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An Automated Error Localization System for Introductory Programming Assignments : 입문자용 프로그래밍 과제의 오류 위치 자동 탐지 시스템 개발
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 이광근 | - |
dc.contributor.author | Duekeun Kim | - |
dc.date.accessioned | 2018-12-03T01:33:32Z | - |
dc.date.available | 2018-12-03T01:33:32Z | - |
dc.date.issued | 2018-08 | - |
dc.identifier.other | 000000152944 | - |
dc.identifier.uri | https://hdl.handle.net/10371/143626 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 공과대학 컴퓨터공학부, 2018. 8. 이광근. | - |
dc.description.abstract | The demand of software education is increasing world wide. However, there
is a lack of teachers and infrastructure corresponding for the demand. There- fore, we present HONEYBEE in this paper, a new error localization algorithm using the maximum satisability (MAX-SAT). It automatically detects the fault locations of the program submitted by students in introductory programming courses. The method is as follows: First, it constructs a logical expression, a trace formula, representing the execution ow for a student program. Second, the trace formula is then extended by attaching the correct input and output pair and supplemental constraints from the answer program. Third, it uses a maximum satisability solver to nd the minimum error point which is a po- tential fault. We evaluate HONEYBEE in two domains. First, HONEYBEE found 87% of the exact error locations of articial programs. Second, it also detected 80% of the fault of real submitted codes. It shows our system works well in actual situation. Moreover, it suggests the method using answer programs and multiple counter examples to improve performance. | - |
dc.description.tableofcontents | Chapter 1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Automated Error Localization Tool . . . . . . . . . . . . . . . . . 2 1.4 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 2 Preliminary 4 2.1 Program and Trace . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Maximum Satisability . . . . . . . . . . . . . . . . . . . . . . . 5 Chapter 3 Algorithm 7 3.1 Generating an Extended Trace Formula . . . . . . . . . . . . . . 8 3.1.1 Trace Formula . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.2 Selectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.1.3 Input/Output Constraint . . . . . . . . . . . . . . . . . . 9 3.2 Localization Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 10 3.3 Consulting with Solutions . . . . . . . . . . . . . . . . . . . . . . 11 3.3.1 Variable Supplemental Constraint . . . . . . . . . . . . . 11 3.3.2 Condition Supplemental Constraint . . . . . . . . . . . . 11 3.3.3 Eect of Consulting with Solutions . . . . . . . . . . . . . 12 3.4 Using Multiple Counterexamples . . . . . . . . . . . . . . . . . . 12 Chapter 4 Experimental Result 14 4.1 Articial Faulty Programs . . . . . . . . . . . . . . . . . . . . . . 15 4.2 Real Faulty Programs . . . . . . . . . . . . . . . . . . . . . . . . 16 Chapter 5 Related Works 18 5.1 Error Localization . . . . . . . . . . . . . . . . . . . . . . . . . . 18 5.2 Feedback Generation . . . . . . . . . . . . . . . . . . . . . . . . . 19 Chapter 6 Conclusion 21 Bibliography 23 초록 26 | - |
dc.format | application/pdf | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject.ddc | 621.39 | - |
dc.title | An Automated Error Localization System for Introductory Programming Assignments | - |
dc.title.alternative | 입문자용 프로그래밍 과제의 오류 위치 자동 탐지 시스템 개발 | - |
dc.type | Thesis | - |
dc.description.degree | Master | - |
dc.contributor.affiliation | 공과대학 컴퓨터공학부 | - |
dc.date.awarded | 2018-08 | - |
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