Build a fact extractor for Python programs
Software programs’ sizes are increasing since more features are built to meet the growing demands. Each version of a program must advance and address the flaws in previous versions over a short period. As the software programs evolve, program facts can be drawn from software artifacts to understand...
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Nanyang Technological University
2022
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sg-ntu-dr.10356-1564602022-04-17T09:19:14Z Build a fact extractor for Python programs Truong, Quang Duc Li Yi School of Computer Science and Engineering yi_li@ntu.edu.sg Engineering::Computer science and engineering Software programs’ sizes are increasing since more features are built to meet the growing demands. Each version of a program must advance and address the flaws in previous versions over a short period. As the software programs evolve, program facts can be drawn from software artifacts to understand the dependencies among different pieces of code in a program and provide interesting insights about the version changes. These facts can, therefore, also be used for quality assurance. Although fact extractors have been discussed for other various languages, there has been little done for Python. This report seeks to explore how facts can be extracted and stored in a “fact base” for Python programs by showing the approaches to writing fact extractors. Bachelor of Engineering (Computer Science) 2022-04-17T09:19:14Z 2022-04-17T09:19:14Z 2022 Final Year Project (FYP) Truong, Q. D. (2022). Build a fact extractor for Python programs. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156460 https://hdl.handle.net/10356/156460 en SCSE21-0121 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering Truong, Quang Duc Build a fact extractor for Python programs |
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Software programs’ sizes are increasing since more features are built to meet the growing demands. Each version of a program must advance and address the flaws in previous versions over a short period. As the software programs evolve, program facts can be drawn from software artifacts to understand the dependencies among different pieces of code in a program and provide interesting insights about the version changes. These facts can, therefore, also be used for quality assurance.
Although fact extractors have been discussed for other various languages, there has been little done for Python. This report seeks to explore how facts can be extracted and stored in a “fact base” for Python programs by showing the approaches to writing fact extractors. |
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Li Yi |
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Li Yi Truong, Quang Duc |
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Truong, Quang Duc |
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Truong, Quang Duc |
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Build a fact extractor for Python programs |
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Build a fact extractor for Python programs |
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Build a fact extractor for Python programs |
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Build a fact extractor for Python programs |
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Build a fact extractor for Python programs |
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build a fact extractor for python programs |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/156460 |
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