Using Feature-Oriented Analysis to Recover Legacy Software Design for Software Evolution

Most design recovery approaches start from analysing source code. Nonetheless, it is very difficult to get adequate design information only depending on source code. Additional available information is required and Feature Oriented Analysis (FOA) is a way to reach this aim. FOA addresses the understanding of features in software systems and defines mechanisms for carrying a feature from the problem domain into the solution domain. Using feature as the first-class entity for software evolution can improve program comprehension and design recovery. In this paper, an approach is proposed to recover software design based on the feature model, which is a kind of legacy system knowledge. The features will first be located and mapped to the implementation module so that feature-oriented components can be identified and retrieved, and then, through the analysis of the feature relations, the design model of legacy system can be recovered and used for the future evolution

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

ModelVars2SPL : an automated approach to reengineer model variants into software product lines

Orientadora : Profª. Drª. Silvia R. VergilioCoorientador : Prof Dr. Roberto E. Lopez-HerrejonTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 11/04/2017Inclui referências : f. 74-82Área de concentração : Ciência da computaçãoResumo: Linhas de Produto de Software (LPSs) são famílias de sistemas de software relacionados que são desenvolvidos para um segmento de mercado ou domínio. Comumente, LPSs surgem de um conjunto de variantes existentes, quando a manutenção e/ou evolução individuais tornam-se complexas. Contudo, as abordagens encontradas na literatura para extração de LPS a partir de variantes existentes não dão suporte a modelos de projeto, são parcialmente automatizadas, ou não refletem restrições de domínio em termos de combinação de características. Para lidar com estas limitações, o objetivo deste trabalho é apresentar uma abordagem automatizada para fazer a reengenharia de variantes de modelos em uma LPS, chamada ModelVars2SPL (Variantes de Modelos para Linha de Produto de Software, do Inglês Model Variants to Software Product Line). A entrada para a abordagem é um conjunto de diagramas de classe Linguagem de Modelagem Unificada (UML) e uma lista de características que estes implementam. Todo o processo de reengenharia é coberto, e a saída inclui (i) um Modelo de Características, que representa a combinação de características das variantes de entrada, e (ii) uma Arquitetura de Linha de Produto, que representa uma arquitetura global com características anotadas. O processo de reengenharia da ModelVars2SPL é composto por quatro passos, sendo dois deles apoiados em técnicas baseadas em busca, e os dois outros baseados em algoritmos determinísticos. Não existe a necessidade de especialistas humanos para obter soluções. Para avaliar a abordagem proposta, foi conduzido um experimento para aferir a qualidade das soluções obtidas. A qualidade dos Modelos de Características e das Arquiteturas de Linha de Produto foi medida considerando-se o quão bem as variantes de entrada foram representadas. Além disso, a qualidade das saídas em cada passo da abordagem foi avaliada levando-se em consideração os objetivos do processo de reengenharia. Para a experimentação utilizaram-se dez estudos de caso representando dois cenários diferentes. Os resultados da avaliação mostram que a abordagem consegue obter soluções com alto grau de corretude em termos de representação das variantes de entrada, e que as saídas dos passos estão de acordo com as fases do processo de reengenharia. Com base em um exemplo de uso de uma solução mostra-se como os artefatos de LPS obtidos facilitam a atividade de manutenção. Palavras-chave: Reúso, Reengenharia, Linha de Produto de Software, Extração de LPS, Engenharia de Software Baseada em Busca.Abstract: Software Product Lines (SPLs) are families of related software systems developed for specific market segments or domains. SPLs commonly emerge from sets of existing variants when their individual maintenance and/or evolution become complex. However, current approaches for SPL extraction from existing variants do not support design models, are partially automated, or do not reflect domain constraints in terms of feature combinations. To tackle these limitations, the goal of this work is to present an automated approach to reengineer model variants into an SPL, called ModelVars2SPL (Model Variants to Software Product Line). The input of the approach is a set of Unified Modeling Language (UML) class diagrams and the list of features they implement. All the reengineering process is covered, and the output includes (i) a Feature Model, which represents the combinations of features of the input variants, and (ii) a Product Line Architecture, which represents a global architecture with feature-related annotations. The reengineering process of ModelVars2SPL is composed of four steps, two of them rely on searchbased techniques and the others are based on deterministic algorithms. There is no need for human experts for obtaining solutions. We conducted an experiment to evaluate the quality of the solutions obtained with the proposed approach. The quality of the FMs and PLAs was measured by considering how well these artifacts represent the input variants. Furthermore, we evaluate the quality of the outputs in each step of the approach taking into account the goals of the reengineering process. For the experimentation we used ten case studies representing two di_erent scenarios. The results of the evaluation show that the approach can obtain solutions with high degree of correctness in terms of representing the input variants, and that the outputs of the steps are in accordance to the phases of the reengineering process. Based on an example of use we show how the obtained FM and PLA make easier the maintenance activity. Keywords: Reuse, Reengineering, Software Product Line, SPL extraction, Search-Based Software Engineering

A program transformation step prediction based reengineering approach

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