Software Architecture Module-View Recovery Using Cluster Ensembles

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Software architecture recovery using Conway's law

Architectural documentation is recognised as a mechanism for improving software quality and reducing development costs. However, many existing systems do not have any architectural documentation. To obtain the beneets of accurate architectural documentation, research suggests that we use tools to recover the architecture of a system, then continue to use these tools to keep the documentation up...

متن کامل

Software Architecture Recovery

The advent of modern technology shadows its impetus repercussions on successful Legacy systems making them obsolete with time. These systems have evolved the large organizations in major problems in terms of new business requirements, response time, financial depreciation and maintenance. Major difficulty is due to constant system evolution and incomplete, inconsistent and obsolete documents wh...

متن کامل

Pattern-based Software Architecture Recovery

This paper presents a technique for recovering the high level design of legacy software systems based on pattern matching and user defined architectural patterns. Architectural patterns are represented using a description language that is mapped to an attributed relational graph and allows to specify the legacy system components and their data and control flow interactions. Such pattern descrip...

متن کامل

Software Architecture Recovery and Modelling

This paper covers current trends and issues in software architecture recovery. It consists of a summary of the presentations and discussions of the Software Architecture Recovery and Modelling discussion forum held during WCRE 2001, the Working Conference on Reverse Engineering, Stuttgart, Germany, October 2, 2001.

متن کامل

Stacking Class Probabilities Obtained from View-Based Cluster Ensembles

In pattern recognition applications with high number of input features and insufficient number of samples, the curse of dimensionality can be overcome by extracting features from smaller feature subsets. The domain knowledge, for example, can be used to group some of the features together, which are also known as “views”. The features extracted from views can later be combined (i.e. stacking) t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Access

سال: 2019

ISSN: 2169-3536

DOI: 10.1109/access.2019.2920427