For example, providing users may continuously configure and modify custom content with one app variant whereas end users are supposed to use provided content in their variant.
We present a modeling language and an infrastructure for the model-driven development (MDD) of Android apps supporting the specification of different app variants according to user roles. Due to short time-to-market, differing platforms and fast emerging technologies, mobile application development faces typical challenges where model-driven development can help.
Rapidly increasing numbers of applications and users make the development of mobile applications to one of the most promising fields in software engineering. The paper also describes the usability evaluation methodology applied and documents the results focusing on interaction difficulties and practical obstacles reported by the users as well as suggestions for future versions of the application, which generally received quite positive feedback. The use of ICONIX made analysis and design keep a sharp focus on user requirements, assured design and coding documentation, fostered an excellent communication among all participants and stake holders and provided the crucial advantage of high reusability in case of implementing the same application for additional smart phone platforms. The Tennis Coaching Assistant (TCA) is an iPhone application that provides management and scheduling capabilities for tennis coaches and allows a comprehensive overview of the execution of on-court drills and coaching programs. It also studies the integration of hand-held haptic devices in daily work activities by evaluating the usability of the application using as basis test scenarios deriving from the identified use cases. This paper investigates the application of ICONIX, a use case driven, object-oriented (OO) analysis and design methodology, for the development of a smart phone personal assistant.
Smart phone application development is a very active field for both research and the market domain. Having such a type information in hand programmers can identify critical classes more easily and can perform optimizations based on evidence rather than speculations. We can extract information on individual memory operations as well as supply aggregated overview. On top of the usual heap profiler features our allocation entries, including those of template constructs, contain exact type information about the allocated objects.
In this paper we present a type-preserving heap profiler for C++.
Therefore in large software systems programmers do not have an overall picture of which data structures are responsible for bottlenecks and have too few clues for pinpointing enhancement possibilities. Though this information can be retrieved from the location and time of allocation, it cannot be easily automated, if at all. Reporting the actual allocation size gives minimal or no information about the structure or type of the allocated objects. However, in case of some strongly typed programming languages, like C++, the question what has been allocated is not trivial. The sequence of allocations inform us about their order.
Most heap profilers provide sufficient information about which part of the source code is responsible for the memory allocations by showing us the relevant call stacks. They help to reveal memory handling details: the wheres, the whens and the whats of memory allocations. Memory profilers are essential tools to understand the dynamic behaviour of complex modern programs.