Diabetes is a global health issue, requiring intensive management of medication, diet, and exercise for effective treatment. The oversaturated market of mobile apps for healthcare and wellness management raises questions about their efficacy among healthcare providers and patients. Despite the availability of various Diabetes Self-Management (DSM) mobile apps, their use remains limited in helping people with diabetes adopt lifestyle interventions or adjust medications. However, user feedback is an effective technique for monitoring and improving software. In this paper, our objective is to gather requirements based on user feedback analysis for DSM mobile apps. For this purpose, we categorize a total of 1649 user reviews collected from 44 mhealth apps into four categories: bug reports, feature requests, user experiences, and ratings. Among these, feature requests are further examined to support requirements specification.

Autism Spectrum Disorder (ASD) is a neurological and developmental disorder that affects human communication and behavior. ASD is associated with significant healthcare costs for diagnosis as well as for treatment. Disease diagnosis using deep learning model has become a wide research area. This paper proposes a deep classifier model for ASD prediction. The evaluation of the proposed model is performed over three datasets involving child, adolescent, and adult provided by ASDTest database. The obtained results showed that deep classifier model provides better results than other common machine learning classification techniques, with an accuracy of 99.50%, 99.23% and 99.42% for respectively adult, adolescent, and child datasets. Practical experiments conducted over these datasets report encouraging performances which are competitive to other existing ASD prediction models.

Software project scope defines functional and non-functional requirements. These requirements may change to satisfy the customers' needs. However, the control of scope creep represents one of the success keys in software project management. Changes in non-functional requirements affect the ISO/IEC 25010 quality characteristics such as security, portability, etc. Furthermore, some of these quality characteristics may evolve throughout the software life cycle into functional requirements. In this paper, we explore the use of COSMIC method - ISO/IEC 19761 to quantify and evaluate security change requests. Measuring the functional size of security change requests allows stakeholders to make appropriate decisions about whether to accept, defer, or deny the change.

To help developing continuous improvement in Information and Communication Technology, new software are required with functionality and characteristics different from the traditional one. Thus, measurement procedures need to be tailored to this new computing context. In fact, the software functional size is one of the important cost drivers of software development projects. An accurate measurement needs a detailed definition of software requirements and may require an important measurement effort. However, this is not always available. Thus, well defined measurement procedures requiring little effort and providing approximate or rapid measurement results are needed. The COSMIC Functional Size Measurement (FSM) method has knew a great success compared to other methods since it addresses different types of software including "business application", "mobile apps", etc. Moreover, it has been successfully used with UML diagrams for different objectives. In this paper, a Use Case based measurement procedure is proposed in order to estimate the functional size of mobile and web applications using COSMIC FSM method. The proposed procedure helps both beginners and experienced measurer in applying COSMIC and avoiding measurement errors. It is based on a set of measurement formulas tested and validated through the case study "Restaurant Management System".

UML diagrams became a common part of software requirement documentation, implementation, etc. In particular, the Use Case Diagram (UCD) is considered as the de-facto standard for modelling the user requirements at an early phase of the Software Development Life Cycle (SDLC). Each use case can be detailed by an Activity Diagram (UAD). Because Functional Changes (FC) are inevitable during the SDLC, it is required to identify the FC status at different levels of granularity. In our previous work, we proposed an approach for measuring the functional size of a FC in the UAD using COSMIC method. In this paper, we propose to extend this approach by including the UCD. In addition, we predict the status of a FC in UAD from its use case. This approach is applied before the FC implementation. It allows a rapid and an approximate evaluation of how important the FC is and it helps designers/managers in decision-making to answer the FC request.