Abstract Context The most popular mobile platforms, Android and iOS, are traditionally developed using native programming languages—Java and Kotlin for Android, and Objective‐C followed by Swift for iOS, respectively. Due to their popularity, there is always a demand to convert applications written for one of these two platforms to another. Cross‐platform mobile development is widely used as a solution where an application is written once and deployed on multiple platforms written in several other programming languages. One common cross‐platform approach that has been used recently by some research groups is the Trans‐Compilation approach. They focus on translating a program written in iOS into Android or vice versa. The main problem with their solutions is that library function mapping is not generalized and usually functions constitute most of the parts of any program. Objective This study aims to introduce an automatic library mapping approach for mobile programming languages. Method A library function of a source language will be automatically mapped to a corresponding function of the destination language by using the function structure for the two languages. The function structure includes the library to which the function belongs, the return type, parameter types, and the number of parameters. To test our approach, we map from Swift to Java. Results The results of our experiments show that our automatic library mapping approach achieves an average accuracy of 83.6% when tested on the most used libraries and outperforms current state‐of‐the‐art mapping techniques in terms of mapping accuracy. Conclusion These findings show that our automatic mapping approach is promising and can help to overcome the limitations of the trans‐compilation approaches.

During humans' lifetime, their bodies deal with different chemicals through various sources. Chemical toxicity is a challenging problem that needs rapid and efficient methods for evaluation of environmental chemicals, or medications development. Computer science helps in toxicity prediction through building models from pre-tested compounds by learning from data. These models raise a flag to avoid trying some combinations for trial in wet-lab, which reduces the high cost of clinical trials. A compound chemical structure features are represented by Molecular Fingerprint. This survey searches for answers to Q1 How Fingerprints are dependent on the type of the prediction model? Q2 How valid are Fingerprints in toxicity prediction?. The Toxicology in the 21st Century challenge is the case study on this work. By showing the impact of fingerprints as descriptors on different predictive modeling techniques. The survey shows the independence of fingerprints as descriptors, as they work with different QSAR models. Also a need is noticed to test fingerprints separately without other descriptors in toxicity prediction to test their performance.

Mobile development companies aim to maximize the return on investments by making their mobile applications (Apps) available on different mobile platforms. Consequently, the same App is developed several times; each time the developer uses the programming languages and development tools of a specific platform. Therefore, there is a need to have cross-platform mobile applications development solutions that enable the developers to develop the App once and run it everywhere. The Integrated Cross-Platform Mobile Applications Development (ICPMD) solution is one of the attempts that enables the developers to use the most popular programming languages like Java for Android and C# for Windows Phone 8 (WP8). ICPMD is used to transform both the source code and user interface to another language to generate full Apps on the target platform. This paper extends ICPMD by proposing a new code conversion approach based on XSLT and Regular Expressions to ease the conversion process. In addition, it provides the assessment method to compare the ICPMD efficiency with competing approaches. Several Apps are converted from WP8 to Android and vice versa. The ICPMD evaluation results show reasonable improvement over commercial cross-platform mobile development tools (Titanium and Xamarin).