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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王凡 | |
| dc.contributor.author | Che-Jung Wu | en |
| dc.contributor.author | 吳哲榮 | zh_TW |
| dc.date.accessioned | 2021-06-08T06:13:33Z | - |
| dc.date.copyright | 2011-08-10 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-04 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25441 | - |
| dc.description.abstract | 軟體規模愈趨龐大的現在，軟體測試的工作已變得越來越複雜且龐大；而模型驗證也無法完全滿足軟體自動驗證的需求。目前已有使用小量的人工智慧技術在上述的兩種技術之中，但亦無法滿足軟體驗證中各式各樣的挑戰。
在本篇論文中提出了一個模型測試的架構包含了集成測試與模型驗證和自動推演的演算法兩部分。這個架構以一個有限自動機來代表軟體，以及一組測試用例和使用者可自訂的優先排序準則，使用者可透過修改優先排序準則來實現各種人工智慧。 這個架構的核心是以一個模擬器來模擬程式，並具有在程式的各個步驟依要求前進或後退的功能，我們會展示在此架構中如何透過優先排序準則來達成錯誤回報的回歸化測試。回歸化測試的關鍵在於利用優先排序準則來選定測試用例，而優先排序準則可依據測試用例的相似度與上一次執行的測試用例所走路徑來選擇下一個測試用例，並能依照執行的結果一邊自我調整其準則。我們還會展示使用LCS(Longest Common Sequence)的技術來比對測試用例之間各種細部變數的相似程度。最後的實驗結果也證明了此種技術的成果。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-08T06:13:33Z (GMT). No. of bitstreams: 1 ntu-100-R98921074-1.pdf: 1169003 bytes, checksum: 56d7880253848a9cc5d510b51122a374 (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 誌謝
.......................................... i 中文摘要 ....................................... ii Abstract ........................................ iii 1 Introduction .................................... 1 1.1 Background................................. 1 1.2 Motivation.................................. 2 1.3 Softwaretesting ............................... 3 1.4 Model checking ............................... 3 1.5 Our simulator ................................ 4 1.6 Ourframeworkofsoftwaremodeltesting ................. 5 1.7 RegressionTesting ............................. 6 1.8 ThesisFramework.............................. 7 2 RelatedWork ................................... 9 3 Modeling language,EFSM ............................ 10 4Path generator(PATHG) ............................. 13 5 Modeltestingwitha fitness function ....................... 16 5.1 Componemtoftest case ........................... 16 5.2 Capabilityof backtrack ........................... 17 5.3 Fitness function ............................... 17 5.4 Ourworkflow................................ 18 6 Adaptiveregressionmodeltesting ........................ 21 6.1 Longest common subsequences(LCS) ................... 22 6.2 Designofthe fitness function ........................ 22 6.2.1 Similarity Estimation ........................ 23 6.2.2Testexecutionsharing ....................... 26 6.2.3 FitnessFormulation ........................ 27 6.3 Supervised learningofthe weighting ................... 28 7 Implementationandexperiment ......................... 30 7.1 OurSUT................................... 31 7.2 Performance Analysis ............................ 32 8 Conclusionsand futurework ........................... 37 Reference ....................................... 38 | |
| dc.language.iso | en | |
| dc.subject | 軟體測試 | zh_TW |
| dc.subject | aritificial intelligence | en |
| dc.subject | bug-fix | en |
| dc.subject | test plan | en |
| dc.subject | regression testing | en |
| dc.subject | software testing | en |
| dc.subject | model testing | en |
| dc.title | 使用LCS計數的錯誤更正回歸測試 | zh_TW |
| dc.title | Using LCS techniques for the regression testing of bug-fixes | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 戴顯權,劉志文,陳郁方,陳銘憲,顏嘉志 | |
| dc.subject.keyword | 軟體測試, | zh_TW |
| dc.subject.keyword | bug-fix,test plan,regression testing,model testing,software testing,aritificial intelligence, | en |
| dc.relation.page | 42 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2011-08-04 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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