SEApr 29, 2021

A holistic approach for cross-platform software development

arXiv:2104.14614v115 citations
Originality Incremental advance
AI Analysis

This work addresses the challenge for developers who need to build software across multiple platforms, offering a more flexible and efficient solution compared to existing restricted or native methods, though it appears incremental in nature.

The authors tackled the problem of cross-platform software development by proposing a holistic approach using a general-purpose language to abstract platform details, enabling automatic code generation and deployment across multiple platforms. The approach was evaluated through recreating an existing system, testing with developers, and adding cross-platform testing support, showing potential for cost reduction and reuse.

Cross-platform development solutions can help to make software available on different devices and platforms. But these are normally restricted to preconfigured platforms and consider that each individual solution is equal or similar to each other. As a result, developers have to resort to native development and build individual solutions, one for each device/platform, that cooperate to deliver the desired global functionality. This article presents an approach that takes advantage of existing solutions and have support for extending and including new platforms, and distributing functionality across devices. The approach is based on a general-purpose language that raises the abstraction level in order to keep the software free from platform details. Automatic transformations produce executable code that can be properly divided and deployed separately into different platforms. The proposed approach was evaluated in four ways. In the first evaluation, an existing cross-platform system was recreated using the approach. The second and third evaluations was conducted with expert and novice developers, who tested the approach in practice. The fourth evaluation introduced support for cross-platform testing. Results have brought evidence supporting the following main contributions: use of a single environment, the ability to reuse similar concepts between platforms and the potential to reduce costs.

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