Jesús Gorroñogoitia

Migrating Legacy Software to the Cloud with ARTIST

As cloud computing allows improving the quality of software and aims at reducing costs of operating software, more and more software is delivered as a service. However, moving from a software as a product strategy to delivering software as a service hosted in cloud environments is very ambitious. This is due to the fact that managing software modernization is still a major challenge, especially when paradigm shifts, such as moving to cloud environments, are targeted that imply fundamental changes to how software is modernized, delivered, and sold. Thus, in addition to technical aspects, business aspects need also to be considered. ARTIST proposes a comprehensive software modernization approach covering business and technical aspects. In particular, ARTIST employs Model-Driven Engineering (MDE) techniques to automate the reverse engineering of legacy software and forward engineering of cloud-based software in a way that modernized software truly benefits from targeted cloud environments. Therewith, ARTIST aims at reducing the risks, time, and costs of software modernization and lowers the barriers to exploit cloud computing capabilities and new business models.

ARTIST Methodology and Framework: A Novel Approach for the Migration of Legacy Software on the Cloud

Nowadays Cloud Computing is considered as the ideal environment for engineering, hosting and provisioning applications. A continuously increasing set of cloud-based solutions is available to application owners and developers to tailor their applications exploiting the advanced features of this paradigm for elasticity, high availability and performance. Although these offerings provide many benefits to new applications, they also incorporate constrains to the modernization and migration of legacy applications by obliging the use of specific technologies and explicit architectural design approaches. The modernization and adaptation of legacy applications to cloud environments is a great challenge for all involved stakeholders, not only from the technical perspective, but also in business level with the need to adapt the business processes and models of the modernized application that will be offered from now on, as a service. In this paper we present a novel model-driven approach for the migration of legacy applications in modern cloud environments which covers all aspects and phases of the migration process, as well as an integrated framework that supports all migration process.

Cloud modernization assessment framework: Analyzing the impact of a potential migration to Cloud

Many software companies have in mind jumping into the Cloud in order to take advantage of this technical paradigm as well as the innovative business models associated (such as SaaS). However, taking this leap becomes a hard task since it implies a high uncertainty and a raised risk without knowing when or even if the investment will be recovered. This paper presents the solution proposed by the ARTIST project to assess companies which are considering the migration of their products to Cloud, and provide estimations of the costs, ROI, efforts and migration tasks that this process could imply. The envisioned solution comprises a pre-migration phase through which 1) the maturity (to migrate to Cloud) of the application and the company will be measured, 2) a feasibility analysis both at technical and business level will be performed. In addition to the general approach of the proposed solution, this paper presents the first results obtained by means of a theoretical exercise conducted with the PetStore Java application.

A Situational Approach for the Definition and Tailoring of a Data-Driven Software Evolution Method

Successful software evolution heavily depends on the selection of the right features to be included in the next release. Such selection is difficult, and companies often report bad experiences about user acceptance. To overcome this challenge, there is an increasing number of approaches that propose intensive use of data to drive evolution. This trend has motivated the SUPERSEDE method, which proposes the collection and analysis of user feedback and monitoring data as the baseline to elicit and prioritize requirements, which are then used to plan the next release. However, every company may be interested in tailoring this method depending on factors like project size, scope, etc. In order to provide a systematic approach, we propose the use of Situational Method Engineering to describe SUPERSEDE and guide its tailoring to a particular context.

The MegaM@Rt2 ECSEL project: MegaModelling at Runtime – Scalable model-based framework for continuous development and runtime validation of complex systems

Abstract A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.

Grammar Based Genetic Programming for Software Configuration Problem

Software Product Lines (SPLs) capture commonalities and variability of product families, typically represented by means of feature models. The selection of a set of suitable features when a software product is configured is typically made by exploring the space of tread-offs along different attributes of interest, for instance cost and value. In this paper, we present an approach for optimal product configuration by exploiting feature models and grammar guided genetic programming. In particular, we propose a novel encoding of candidate solutions, based on grammar representation of feature models, which ensures that relations imposed in the feature model are respected by the candidate solutions.