A Model Driven Approach for State Management in Mobile Applications
With the paradigm shift from desktop to mobile applications and the growing demand for mobile devices has awakened the interest of the IT industry on how to tackle the development of mobile applications. Managing application state is hard in building modern mobile applications. As application complexity increases, it becomes increasingly difficult to keep the track of changing state and mapping those changes back to user interface. State management is challenging due to its low-level implementation complexity. To overcome above mentioned issue, there is a strong need to introduce model driven approach for state management in mobile applications. This paper proposes a Unified Modeling Language profile for Mobile Application State Management (UMASM) to simplify mobile application state management requirements. Particularly, UMASM is capable of representing mobile state management requirements at higher abstraction level. This provides the strong basis to automatically generate low level implementations in target platform like Redux from high level UMASM models. The applicability of UMASM is validated through e-banking application case study.
MethApp4Mob: A Methodological Approach for Mobile Applications Development
The aspects of mobile technology have introduced challenges for developers, raising the need to improve the software development methodologies traditionally used. As a result of the analysis of the state of the art, an agile methodological approach for its development is presented, consisting of 8 phases: negotiation, planning, design, implementation and alpha testing, beta testing and feedback analysis, application publication, release and maintenance, promotion, and a series of steps, good practices, principles and tools, to offer mechanisms to accompany and streamline the development process. Some validations were carried out including a exploratory study, seeking to propose a robust methodology but at the same time easy to apply in a company.
Multi-directional spatial error concealment using adaptive edge thresholding
In this paper, a new method for spatial concealment of missing areas in image and video signals transmitted over error prone infrastructures, is presented. The concealment process is performed in three steps. First, a novel technique is used to estimate the significant edges of missing areas after performing a directional edge analysis on the correctly received neighboring blocks of the missing areas. This technique uses the moments of the neighboring edge magnitudes to obtain an adaptive threshold for rejecting non-significant directions. Second, based on the predicted significant directions, an approximation is obtained for each missing pixel. Finally, for each pixel, we compute a weighted average by using two edge correspondence measures as weighting factors. Moreover, the adaptive thresholding of the edges let us include as many edges as necessary in the interpolation process. Experiments show that the proposed method outperforms the previous state of the art methods based on both subjective and objective measures.