000 03005cam a2200385 i 4500
001 1374251026
003 OCoLC
005 20250314134541.0
006 m o d
007 cr cnu---unuuu
008 230330s2023 sz a ob 000 0 eng d
020 _a9783031220562
024 7 _a10.1007/978-3-031-22057-9
_2doi
035 _a(OCoLC)1374251026
_z(OCoLC)1374189623
040 _aGW5XE
_beng
_erda
_epn
_cGW5XE
_dYDX
_dEBLCP
050 4 _aQA76.76.T48
072 7 _aUN
_2bicssc
072 7 _aCOM018000
_2bisacsh
072 7 _aUN
_2thema
082 0 4 _a005.1/4 PAR 2023
_223/eng/20230330
100 1 _aParsa, Saeed,
_eauthor
245 1 0 _aSoftware testing automation :
_btestability evaluation, refactoring, test data generation and fault localization /
_cSaeed Parsa
264 1 _aCham :
_bSpringer,
_c[2023]
264 4 _c©2023
300 _axxiv, 580 pages :
_billustrations (chiefly color) ;
_c24 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _acolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references
505 0 _aSoftware Testability -- Unit testing and Test-Driven Development -- Acceptance Testing and Behavior Driven Development
506 _aAvailable to OhioLINK libraries
520 _aThis book is about the design and development of tools for software testing. It intends to get the reader involved in software testing rather than simply memorizing the concepts. The source codes are downloadable from the book website. The book has three parts: software testability, fault localization, and test data generation. Part I describes unit and acceptance tests and proposes a new method called testability-driven development (TsDD) in support of TDD and BDD. TsDD uses a machine learning model to measure testability before and after refactoring. The reader will learn how to develop the testability prediction model and write software tools for automatic refactoring. Part II focuses on developing tools for automatic fault localization. This part shows the reader how to use a compiler generator to instrument source code, create control flow graphs, identify prime paths, and slice the source code. On top of these tools, a software tool, Diagnoser, is offered to facilitate experimenting with and developing new fault localization algorithms. Diagnoser takes a source code and its test suite as input and reports the coverage provided by the test cases and the suspiciousness score for each statement. Part III proposes using software testing as a prominent part of the cyber-physical system software to uncover and model unknown physical behaviors and the underlying physical rules. The reader will get insights into developing software tools to generate white box test data.
650 0 _aComputer software
_0https://id.loc.gov/authorities/subjects/sh85029534
_xTesting
_0https://id.loc.gov/authorities/subjects/sh99005648
_xAutomation.
_0https://id.loc.gov/authorities/subjects/sh00007652
942 _2ddc
_c2
999 _c60370
_d60370