From typestate verification to interpretable deep models (invited talk abstract)
| Autor: | Stephen Fink, Ganesan Ramalingam, Emmanuel Geay, Eran Yahav, Nurit Dor |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Java
Computer science Programming language 020207 software engineering 02 engineering and technology Static analysis computer.software_genre Domain (software engineering) Program analysis 020204 information systems Scalability 0202 electrical engineering electronic engineering information engineering Code (cryptography) Aliasing (computing) computer Program synthesis computer.programming_language |
| Zdroj: | ISSTA |
| DOI: | 10.1145/3293882.3338992 |
| Popis: | The paper ``Effective Typestate Verification in the Presence of Aliasing'' was published in the International Symposium on Software Testing and Analysis (ISSTA) 2006 Proceedings, and has now been selected to receive the ISSTA 2019 Retrospective Impact Paper Award. The paper described a scalable framework for verification of typestate properties in real-world Java programs. The paper introduced several techniques that have been used widely in the static analysis of real-world programs. Specifically, it introduced an abstract domain combining access-paths, aliasing information, and typestate that turned out to be simple, powerful, and useful. We review the original paper and show the evolution of the ideas over the years. We show how some of these ideas have evolved into work on machine learning for code completion, and discuss recent general results in machine learning for programming. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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