A systematic review allows synthesizing the state of knowledge related to a clearly formulated research question as well as understanding the correlations between exposures and outcomes. A systematic review usually leverages explicit, reproducible, and systematic methods that allow reducing the potential bias that may arise when conducting a review. When properly conducted, a systematic review yields reliable findings from which conclusions and decisions can be made. Systematic reviews are increasingly popular and have several stakeholders to whom they allow making recommendations on how to act based on the review findings. They also help support future research prioritization. A systematic review usually has several components. The abstract is one of the most important parts of a review because it usually reflects the content of the review. It may be the only part of the review read by most readers when forming an opinion on a given topic. It may help more motivated readers decide whether the review is worth reading or not. But abstracts are sometimes poorly written and may, therefore, give a misleading and even harmful picture of the review’s contents. To assess the extent to which a review’s abstract is well constructed, we used a checklist-based approach to propose a measure that allows quantifying the systematicity of review abstracts i.e., the extent to which they exhibit good reporting quality. Experiments conducted on 151 reviews published in the software engineering field showed that the abstracts of these reviews had suboptimal systematicity.
Abstract. Software architecture recovery is a bottom-up process that aims at building high-level views that support the understanding of existing software applications. Many approaches have been proposed to support architecture recovery using various techniques. However, very few approaches are driven by the architectural styles that were used to build the systems under analysis. In this paper, we address the problem of recovering layered views of existing software systems. We re-examine the layered style to extract a set of fundamental principles which encompass a set of constraints that a layered system must conform to at design time and during its evolution. These constraints are used to guide the recovery process of layered architectures. In particular, we translate the problem of recovering the layered architecture into a quadratic assignment problem (QAP) based on these constraints, and we solve the QAP using a heuristic search algorithm. In this paper, we introduce the QAP formulation of the layering recovery and we present and discuss the results of the experimentation with the approach on four open source software systems.
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