Improving android applications searching and browsing by using information retrieval and static bytecode analysis
Abstract. A plethora of mobile applications have been developed to satisfy users needs. These applications help users to complete different activities like read books, access to bank accounts, listening to music, write notes, translate text, among others. All the applications are usually published o...
- Autores:
-
Bernal Cárdenas, Carlos Eduardo
- Tipo de recurso:
- Fecha de publicación:
- 2014
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/54046
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/54046
http://bdigital.unal.edu.co/48847/
- Palabra clave:
- 0 Generalidades / Computer science, information and general works
51 Matemáticas / Mathematics
62 Ingeniería y operaciones afines / Engineering
65 Gerencia y servicios auxiliares / Management and public relations
Information retrieval
Android
Search engines
Static analysis
Bytecode
Recuperación de información
Android
Motores de búsqueda
Análisis estático
Bytecode
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Abstract. A plethora of mobile applications have been developed to satisfy users needs. These applications help users to complete different activities like read books, access to bank accounts, listening to music, write notes, translate text, among others. All the applications are usually published on mobile markets, in which users can download the binary/byte-code that will be executed on the device. These markets provides information such as application description, rating, and related applications that is used when users perform a search. Nonetheless, most of the applications search engines only use textual information extracted from descriptions, applications names, software documentation, and source code. This thesis presents an approach that uses byte-code information such as sensors, permissions, and intents from Android APKs to augment the data that is used to perform the search. We surveyed 9 mobile developers to evaluate the effectiveness of our approach comparing it with other two search engines. As a result we obtained that there is no significant difference in the values of confidence level, precision, and normalized discounted cumulative gain compare to the other search engines. In addition we provided an in-depth analysis to validate and give reasoning about the obtained results. |
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