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Recover and RELAX: Concern-Oriented Software Architecture Recovery for Systems Development and Maintenance

机译:恢复和放松:面向问题的软件体系结构恢​​复,用于系统开发和维护

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The stakeholders of a system are legitimately interested in whether and how its architecture reflects their respective concerns at each point of its development and maintenance processes. Having such knowledge available at all times would enable them to continually adjust their systems structure at each juncture and reduce the buildup of technical debt that can be hard to reduce once it has persisted over many iterations. Unfortunately, software systems often lack reliable and current documentation about their architecture. In order to remedy this situation, researchers have conceived a number of architectural recovery methods, some of them concern-oriented. However, the design choices forming the bases of most existing recovery methods make it so none of them have a complete set of desirable qualities for the purpose stated above. Tailoring a recovery to a system is either not possible or only through iterative experiments with numeric parameters. Furthermore, limitations in the scalability of the employed recovery algorithms make it prohibitive to apply the existing techniques to large systems. Finally, since several current recovery methods employ non-deterministic sampling, their inconsistent results do not lend themselves well to tracking a systems course over several versions, as needed by its stakeholders. RELAX (RELiable Architecture EXtraction), a new concern-based recovery method that uses text classification, addresses these issues efficiently (1) by assembling the overall recovery result from smaller, independent parts, (2) basing it on an algorithm with linear time complexity and (3) being tailorable to the recovery of a single system or a sequence thereof through the selection of meaningfully named, semantic topics. An intuitive and informative architectural visualization rounds out RELAX's contributions. RELAX is illustrated on a number of existing open-source systems and compared to other recovery methods.
机译:一个系统的利益相关者对它的体系结构在开发和维护过程的每个点上是否以及如何反映他们各自的关注有合法的兴趣。始终拥有这样的知识将使他们能够在每个关头持续调整其系统结构,并减少技术债务的积累,一旦这种债务持续了多次迭代,就很难减少。不幸的是,软件系统通常缺乏有关其体系结构的可靠且最新的文档。为了纠正这种情况,研究人员构思了许多体系结构恢​​复方法,其中一些是关注问题的。但是,构成大多数现有回收方法基础的设计选择使其无法实现上述目的,因此它们都没有一整套理想的质量。为系统量身定制恢复是不可能的,或者只能通过使用数字参数进行迭代实验来实现。此外,所采用的恢复算法的可伸缩性方面的限制使得无法将现有技术应用于大型系统。最后,由于几种当前的恢复方法采用了不确定性采样,因此,它们的不一致结果并不能很好地帮助他们按照涉众的需要来跟踪多个版本的系统进程。 RELAX(RELiable Architecture Extraction)是一种新的基于关注点的恢复方法,使用文本分类,可以有效地解决这些问题(1)通过组合较小的独立部分的总体恢复结果,(2)基于线性时间复杂度的算法(3)通过选择有意义命名的语义主题,使其适合于单个系统或其序列的恢复。直观,信息丰富的建筑可视化功能完善了RELAX的贡献。 RELAX已在许多现有的开源系统上进行了说明,并与其他恢复方法进行了比较。

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