Call for papers, Automated and verifiable Software sYstem DEvelopment (ASYDE), 2024

During the last three decades, automation in software development has gone mainstream. Software development teams strive to automate as much of the software development activities as possible, spanning requirements specification, system modeling, code generation, testing, deployment, verification, as well as release phases, project status reporting, and system maintenance. Automation helps to reduce development time and cost, as well as to concentrate knowledge by bringing quality into every step of the development process.

Realizing high-quality software systems requires producing software that is efficient, error-free, cost-effective, and that satisfies evolving requirements. Thus, one of the most crucial factors impacting software quality concerns not only the automation of the development process but also the ability to verify the outcomes of each process activity and the goodness of the resulting software product as well. This becomes particularly true these days when we are, and will be, increasingly surrounded by a virtually infinite number of software artifacts – often underspecified – that can be composed to build new applications. This situation radically changes the way software will be produced and used: (i) software is increasingly produced according to a certain goal, that can change during the system’s execution, and by integrating existing software; (ii) the focus of software production is then on the ability to perform automated reasoning to achieve software integration and development that can be kept always correct-by-construction via static and dynamic verification.

This calls for automated software development methods and techniques, compositional verification theories, integration architectures, as well as, automated flexible and dynamic composition, and development mechanisms.

Despite great interest in automated and verifiable software system development, no common formal aspects and software engineering approaches have been fully established yet. Developing software systems via an automated generation and verification method encompasses a variety of foundational principles and practical aspects, ranging from modeling and analysis issues to model-checking, from model-driven development techniques and code synthesis to run-time management issues, and AI approaches such as machine learning tools and large language models (LLMs).

This special issue aims to collect contributions to address challenges related to novel software engineering approaches to automated and verifiable development of software systems.

Topic of interest:

Automated software development, verification and integration, for example, automated synthesis of software integration code, formal methods for automated software development, automated and verifiable software development, software quality assurance for automated software development.
Specification, architecture, and design of software and verification models.
Description and validation of non-functional properties of software.
Dynamic verification and testing.
Correct-by-construction software development.
Compositional theories for software development and its (dynamic) verification.
Service-oriented and component-based software development.
Serverless-based systems development.
Model-driven software development.
Microservices, for example, formal specification of (micro)services, formal models for microservices, methods and tools for (semi)-automatically migrating monolithic systems to component-based or microservice-based systems.
Automated planning methods.
Machine learning and AI techniques.
Automatic methods for the development and verification of smart contracts.

Deadline

29 September 2025

How to Submit

Submission link at Springer.

Guest editor list

Gianluca Filippone, gianluca.filippone@gssi.it (co-lead Guest Editor)

Gian Luca Scoccia, gianluca.scoccia@gssi.it (co-lead Guest Editor)

Marco Autili, marco.autili@univaq.it

Alessio Bucaioni, alessio.bucaioni@mdu.se

Lina Marsso, lina.marsso@utoronto.ca