2014Unpublished venueRequires access

Interactive Scalable Abstraction of Reverse Engineered UML Class Diagrams

Mohd Hafeez Osman, Michel R. V. Chaudron, Peter van der Putten

Open publisher page 9 citations

Abstract

A large fraction of the time consumed in software development and maintenance is spent on understanding the software, which indicates it is a critical activity. Software documentation, including software architecture design documentation, is an important aid in software comprehension. However, keeping documentation up to date with evolving source code is often challenging and absence of up date or more comprehensive design-level documentation is not uncommon. As a solution, software architecture design may be recovered using reverse engineering techniques. However, existing reverse engineering methods produce complete design diagrams that include all the details that exist in the source code. The absence of abstraction from implementation details limits the usefulness of existing reverse engineering techniques for understanding software. This paper aims to address this problem by providing a method and tool that interactively allows developers to interactively explore a reverse engineered class diagram at scalable levels of abstraction. To this end, we propose a Software Architecure Abstraction (SAAbs) framework and an automated tool which implements the SAAbs framework. The SAAbs framework applies a machine learning scoring algorithm to produce a class importance ranking for class diagrams, this ranking is the basis for software architecture abstraction and visualization. We validate this framework by validating the SAAbs tool using a semi-structured survey. On average, 30 respondents of this survey rated 5.40 out of 6 points, which indicate that this is a useful tool to assist software developers in understanding a system.

About this research paper

What this paper is about

A large fraction of the time consumed in software development and maintenance is spent on understanding the software, which indicates it is a critical activity. Software documentation, including software architecture design documentation, is an important aid in software comprehension. However, keeping documentation up to date with evolving source code is often challenging and absence of up date or more comprehensive design-level documentation is not uncommon. As a solution, software architecture design may be recovered using reverse engineering techniques. However, existing reverse engineering methods produce complete design diagrams that include all the details that exist in the source code. The absence of abstraction from implementation details limits the usefulness of existing reverse engineering techniques for understanding software. This paper aims to address this problem by providing a method and tool that interactively allows developers to interactively explore a reverse engineered class diagram at scalable levels of abstraction. To this end, we propose a Software Architecure Abstraction (SAAbs) framework and an automated tool which implements the SAAbs framework. The SAAbs framework applies a machine learning scoring algorithm to produce a class importance ranking for class diagrams, this ranking is the basis for software architecture abstraction and visualization. We validate this framework by validating the SAAbs tool using a semi-structured survey. On average, 30 respondents of this survey rated 5.40 out of 6 points, which indicate that this is a useful tool to assist software developers in understanding a system.

Why it matters

OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

A large fraction of the time consumed in software development and maintenance is spent on understanding the software, which indicates it is a critical activity. Software documentation, including software architecture design documentation, is an important aid in software comprehension. However, keeping documentation up to date with evolving source code is often challenging and absence of up date or more comprehensive design-level documentation is not uncommon. As a solution, software architecture design may be recovered using reverse engineering techniques. However, existing reverse engineering methods produce complete design diagrams that include all the details that exist in the source code. The absence of abstraction from implementation details limits the usefulness of existing reverse engineering techniques for understanding software. This paper aims to address this problem by providing a method and tool that interactively allows developers to interactively explore a reverse engineered class diagram at scalable levels of abstraction. To this end, we propose a Software Architecure Abstraction (SAAbs) framework and an automated tool which implements the SAAbs framework. The SAAbs framework applies a machine learning scoring algorithm to produce a class importance ranking for class diagrams, this ranking is the basis for software architecture abstraction and visualization. We validate this framework by validating the SAAbs tool using a semi-structured survey. On average, 30 respondents of this survey rated 5.40 out of 6 points, which indicate that this is a useful tool to assist software developers in understanding a system.

Key concepts: Computer science, Reverse engineering, Software engineering, Documentation, Program comprehension, Software construction, Software development, Software system

Related papers

Back to paper searchBrowse research topicsOriginal source
Interactive Scalable Abstraction of Reverse Engineered UML Class Diagrams — Research Paper | ScholarLens