物件導向軟體之架構(Object-Oriented Software Construction)探討

Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

[서평]「The Unified Modeling Language User Guide」

[서평]「Component Software」 - Beyond Object-Oriented Programming -

https://www.cs.cmu.edu/~ckaestne/pdf/SCP12.pdf

FeatureIDE: An extensible framework for feature-oriented software development

https://hal.inria.fr/hal-00767175/document

FAMILIAR: A domain-specific language for large scale management of feature models

In product line engineering, domain analysis is the process of analyzing related products to identify their common and variable features. This process is generally carried out by experts on the basis of existing product descriptions, which are expressed in a more or less structured way. Modeling and reasoning about product descriptions are error-prone and time consuming tasks. Feature models (FMs) constitute popular means to specify product commonalities and variabilities in a compact way, and to provide automated support to the domain analysis process. This paper aims at easing the transition from product descriptions expressed in a tabular format to FMs accurately representing them. This process is parameterized through a dedicated language and high-level directives (e.g., products/features scoping). We guarantee that the resulting FM represents the set of legal feature combinations supported by the considered products and has a readable tree hierarchy together with variability information. We report on our experiments based on public data and characterize the properties of the derived FMs.

On extracting feature models from product descriptions

Feature modeling is a widely used technique in Software Product Line development. Feature models allow stakeholders to describe domain concepts in terms of commonalities and differences within a family of software systems. Developing a complex monolithic feature model can require significant effort and restrict the reusability of a set of features already modeled. We advocate using modeling techniques that support separating and composing concerns to better manage the complexity of developing large feature models. In this paper, we propose a set of composition operators dedicated to feature models. These composition operators enable the development of large feature models by composing smaller feature models which address well-defined concerns. The operators are notably distinguished by their documented capabilities to preserve some significant properties.

/pdf/composing-feature-models-45iit05b6s.pdf

Composing feature models

Reverse engineering the variability of an existing system is a challenging activity. The architect knowledge is essential to identify variation points and explicit constraints between features, for instance in feature models (FMs), but the manual creation of FMs is both time-consuming and error-prone. On a large scale, it is very difficult for an architect to guarantee that the resulting FM is consistent with the architecture it is associated with. In this paper, we present a comprehensive, tool supported process for reverse engineering architectural FMs. We develop automated techniques to extract and combine different variability descriptions of an architecture. Then, alignment and reasoning techniques are applied to integrate the architect knowledge and reinforce the extracted FM. We illustrate the process when applied to a representative software system and we report on our experience in this context.

/pdf/reverse-engineering-architectural-feature-models-4a2u5bvqs4.pdf

Reverse engineering architectural feature models

Feature models (FMs) are a popular formalism for describing the commonality and variability of software product lines (SPLs) in terms of features. As SPL development increasingly involves numerous large FMs, scalable modular techniques are required to manage their complexity. In this paper, we present a novel slicing technique that produces a projection of an FM, including constraints. The slicing allows SPL practitioners to find semantically meaningful decompositions of FMs and has been integrated into the FAMILIAR language.

Philippe Lahire

Papers

FAMILIAR: A domain-specific language for large scale management of feature models

On extracting feature models from product descriptions

Composing feature models

Reverse engineering architectural feature models

Slicing feature models