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| Content Provider | ACM Digital Library |
|---|---|
| Author | Scanniello, Giuseppe Francese, Rita Risi, Michele Gravino, Carmine Tortora, Genoveffa |
| Abstract | In this paper, we focus on the definition of estimators to predict method calls in Android apps. Estimation models are based on information from requirements specification documents (e.g., number of actors, number of use cases, and number of classes in the conceptual model). We have used a dataset containing information on 23 Android apps. After performing data-cleaning, we applied linear regression to build estimation models on 21 data points. Results suggest that measures gathered from requirements specification documents can be considered good predictors to estimate the number of internal calls (i.e., methods invoking other methods present in the app) and external calls (i.e., invocations to API) as well as their sum. |
| Starting Page | 13 |
| Ending Page | 14 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781450341783 |
| DOI | 10.1145/2897073.2897113 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-05-14 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Estimation models Empirical study Android platform |
| Content Type | Text |
| Resource Type | Article |
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