 274:
274 Verena Wolf model test processe
Page 275 and 276:
Part III Model-Based Test Case Gene
Page 277 and 278:
Part III. Model-Based Test Case Gen
Page 279 and 280:
282 Alexander Pretschner and Jan Ph
Page 281 and 282:
Page 283 and 284:
Page 285 and 286:
Page 287 and 288:
Page 289 and 290:
11 Evaluating Coverage Based Testin
Page 291 and 292:
Page 293 and 294:
Page 295 and 296:
Page 297 and 298:
Page 299 and 300:
Page 301 and 302:
Page 303 and 304:
Page 305 and 306:
Page 307 and 308:
Page 309 and 310:
Page 311 and 312:
Page 313 and 314:
Page 315 and 316:
Page 317 and 318:
Page 319 and 320:
12 Technology of Test-Case Generati
Page 321 and 322:
Page 323 and 324:
Page 325 and 326:
Increment ∆Counter 12 Technology
Page 327 and 328:
Page 329 and 330:
Page 331 and 332:
(12.4) ✟ nat(X ′ ) {A/0, B/X
Page 333 and 334:
Page 335 and 336:
Page 337 and 338:
a: b: (6) α1+1−α2 α2 a: b: PC:
Page 339 and 340:
Page 341 and 342:
Page 343 and 344:
Page 345 and 346:
Page 347 and 348:
Page 349 and 350:
12.5 Summary 12 Technology of Test-
Page 351 and 352:
13 Real-Time and Hybrid Systems Tes
Page 353 and 354:
Test Driver SUT 13 Real-Time and Hy
Page 355 and 356:
Page 357 and 358:
Page 359 and 360:
Page 361 and 362:
Page 363 and 364:
Page 365 and 366:
Page 367 and 368:
Page 369 and 370:
Page 371 and 372:
Page 373 and 374:
Page 375 and 376:
Page 377 and 378: 13 Real-Time and Hybrid Systems Tes
Page 379 and 380: fitness 13 Real-Time and Hybrid Sys
Page 381 and 382: 13.5 Summary 13 Real-Time and Hybri
Page 383 and 384: 13 Real-Time and Hybrid Systems Tes
Page 385 and 386: 390 Part IV. Tools and Case Studies
Page 387 and 388: 392 Axel Belinfante, Lars Frantzen,
Page 427: 432 Axel Belinfante, Lars Frantzen,
Page 435 and 436: 440 Wolfgang Prenninger, Mohammad E
Page 457 and 458: Part V Standardized Test Notation a
Page 459 and 460: 466 George Din inter-operability te
Page 461 and 462: 468 George Din • Tabular Presenta
Page 463 and 464: 470 George Din 16.3.1 Test Building
Page 465 and 466: 472 George Din Abstract Test System
Page 467 and 468: 474 George Din field can be marked
Page 469 and 470: 476 George Din • omit: the value
Page 471 and 472: 478 George Din altstep Default() ru
Page 473 and 474: 480 George Din alt { [] httpPort.re
Page 475 and 476: 482 George Din • Test Management
Page 477 and 478: 484 George Din Value Type getType()
Page 479 and 480:
486 George Din This task is rather
Page 481 and 482:
488 George Din hosts, of preparing
Page 483 and 484:
490 George Din A B C D MEM = 256 MB
Page 485 and 486:
492 George Din A hardware load moni
Page 487 and 488:
494 George Din ptcType2 ptcType3
Page 489 and 490:
496 George Din communicate with the
Page 491 and 492:
498 Zhen Ru Dai U2TP document is no
Page 493 and 494:
500 Zhen Ru Dai state machines, sta
Page 495 and 496:
502 Zhen Ru Dai TestResult TestCase
Page 497 and 498:
504 Zhen Ru Dai can be mapped to JU
Page 499 and 500:
506 Zhen Ru Dai 17.4 Test Developme
Page 501 and 502:
508 Zhen Ru Dai Slave: Master: SRI
Page 503 and 504:
510 Zhen Ru Dai sa: Slave− Appli
Page 505 and 506:
512 Zhen Ru Dai sdConnect_To_Master
Page 507 and 508:
514 Zhen Ru Dai BluetoothUnitTest
Page 509 and 510:
516 Zhen Ru Dai is returned to the
Page 511 and 512:
518 Zhen Ru Dai (1) /* test configu
Page 513 and 514:
520 Zhen Ru Dai (1) /* test case */
Page 515 and 516:
Part VI Beyond Testing This last pa
Page 517 and 518:
526 Séverine Colin and Leonardo Ma
Page 519 and 520:
Page 521 and 522:
Page 523 and 524:
Page 525 and 526:
Page 527 and 528:
Page 529 and 530:
Page 531 and 532:
Page 533 and 534:
Page 535 and 536:
Page 537 and 538:
Page 539 and 540:
Page 541 and 542:
Page 543 and 544:
Page 545 and 546:
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
Page 557 and 558:
19 Model Checking 567 Another appro
Page 559 and 560:
19 Model Checking 569 has a transit
Page 561 and 562:
19 Model Checking 571 The alternati
Page 563 and 564:
19 Model Checking 573 Obviously the
Page 565 and 566:
19 Model Checking 575 purposes ther
Page 567 and 568:
19 Model Checking 577 otherwise it
Page 569 and 570:
19 Model Checking 579 Expanding a P
Page 571 and 572:
19 Model Checking 581 We conduct an
Page 573 and 574:
• SA ⊆ Σ ∗ is a nonempty fin
Page 575 and 576:
19 Model Checking 585 When OT is cl
Page 577 and 578:
19 Model Checking 587 • se = s
Page 579 and 580:
19 Model Checking 589 the new colum
Page 581 and 582:
19 Model Checking 591 Henceforth th
Page 583 and 584:
19 Model Checking 593 DT , the tran
Page 585 and 586:
19 Model Checking 595 queries. At t
Page 587 and 588:
19 Model Checking 597 Assistant 4.
Page 589 and 590:
19 Model Checking 599 have created
Page 591 and 592:
19 Model Checking 601 Logic (see Se
Page 593 and 594:
19 Model Checking 603 linear time l
Page 595 and 596:
20 Model-Based Testing - A Glossary
Page 597 and 598:
20 Model-Based Testing - A Glossary
Page 599 and 600:
612 Bengt Jonsson a/0 b/0 b/1 s2 s4
Page 601 and 602:
614 Bengt Jonsson of input symbols
Page 603 and 604:
616 Joost-Pieter Katoen The followi
Page 605 and 606:
618 Literature [AFH94] Rajeev Alur,
Page 607 and 608:
620 Literature [BCMD90] J. R. Burch
Page 609 and 610:
622 Literature [BRV95] Ed Brinksma,
Page 611 and 612:
624 Literature [CL97a] Duncan Clark
Page 613 and 614:
626 Literature [DGNP04] Z. R. Dai,
Page 615 and 616:
628 Literature [FHP02] Eitan Farchi
Page 617 and 618:
630 Literature [GL02] Hubert Garave
Page 619 and 620:
632 Literature [Hib61] Thomas N. Hi
Page 621 and 622:
634 Literature [HR01b] Klaus Havelu
Page 623 and 624:
636 Literature [KKL + 01] M. Kim, S
Page 625 and 626:
638 Literature [LPY97] Kim Guldstra
Page 627 and 628:
640 Literature [Müh97] H. Mühlenb
Page 629 and 630:
642 Literature [Pha93] M. Phalippou
Page 631 and 632:
644 Literature [RdBJ00] V. Rusu, L.
Page 633 and 634:
646 Literature [Sch00] Johann M. Sc
Page 635 and 636:
648 Literature [SVG02] S. Schulz an
Page 637 and 638:
650 Literature [Vas73] M. P. Vasile
Page 639 and 640:
Index =⇒ , 175 ioco, 187 ioconf,
Page 641 and 642:
homing sequence, 8 - adaptive, 8, 2
Page 643 and 644:
eset sequence, see synchronizing se
Page 645:
timed transition system, 223, 360,
show all

Lecture Notes in Computer Science 3472

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?