Software Architecture Recovery Techniques

There are many software architecture recovery techniques which has been discovered which automatically recover software architecture from the software implementation. In this project we will propose a research approach for comparing different software architecture recovery techniques. A dependency (code dependency) is a file that something you are trying to install requires. It can be a library of a third-party organization. These dependencies effect the application but it is very hard to makeany software without using these external dependencies. But these code dependencies have some disadvantages too. Firstly, we will specify about the code dependencies and their impact on software design. Then we will describe some software architecture recovery techniques. We will take a project (Bash) as our research base and we will apply these recovery techniques to the project. We will use some software testing tools to compare these algorithms (software recovery techniques) with each project.

Clustering Similarity Measures for Architecture Recovery of Evolving Software

Automated software architecture recovery of module views from source code is a challenging research issue. Different similarity measures are used to evaluate clustering algorithms in the software architecture recovery of module views. However, few studies seek to evaluate whether such measures accurately capture the similarities between two clusterings. This work presents an evaluation of six clustering similarity measures through the use of intrinsic quality and stability measures and the use of ground truth architectures proposed by developers. The results suggest that the MeCl metric is the most adequate to measure similarity in the context of comparison with ground truth models provided by developers. However, when the architectural models do not exist, the Purity metric shows the best results, as measured by the correlation with the intrinsic Silhouette coefficient.