Migrating to Cloud-Native Architectures Using Microservices: An Experience Report

Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not ready to fully exploit the benefits of this environment, and adapting them to this environment is a non-trivial task. Microservices have appeared recently as novel architectural styles that are native to the cloud. These cloud-native architectures can facilitate migrating on-premise architectures to fully benefit from the cloud environments because non-functional attributes, like scalability, are inherent in this style. The existing approaches on cloud migration does not mostly consider cloud-native architectures as their first-class citizens. As a result, the final product may not meet its primary drivers for migration. In this paper, we intend to report our experience and lessons learned in an ongoing project on migrating a monolithic on-premise software architecture to microservices. We concluded that microservices is not a one-fit-all solution as it introduces new complexities to the system, and many factors, such as distribution complexities, should be considered before adopting this style. However, if adopted in a context that needs high flexibility in terms of scalability and availability, it can deliver its promised benefits

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

A Planning Approach to Migrating Domain-specific Legacy Systems into Service Oriented Architecture

The planning work prior to implementing an SOA migration project is very important for its success. Up to now, most of this kind of work has been manual work. An SOA migration planning approach based on intelligent information processing methods is addressed to semi-automate the manual work. This thesis will investigate the principle research question: “How can we obtain SOA migration planning schemas (semi-) automatically instead of by traditional manual work in order to determine if legacy software systems should be migrated to SOA computation environment?”. The controlled experiment research method has been adopted for directing research throughout the whole thesis. Data mining methods are used to analyse SOA migration source and migration targets. The mined information will be the supplementation of traditional analysis results. Text similarity measurement methods are used to measure the matching relationship between migration sources and migration targets. It implements the quantitative analysis of matching relationships instead of common qualitative analysis. Concretely, an association rule and sequence pattern mining algorithms are proposed to analyse legacy assets and domain logics for establishing a Service model and a Component model. These two algorithms can mine all motifs with any min-support number without assuming any ordering. It is better than the existing algorithms for establishing Service models and Component models in SOA migration situations. Two matching strategies based on keyword level and superficial semantic levels are described, which can calculate the degree of similarity between legacy components and domain services effectively. Two decision-making methods based on similarity matrix and hybrid information are investigated, which are for creating SOA migration planning schemas. Finally a simple evaluation method is depicted. Two case studies on migrating e-learning legacy systems to SOA have been explored. The results show the proposed approach is encouraging and applicable. Therefore, the SOA migration planning schemas can be created semi-automatically instead of by traditional manual work by using data mining and text similarity measurement methods

Recommender systems in model-driven engineering: A systematic mapping review

Recommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and model-based development processes. In this paper, we report on a systematic mapping review (based on the analysis of 66 papers) that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of researchThis work has been funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 813884 (Lowcomote [134]), by the Spanish Ministry of Science (projects MASSIVE, RTI2018-095255-B-I00, and FIT, PID2019-108965GB-I00) and by the R&D programme of Madrid (Project FORTE, P2018/TCS-431

Building a Systematic Legacy System Modernization Approach

A systematic legacy system modernizing approach represents a new approach for modernizing legacy systems. Systematic legacy system modernization has software reuse as an integral part of modernization. We have developed a modernization approach which uses software architecture reconstruction to find reusable components within the legacy system. The practice of software development and modernization continues to shift towards the reuse of components from legacy systems to handle the complexities of software development. Modernization of a legacy system requires reuse of software artefacts from legacy system to conserve the business rules and improve the system’s quality attributes. Software reuse is an integral part of our systematic legacy modernization approach. Software should be considered as an asset and reuse of these assets is essential to increase the return on the development costs. Software reuse ranges from reuse of ideas to algorithms to any documents that are created during the software development life cycle. Software reuse has many potential benefits which include increased software quality, and decreased software development cost and time. Demands for lower software production and maintenance costs, faster delivery of systems and increased quality can only be met by widespread and systematic software reuse. In spite of all these benefits software reuse adoption is not widespread in the software development communities. Software reuse cannot possibly become an engineering discipline so long as issues and concerns have not been clearly understood and dealt with. We have conducted two surveys to understand the issues and concerns of software reuse in the Conventional Software Engineering (CSE) Community and the Software Product Line (SPL) Community where reuse is an integral part of the product development. The quantitative and qualitative analysis of our surveys identified the critical factors which affect and inhibit software engineers and developers adopting software reuse. Software reuse has been talked about in generic terms in software product lines. Though software reuse is a core concept in SPL it has however failed to become a standardized practice. The survey conducted on the SPL Community investigates how software reuse is adopted in SPL so as to provide the necessary degree of support for engineering software product line applications and to identify some of the issues and concerns in software reuse. The identified issues and concerns have helped us to understand the difference between software reuse in the CSE and SPL Communities. It has also given us an indication of how both communities can learn good software reuse practices from each other in order to develop a common software reuse process. Based on the outcome of our surveys we have developed a systematic software reuse process, called the Knowledge Based Software Reuse (KBSR) Process, which incorporates a Repository of reusable software assets to build a systematic legacy system modernization approach. Being able to reuse software artefacts, be it software requirement specification, design, or code, would greatly enhance software productivity and reliability. All of these software artefacts can go in the Knowledge Based Software Reuse Repository and be candidates for reuse

Model Driven Management of Complex Systems: Implementing the Macroscope\u27s vision

Several years ago, first generation model driven engineering (MDE) tools focused on generating code from high-level platform-independent abstract descriptions. Since then, the target scope of MDE has much broadened and now addresses for example testing, verification, measurement, tool interoperability, software evolution, and many more hard issues in software engineering. In this paper we study the applicability of MDE to another difficult problem: the management of complex systems. We show how the basic properties of MDE may be of significant help in this context and we characterize and extend MDE by the concept of a "megamodel", i.e. a model which elements may themselves be models. We sketch the basic characteristics of a tool for handling megamodels and we apply it to the example of the Eclipse.org ecosystem, chosen here as a representative illustration of a complex system. The paper finally discusses how the proposed original approach and tools may impact the construction and maintenance of computer based complex systems

Developing Legacy System Migration Methods and Tools for Technology Transfer

This paper presents the research results of an ongoing technology transfer project carried out in coopera- tion between the University of Salerno and a small software company. The project is aimed at developing and transferring migration technology to the industrial partner. The partner should be enabled to migrate monolithic multi-user COBOL legacy systems to a multi-tier Web-based architecture. The assessment of the legacy systems of the partner company revealed that these systems had a very low level of decompos- ability with spaghetti-like code and embedded control flow and database accesses within the user interface descriptions. For this reason, it was decided to adopt an incremental migration strategy based on the reengineering of the user interface using Web technology, on the transformation of interactive legacy programs into batch programs, and the wrapping of the legacy programs. A middleware framework links the new Web-based user interface with the Wrapped Legacy System. An Eclipse plug-in, named MELIS (migration environment for legacy information systems), was also developed to support the migration process. Both the migration strategy and the tool have been applied to two essential subsystems of the most business critical legacy system of the partner company