Rigi—An environment for software reverse engineering, exploration, visualization, and redocumentation

Kienle, Holger M.; Müller, Hausi A.

doi:10.1016/j.scico.2009.10.007

Cited by 38 publications

(10 citation statements)

References 38 publications

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“…An excellent overview of software visualization is given by Diehl [23]. Wellknown software visualization systems include Rigi [24], VCG [25], aiSee [26], Mondrian [27], and sv3D [28] (for structure and metrics); and CodeCity [29,30] and SeeSoft [31] (for software evolution).…”

Section: Related Workmentioning

confidence: 99%

The Solid* toolset for software visual analytics of program structure and metrics comprehension: From research prototype to product

Reniers

Voinea

Ersoy

et al. 2014

Science of Computer Programming

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Software visual analytics (SVA) tools combine static program analysis and fact extraction with information visualization to support program comprehension. However, building efficient and effective SVA tools is highly challenging, as it involves extensive software development in program analysis, graphics, information visualization, and interaction. We present a SVA toolset for software maintenance, and detail two of its components which target software structure, metrics and code duplication. We illustrate the toolset's usage for constructing software visualizations with examples in education, research, and industrial contexts. We discuss the design evolution from research prototypes to integrated, scalable, and easy-to-use products, and present several guidelines for the development of efficient and effective SVA solutions.

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Section: Related Workmentioning

confidence: 99%

The Solid* toolset for software visual analytics of program structure and metrics comprehension: From research prototype to product

Reniers

Voinea

Ersoy

et al. 2014

Science of Computer Programming

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“…Panas et al [8] proposes a 3D visualization metaphor to model software production cost as real cities. A reverse engineering environment called Rigi is presented in [9] to analyze, interactively explore, summarize, and document large projects. Marcus et al [10] presented the sv3D framework for software visualization.…”

Section: A Visualizing Static Code Structurementioning

confidence: 99%

Visualizing Code Bad Smells

Hammad¹,

Alsofriya²

2019

IJACSA

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Software visualization is an effective way to support human comprehension to large software systems. In software maintenance, most of the time is spent on understanding code in order to change it. This paper presents a visualization approach to help maintainers to locate and understand code bad smells. Software maintainers need to locate and understand these bad smells in order to remove them via code refactoring. Object oriented code elements are visualized as well as their bad smells if they exist. The proposed visualization shows classes as building and bad smell as letter avatars based on the initials of the names of bad smells. These avatars are shown as warning signs on the buildings. A framework is proposed to automatically analyze code to identify bad smells and to generate the proposed visualizations. The evaluation of the proposed visualizations showed they reduce the comprehension time needed to understand bad smells.

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“…The eCST is more fine-grained than a FAMIX model. Heavyweight models similar to FAMIX, such as KDM [4] or ASTM [3] as well as general-purpose models such as RSF [45] or GXL [86] model not only the kinds of nodes, but also their relationships and structure explicitly. The same is true for M 3 [41], which is specifically designed for use with Rascal Metaprogramming Language [40] and which also includes noncode concepts such as physical and logical source locations.…”

Section: Multi-language Analysismentioning

confidence: 99%

Redundancy-free analysis of multi-revision software artifacts

Alexandru¹,

Panichella²,

Proksch³

et al. 2018

Empir Software Eng

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Researchers often analyze several revisions of a software project to obtain historical data about its evolution. For example, they statically analyze the source code and monitor the evolution of certain metrics over multiple revisions. The time and resource requirements for running these analyses often make it necessary to limit the number of analyzed revisions, e.g., by only selecting major revisions or by using a coarse-grained sampling strategy, which could remove significant details of the evolution. Most existing analysis techniques are not designed for the analysis of multi-revision artifacts and they treat each revision individually. However, the actual difference between two subsequent revisions is typically very small. Thus, tools tailored for the analysis of multiple revisions should only analyze these differences, thereby preventing re-computation and storage of redundant data, improving scalability and enabling the study of a larger number of revisions. In this work, we propose the Lean Language-Independent Software Analyzer (LISA), a generic framework for representing and analyzing multi-revisioned software artifacts. It employs a redundancy-free, multi-revision representation for artifacts and avoids re-computation by only analyzing changed artifact fragments across thousands of revisions. The evaluation of our approach consists of measuring the effect of each individual technique incorporated, an in-depth study of LISA resource requirements and a large-scale analysis over 7 million program revisions of 4,000 software projects written in four languages. We show that the time and space requirements for multi-revision analyses can be reduced by multiple orders of magnitude, when compared to traditional, sequential approaches.

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Rigi—An environment for software reverse engineering, exploration, visualization, and redocumentation

Cited by 38 publications

References 38 publications

The Solid* toolset for software visual analytics of program structure and metrics comprehension: From research prototype to product

The Solid* toolset for software visual analytics of program structure and metrics comprehension: From research prototype to product

Visualizing Code Bad Smells

Redundancy-free analysis of multi-revision software artifacts

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