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requirements can be used as proxies to retrieve similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn identify previously developed code. [Question/problem] Several NLP approaches for similarity computation are available, and there is little empirical evidence on the adoption of an effective technique in recommender systems specifically oriented to requirements-based code reuse. [Principal ideas/results] This study compares different state-of-the-art NLP approaches and correlates the similarity among requirements with the similarity of their source code. The evaluation is conducted on real-world requirements from two industrial projects in the railway domain. Results show that requirements similarity computed with the traditional tf-idf approach has the highest correlation with the actual software similarity in the considered context. Furthermore, results indicate a moderate positive correlation with Spearman's rank correlation coefficient of more than 0.5. [Contribution] Our work is among the first ones to explore the relationship between requirements similarity and software similarity. In addition, we also identify a suitable approach for computing requirements similarity that reflects software similarity well in an industrial context. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and categorization.

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The emergence of the microservice-oriented architecture (MSA) has led to increased maintainability, better readability, and better scalability. All these advantages make migrating a monolithic software towards an MSA an attractive prospect for organizations. The migration process is recognized to be complex and consequently risky and costly. This process is composed of two phases: (1) the microservice-based architecture recovery phase and (2) the transformation (i.e. materialization) phase.  In this paper, we propose a systematic approach to transform an object-oriented monolithic application towards an MS-oriented one by applying a set of transformation pattern. To validate our approach we automated it with our tool MonoToMicro, and applied it on a set of monolithic Java applications to be migrated towards microservices-based ones.

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Software developers rely on the clone-and-own approach to rapidly develop software product variants (PVs) that meet variability in market needs. To improve the comprehension of how PVs are evolved and varied, we analyze the clone-and-own practices applied by developers of these PVs. We perform an empirical study on 75 android families to gain insights about observable phenomena related to the commonality and variability between the source code of PVs of these families.In particular, we study three research questions to identify the commonality and variability related to the organization of source code files, cloning Java methods, and configuration parameters of AndroidManifest.xml files. The results show that cloning packages, Java files and Java methods is a common practice used by developers of all android families. Maintainers should put efforts for managing the diverse implementations (bodies) of the modified cloned methods and it is essential to consider the commonality and variability of configuration parameters.

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Smart Cities are future urban aggregations, where a multitude of heterogeneous systems and IoT devices interact to provide a safer, more efficient, and greener environment. The vision of smart cities is adapting accordingly to the evolution of software and IoT based services. The current trend is not to have a big comprehensive system, but a plethora of small, well integrated systems that interact one with each other. Monitoring these kinds of systems is challenging for a number of reasons.

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This paper presents two new challenges for the Telco ecosystem transformation in the era of cloud-native microservice-based architectures. (1) Development-for-Operations (Dev-for-Operations) impacts not only the overall workflow for deploying a Platform as a Service (PaaS) in an open foundry environment, but also the Telco business as well as operational models to achieve an economy of scope and an economy of scale. (2) For that purpose, we construct an integrative platform business model in the form of a Multi-Sided Platform (MSP) for building Telco PaaSes. The proposed MSP based architecture enables a multi-organizational ecosystem with increased automation possibilities for Telco-grade service creation and operation. The paper describes how the Dev-for-Operations and MSP lift constraints and offers an effective way for next-generation PaaS building, while mutually reinforcing each other in the Next Generation Platform as a Service (NGPaaS) framework.

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The reuse at the component level is generally more effective than the one at the object-oriented class level. This is due to the granularity level where components expose their functionalities at an abstract level compared to the fine-grained object-oriented classes. Moreover, components clearly define their dependencies through their provided and required interfaces in an explicit way that facilitates the understanding of how to reuse these components. Therefore, several component identification approaches have been proposed to identify components based on the analysis object-oriented software applications. Nevertheless, most of the existing component identification approaches did not consider co-usage dependencies between API classes to identify classes/methods that can be reused to implement a specific scenario. In this paper, we propose an approach to identify reusable software components in object-oriented APIs, based on the interactions between client applications and the targeted API. As we are dealing with actual clients using the API, dynamic analysis allows to better capture the instances of API usage. Approaches using static analysis are usually limited by the difficulty of handling dynamic features such as polymorphism and class loading. We evaluate our approach by applying it to three Java APIs with eight client applications from the DaCapo benchmark. DaCapo provides a set of pre-defined usage scenarios. The results show that our component identification approach has a very high precision.

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Cloud systems are complex and large systems where services provided by different operators must coexist and eventually cooperate. In such a complex environment, controlling the health of both the whole environment and the individual services is extremely important to timely and effectively react to misbehaviours, unexpected events, and failures. Although there are solutions to monitor cloud systems at different granularity levels, how to relate the many KPIs that can be collected about the health of the system and how health information can be properly reported to operators are open questions. This paper reports the early results we achieved in the challenge of monitoring the health of cloud systems. In particular we present CloudHealth, a model-based health monitoring approach that can be used by operators to watch specific quality attributes. The CloudHealth Monitoring Model describes how to operationalize high level monitoring goals by dividing them into subgoals, deriving metrics for the subgoals, and using probes to collect the metrics. We use the CloudHealth Monitoring Model to control the probes that must be deployed on the target system, the KPIs that are dynamically collected, and the visualization of the data in dashboards.

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In the literature of software engineering, many approaches have been proposed for the recovery of software architectures. These approaches propose to group classes into highly-cohesive and loosely-coupled clusters considered as architectural components. The recovered architecture plays mainly a documentation role, as high-level design views that enhance software understandability. In addition, architecture recovery can be considered as an intermediate step for migration to component-based platforms. This migration allows to fully benefit from all advantages brought by software component concept. For that, the recovered clusters should not be considered as simple packaging and deployment units. They should be treated as real components: true structural and behavior units that are instantiable from component descriptors and connected together to materialize the architecture of the software. In this paper, we propose an approach for revealing component descriptors, component instances and component-based architecture to materialize the recovered architecture of an object-oriented software in component-based languages. We applied our solution onto two well known component-based languages, OSGi and SOFA.

Abstract

In the literature of software engineering, many approaches have been proposed for the recovery of software architectures. These approaches propose to group classes into highly-cohesive and loosely-coupled clusters considered as architectural components. The recovered architecture plays mainly a documentation role, as high-level design views that enhance software understandability. In addition, architecture recovery can be considered as an intermediate step for migration to component-based platforms. This migration allows to fully benefit from all advantages brought by software component concept. For that, the recovered clusters should not be considered as simple packaging and deployment units. They should be treated as real components: true structural and behavior units that are instantiable from component descriptors and connected together to materialize the architecture of the software. In this paper, we propose an approach for revealing component descriptors, component instances and component-based architecture to materialize the recovered architecture of an object-oriented software in component-based languages. We applied our solution onto two well known component-based languages, OSGi and SOFA.

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Object-oriented Application Programing Interfaces (APIs) support software reuse by providing pre-implemented functionalities. Due to the huge number of included classes, reusing and understanding large APIs is a complex task. Otherwise, software components are admitted to be more reusable and understandable entities than object-oriented ones. Thus, in this paper, we propose an approach for reengineering object- oriented APIs into component-based ones. We mine components as a group of classes based on the frequency they are used together and their ability to form a quality-centric component. To validate our approach, we experimented on 100 Java applications that used Android APIs.

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A Software Product Line (SPL) aims at applying a pre-planned systematic reuse of large-grained software artifacts to increase the software productivity and reduce the development cost. The idea of SPL is to analyze the business domain of a family of products to identify the common and the variable parts between the products. However, it is common for companies to develop, in an ad-hoc manner (e.g. clone
and own), a set of products that share common functionalities and differ in terms of others. Thus, many recent research contributions are proposed to re-engineer existing product variants to a SPL. Nevertheless, these contributions are mostly focused on managing the variability at the requirement level. Very few contributions address the variability at the architectural level despite its major importance. Starting from this observation, we propose, in this paper, an approach to reverse engineer the architecture of a set of product variants. Our goal is to identify the variability and dependencies among architectural-element variants at the architectural level. Our work relies on Formal Concept Analysis (FCA) to analyze the variability. To validate the proposed approach, we experimented on two families of open-source product variants; Mobile Media and Health Watcher. The results show that our approach is able to identify the architectural variability and the dependencies.

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Migrating towards Service Oriented Architecture SOA has become a major topic of interest during the recent years. Since emerging service technologies have forced non-service based software systems to become legacy, many efforts and researches have been carried out to enable these legacy systems to survive. In this context, several service identification solutions have been proposed. These approaches are either manual, thus considered expensive, or rely on ad-hoc criteria that fail to identify relevant services. In this paper, within the big picture of migrating object-oriented legacy systems towards SOA, we address automatic service identification from source code based on service quality characteristics. To achieve this, we propose a quality measurement model where characteristics of services are refined to measurable metrics.

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Software quality is considered as one of the most important challenges in software engineering. It has many dimensions which differ from users’ point of view that depend on their requirements. Therefore, those dimensions lead to difficulty in measuring and defining the software quality properly. Software quality measurement is the main core of the software quality. Thus, it is necessary to study and develop the software measurements to meet the better quality. The use of libraries increases software quality more than that of using generic programming because these libraries are prepared and tested in advance. In addition, these libraries reduce the effort that is spent in designing, testing, and maintenance processes. In this research, we presented a new model to calculate the saved effort that results from using libraries instead of generic programming in the coding, testing, and productivity processes. The proposed model consists of three metrics that are Library Investment Ratio, Library Investment Level, and Program Simplicity. An empirical analyzes has been applied into ten projects to compare the results of the model with Reuse Percent. The results show that the model has better indication of the improvement of software quality and productivity rather than Reuse Percent.

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