A Comparative Study of Three Program Exploration Tools

Alwis, Brian de; Murphy, Gail C.; Robillard, Martin P.

doi:10.1109/icpc.2007.6

Cited by 22 publications

(18 citation statements)

References 16 publications

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“…Similar to findings by DeAlwis et al [dAMR07], it is thought that both the task size and the form of the task a↵ected the way that participants navigated the software codebases. Unexpectedly, participants performed more navigations in total while navigating the smaller TextEditor++ codebase than while navigating the larger JavaChat codebase.…”

Section: Discussionsupporting

confidence: 77%

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Visuo-spatial Programming: Visualising software structure to aid the integration of egocentric software navigation into an allocentric spatial cognitive map that supports software navigation and composition

Bradley¹

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Despite extensive research into the cognitive processes used by programmers to form a functional mental model of software during program comprehension, there has been little research into how the structure of software is represented within long-term spatial memory.It is conjectured that this lack of emphasis on the spatial aspects of code has inadvertently resulted in mainstream software development environments not adequately supporting relative navigation of the software call graph, which results in programmer disorientation.While software understanding tools for visualising object-oriented software have been developed that leverage spatial memory, opening a class to reveal its source code usually obscures the spatial representation and also places the source code in a single common location that has no spatial relationship to the code just navigated from. This is likely to interfere with the integration of spatial information related to individual source code files into a common cognitive map within spatial memory.A key challenge that tool designers face is that, for any non-trivial program, it is impossible to represent all of the source code of a program on the screen at once. Recent prototype environments have used a variety of strategies, including using a semantic zoom that allows classes to be represented with differing amounts of information visible, allowing fragments of classes to be arranged on independent surfaces, and representing individual methods as bubbles that can be grouped within a scrollable workspace. This project has taken a different approach by conferring a spatial structure on source code that is based on its emergent structure, and implementing a visualisation technique that uses this structure to provide a consistent spatial representation of methods. The method-flow visualisation technique has been developed to support short-term spatial memory by placing editor columns within a scrollable flow view that ensures each column maintains a consistent spatial position if scrolled. As the programmer navigates a call graph by following hyperlink-enabled method calls, editor columns are added to the righthand end of the flow view. At any time, the programmer can scroll the flow view to see previously traversed methods. It is theorised that method-flow allows short-term visuospatial memory to be refreshed, and provides more time for methods to be integrated into a cognitive map within spatial memory.Method-flow has been implemented as the Visuocode prototype software development environment and has been both informally and formally evaluated. Formal evaluation consisted of two qualitative think-aloud studies -the first of software navigation, and the second of program composition. Both formal studies asked each participant to perform a number of programming tasks using both Eclipse and Visuocode. During the studies, the screen activity of participants was recorded using screen-capture software, and later analysed to determine the number and type of navigations performed during each ...

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Section: Discussionsupporting

confidence: 77%

“…DeAlwis et al [dAMR07] reported on a quantitative study of 18 professional programmers that investigated the e↵ectiveness of three software exploration plug-ins for Eclipse. Each participant was asked to investigate and document a solution for two change tasks, and were given 40 minutes to complete each task.…”

Section: Alternative Technologiesmentioning

confidence: 99%

Visuo-spatial Programming: Visualising software structure to aid the integration of egocentric software navigation into an allocentric spatial cognitive map that supports software navigation and composition

Bradley¹

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“…Suade has been used in a case study comparing several program exploration tools [56], and it has also been directly compared to Dora [102], another static feature location technique.…”

Section: Tools For Static Feature Locationmentioning

confidence: 99%

“…JQuery [107], an Eclipse plug-in, is a source code browsing tool designed to help pro- De Alwis et al [56] performed a comparative study of three program exploration tools:…”

Section: Program Exploration Toolsmentioning

confidence: 99%

Supporting Feature-Level Software Maintenance

Revelle

2009

2009 16th Working Conference on Reverse Engineering

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Software maintenance is the process of modifying a software system to fix defects, improve performance, add new functionality, or adapt the system to a new environment. A maintenance task is often initiated by a bug report or a request for new functionality. Bug reports typically describe problems with incorrect behaviors or functionalities. These behaviors or functionalities are known as features. Even in very well-designed systems, the source code that implements features is often not completely modularized. The delocalized nature of features makes maintaining them challenging. Since maintenance tasks are expressed in terms of features, the goal of this dissertation is to support software maintenance at the feature-level. We focus on two tasks in particular: feature location and impact analysis via feature coupling.Feature location is the process of identifying the source code that implements a feature, and it is an essential first step to any maintenance task. There are many existing techniques for feature location that incorporate various types of analyses such as static, dynamic, and textual. In this dissertation, we recognize the advantages of leveraging several types of analyses and introduce a new approach to feature location based on combining dynamic analysis, textual analysis, and web mining algorithms applied to software. The use of web mining for feature location is a novel contribution, and we show that our new techniques based on web mining are significantly more effective than the current state of the art.After using feature location to identify a feature's source code, maintenance can be completed on that feature. Impact analysis should then be performed to revalidate the system and determine which other features may have been affected by the modifications. We define three feature coupling metrics that capture the relationship between features based on structural information, textual information, and their combination. Our novel feature coupling metrics can be used for impact analysis to quantify the strength of coupling between pairs of features. We performed three empirical studies on open-source software systems to asses the feature coupling metrics and established three major results. First,

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“…In order to consider this information, user studies are required, which assume collecting low level information, such as interaction events, from within the IDE [Fritz et al 2007]. We are planning on addressing this issue in our future work building on the results of prior user studies [de Alwis et al 2007;Ko et al 2006;Robillard et al 2004;Starke et al 2009]. A user study is also required to evaluate the practical usefulness of the attribute labels for navigational decisions during concept location.…”

Section: Threats To Validitymentioning

confidence: 99%

Concept location using formal concept analysis and information retrieval

Poshyvanyk

Gethers

Marcus

2012

ACM Trans. Softw. Eng. Methodol.

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________________________________________________________________________The paper addresses the problem of concept location in source code by proposing an approach that combines Formal Concept Analysis and Information Retrieval. In the proposed approach, Latent Semantic Indexing, an advanced Information Retrieval approach, is used to map textual descriptions of software features or bug reports to relevant parts of the source code, presented as a ranked list of source code elements. Given the ranked list, the approach selects the most relevant attributes from the best ranked documents, clusters the results, and presents them as a concept lattice, generated using Formal Concept Analysis.The approach is evaluated through a large case study on concept location in the source code on six opensource systems, using several hundred features and bugs. The empirical study focuses on the analysis of various configurations of the generated concept lattices and the results indicate that our approach is effective in organizing different concepts and their relationships present in the subset of the search results. In consequence, the proposed concept location method has been shown to outperform a standalone Information Retrieval based concept location technique by reducing the number of irrelevant search results across all the systems and lattice configurations evaluated, potentially reducing the programmers' effort during software maintenance tasks involving concept location.

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A Comparative Study of Three Program Exploration Tools

Cited by 22 publications

References 16 publications

Visuo-spatial Programming: Visualising software structure to aid the integration of egocentric software navigation into an allocentric spatial cognitive map that supports software navigation and composition

Visuo-spatial Programming: Visualising software structure to aid the integration of egocentric software navigation into an allocentric spatial cognitive map that supports software navigation and composition

Supporting Feature-Level Software Maintenance

Concept location using formal concept analysis and information retrieval

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