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Skip to Search Results- 1Conclusion stability
- 1Defect prediction
- 1Energy Estimation
- 1Mobile Application
- 1Static Analysis
- 1Time-aware evaluation
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2022
Bangash, A.A., Ali, K., Hindle, Abram
Android byte-code transformations are used to optimize applications (apps) in terms of run-time performance and size. But do they affect the energy consumption during this process? If they do, can we employ them to reduce an app’s energy consumption? Given that most existing energy optimization...
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2023
Bangash, A.A., Eng, K., Jamal, Q., Ali, K., Hindle, Abram
Smartphone application (app) developers measure the energy consumption of their apps to ensure that they do not consume excessive energy. However, existing techniques require developers to generate and execute test cases on expensive, sophisticated hardware. To address these challenges, we...
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2021
Bangash, A.A., Tiganov, D., Ali, K., Hindle, Abram
Several types of apps require accessing user location, including map navigation, food ordering, and fitness tracking apps. To access user location, app developers use frameworks that the underlying platform provides to them. For the iOS platform, the Core Location framework enables developers to...
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2020
Bangash, A., Sahar, H., Hindle, Abram, Ali, K.
Researchers in empirical software engineering often make claims based on observable data such as defect reports. Unfortunately, in many cases, these claims are generalized beyond the data sets that have been evaluated. Will the researcher’s conclusions hold a year from now for the same software...
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2019
Bangash, A.A., Sahar, H., Chowdhury, S., Wong, A.W., Hindle, Abram, Ali, K.
Machine learning, a branch of Artificial Intelligence, is now popular in software engineering community and is successfully used for problems like bug prediction, and software development effort estimation. Developers' understanding of machine learning, however, is not clear, and we require...