API Usage Verification Through Dataflow Analysis
| dc.contributor.advisor | Tian Zhao | |
| dc.contributor.committeemember | Ethan Munson | |
| dc.contributor.committeemember | Christine Cheng | |
| dc.creator | Tapsoba, Kenneth Baptiste | |
| dc.date.accessioned | 2025-01-16T19:47:11Z | |
| dc.date.available | 2025-01-16T19:47:11Z | |
| dc.date.issued | 2014-12-01 | |
| dc.description.abstract | Using APIs in a program is often difficult because of the incomplete documentation and the shortage of available examples. To cope with that, we have seen the increase of API checking tools that provide efficient suggestions for API usage. However, most of those checking tools use a pattern-based analysis to determine errors such as misuse of API calls. In this thesis, we introduce a different analysis technique that relies on explicit API state transitions for the analysis of the program. We adopt a static dataflow analysis framework from SOOT to inspect state transitions at each program point. | |
| dc.identifier.uri | http://digital.library.wisc.edu/1793/88518 | |
| dc.relation.replaces | https://dc.uwm.edu/etd/646 | |
| dc.subject | API Usage | |
| dc.subject | Dataflow Analysis | |
| dc.subject | Program Analysis | |
| dc.subject | Soot | |
| dc.subject | Verification | |
| dc.title | API Usage Verification Through Dataflow Analysis | |
| dc.type | thesis | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | University of Wisconsin-Milwaukee | |
| thesis.degree.name | Master of Science |
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