The experimental results from applying the hybrid approach on synthetic program transformation problems show a significant improve in the optimized output on which the hybrid approach achieved an LoC decline rate of 50.51% over the application of basic genetic algorithm only where 17.34% LoC decline rate was reached. In this research we targeted the program size, to reach the lowest possible decline rate of the number of Lines of Code (LoC) of a targeted program. It succeeded in optimizing the search process for the optimal program transformation sequence that targets a specific optimization goal. In this paper, we introduce a hybrid approach for program optimization. Developing applications that run on top of mobile devices requires the software developer to consider the limited resources of these devices, which on one side give them their mobile advantages, however, on the other side, if an application is developed without the consideration of these limited resources then the mobile application will neither work properly nor allow the device to run smoothly. Software development as well as other branches of software engineering has been affected by this progress. The vast field of software engineering that has witnessed a significant progress in the past years is responsible for this form of digital transformation. One form of the digital transformation revolution appears in the transformation of our routine everyday tasks into computer executable programs in the form of web, desktop and mobile applications. The digital transformation revolution has been crawling toward almost all aspects of our lives. First the algorithm is initialized with the rejected individuals from the GA, then the algorithm iterates through each individuals and calculates the velocity and personal best then the personal best is compared against the global best such that the global best will be overwritten with the personal best if the personal best achieves better result than the global best, otherwise the algorithm's iterations limit is checked such that the algorithm will output the global best and breaks if the iterations limit is reached, otherwise the algorithm will calculate the new position and velocity, increment i and j and continue. Below is the algorithm that describes the PSO integration: In the algorithm above, V, P, PB and GB are calculated according to Equations in (1) to (4). The position of a particle represents the currently targeted point in the search space that it traverses, the change of a particle's velocity reflects in a change of its position to attempt to reach a better solution. The Android Eclipce system environment, without developing the application and running in the emulator. This work will guide the researchers who want to develop applications in In detail along with the structures in xml and java files. Designs for building NEU-CEIT Android application are written The installation steps of the necessary software are mentioned.Īdroid SDK and Eclipse ADT installation, Android SDK directory settings, Android SDK and AVD manager settings, It providesĭetailed information on setting up a virtual device for Android, the hierarchical view and functions of Android project files, creatingĪn Android project from scratch and developing the application. Mobile application development steps are described for those who want to develop a mobile app for their ownīusiness, blog, service or product, but have limited resources for it. WhileĪndroid sets the ground for different applications, people are aiming for unlimited entertainment for their lives and learning while Android is known as an operating system that comes face to face with more than one million applications. In this work, an article has prepared which can be a guide to researchers who want to start developing Android-basedĪpplications.
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