Revisiting the Delta IC approach to component recovery

Canfora, G.; Czeranski, J.; Koschke, R.

doi:10.1109/wcre.2000.891461

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…Each chain represents a new package containing classes having similar responsibilities (i.e., highly coupled classes) and that should be in the same package after the refactoring process. However, in the class-by-class matrix there could be very few zero values, due to spurious (but light) structural and/or conceptual relationships between classes [7]. Thus, a transitive closure may include almost all the classes in a single chain.…”

Section: Tool Architecturementioning

confidence: 99%

Extract Package Refactoring in ARIES

Palomba

Tufano

Bavota

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

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Software evolution often leads to the degradation of software design quality. In Object-Oriented (OO) systems, this often results in packages that are hard to understand and maintain, as they group together heterogeneous classes with unrelated responsibilities. In such cases, state-of-the-art re-modularization tools solve the problem by proposing a new organization of the existing classes into packages. However, as indicated by recent\ud empirical studies, such approaches require changing thousands of lines of code to implement the new recommended modularization. In this demo, we present the implementation of an Extract Package refactoring approach in ARIES (Automated Refactoring In EclipSe), a tool supporting refactoring operations in Eclipse. Unlike state-of-the-art approaches, ARIES automatically identifies and removes single low-cohesive packages from software\ud systems, which represent localized design flaws in the package organization, with the aim to incrementally improve the overall quality of the software modularisation

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Section: Tool Architecturementioning

confidence: 99%

Extract Package Refactoring in ARIES

Palomba

Tufano

Bavota

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

View full text Add to dashboard Cite

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“…The concept-based techniques were evaluated by Alexander Porrmann using the same framework [29]. Additionally, in joint work with Gerardo Canfora and Jörg Czeranski, we improved the Delta-IC method [7] (originally developed by Canfora and others [11]). The difference between the old and new version of Delta-IC was measured using the evaluation framework.…”

Section: The Time After the Publication Of The Dissertation: Its Recementioning

confidence: 99%

Atomic architectural component recovery for program understanding and evolution

Koschke¹

International Conference on Software Maintenance, 2002. Proceedings.

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111

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Component recoveryOver time, ad-hoc changes deteriorate the system structure. These changes make program understanding increasingly more difficult; they decrease cohesion within components and increase coupling among components aggravating subsequent changes. Ad-hoc changes are rarely well documented making architectural descriptions obsolete. All these negative effects lead to increased maintenance costs. To get back control on large and complex legacy systems suffering from ad-hoc changes, it is necessary to recover the software architecture as built, to improve the architecture, and to restructure the system accordingly. Component recovery is a means to this end. Its purpose is to retrieve logical components from existing systems. Component are structural entities used to group elements. Types of components considered in this thesis are modules and subsystems. As opposed to the actual physical components of a system, i.e., the files, packages, or source directories of the system, logical components may only contain related elements that jointly contribute to a common purpose. This thesis is on automatic and semiautomatic methods for component recovery. Historic perspective -the impact of this dissertationThis dissertation was published two years ago -too little time to fully develop its impact. Yet, a look back in the history of component recovery and the recent reception of this dissertation allows at least a glimpse on the impact of this dissertation on research in that area. Period of pioneering featComponent recovery and remodularization techniques have been studied since the early eighties. Belady and Evangelisti in 1982 [9] and Hutchens and Basili in 1985 [10] were among the first researchers in that area. Since then, component recovery has been a very active research area. At the time when the research to this dissertation started, more than 20 research papers had been published on fully automatic and semi-automatic techniques for component recovery, and their number is still growing .These papers proposed many new interesting techniques. However, many of these techniques were not really evaluated quantitatively. If authors did evaluate their techniques, the evaluation was not comparable to evaluations of other authors because different evaluation techniques were used for different subject systems. Therefore, it was not clear which techniques one should use under which circumstances; it was not even clear whether these automatic techniques compare to manual remodularization at all.The abundance of published methods called for frameworks to unify, classify, and compare them in order to make informed selections of appropriate component recovery techniques. The dissertation's contribution in the period of consolidationThe dissertation is the first contribution to a consolidation in component recovery. Its contributions are explained in the following.

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A user‐assisted approach to component clustering

Sartipi

Kontogiannis

2003

J. Softw. Maint. Evol.: Res. Pract.

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In this paper, we present a user‐assisted clustering technique for software architecture recovery based on a proximity measure that we call component association. The component association measure is computed on the shared properties among groups of highly related system entities. In this approach, the software system is modeled as an attributed relational graph with the software constructs (entities) represented as nodes and data/control dependencies represented as edges. The application of data mining techniques on the system graph allows us to generate a component graph where the edges are labeled by the association strength values among the components. An interactive partitioning technique is used to partition a system into cohesive components. Graph visualization tools and cluster quality evaluation metrics are applied by the user to assess and fine tune the partition result. Copyright © 2003 John Wiley & Sons, Ltd.

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Revisiting the Delta IC approach to component recovery

Cited by 4 publications

References 26 publications

Extract Package Refactoring in ARIES

Extract Package Refactoring in ARIES

Atomic architectural component recovery for program understanding and evolution

A user‐assisted approach to component clustering

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