Static Taint Analysis Applied to Detecting Bad Programming Practices in Android
Frameworks and Application Programming Interfaces (API) usually come along with a set of guidelines that establish good programming practices in order to avoid pitfalls which could lead, at least, to bad user experiences, and at most, to program crashes. Most often than not, such guidelines are not...
Guardado en:
| Autores principales: | , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2017
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/66161 http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/ASSE/asse-04.pdf |
| Aporte de: |
| Sumario: | Frameworks and Application Programming Interfaces (API) usually come along with a set of guidelines that establish good programming practices in order to avoid pitfalls which could lead, at least, to bad user experiences, and at most, to program crashes. Most often than not, such guidelines are not at all enforced by IDEs. This work investigates whether static taint analysis could be effectively used for automatically detecting bad programming patterns in Android applications. It presents the implemented tool, called CheckDroid, together with the preliminary experimental evaluation carried out. |
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