Context: In the last few years, smartphones have become an essential part of our lives. Several mobile applications have been uploaded to their respective app stores on daily basis to facilitate the end-users. To ensure the availability of the application and its services, the application needs to be able to detect and deal with various types of changes. Mobile application based self-adaptation is regarded as a solution to handle the above-mentioned chnages. Objective: The objectives of this study are: (i) identification of current state-of-the-art techniques, frameworks, models, and algorithms for self-adaptation in mobile applications context, (ii) exploring the core challenges faced in the development of self-adaptive mobile applications, and (iii) conducting a SWOT (Strength Weakness Opportunity Threat) analysis to figure out the research gaps in the targeted research field. Method: To accomplish the mentioned objective, we conducted a systematic literature review to enlighten the need for adaptation in this domain, the targeted areas, their beneficial aspects, state-of-the-art proposed solutions, and their challenges. We performed the keyword-based search on 11 well-known databases to determine the potential studies published between years 2015 to 2020. In total, 31 studies (from 933 potential studies) are selected grounded on the defined inclusion and exclusion criteria. Results: The main findings of this work are: (i) MAPE-K (Monitor Analyze Plan Execute-Knowledge) model is frequently used in several studies due to its resilience, (ii) current work focuses on the android operating system due to its popularity and flexibility; however, it lacks in considering other mobile's operating systems, and (iii) reported work also lacks in mentioning any benchmark (self-adaptive framework). Conclusion: The current study is helpful for the researchers intended to work in the smartphones domain. From developers viewpoint, this study reports the faced challenges during the development of smartphones applications. Moreover, the performed study is beneficial in filling the identified research gaps by providing a foundation useful to plan future research regarding self-adaptation in smartphone applications context.
All Science Journal Classification (ASJC) codes
- Information Systems and Management