Stacksplorer

Karrer, Thorsten; Krämer, Jan-Peter; Diehl, Jonathan; Hartmann, Björn; Borchers, Jan

doi:10.1145/2047196.2047225

Cited by 37 publications

(2 citation statements)

References 24 publications

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“…Stacksplorer [21] visualizes method's callers in a column on the left of the code editor view, callees in the right one. ConcernMapper [14] eMoose [15] Pollicino [16] SE-Editor [17] Spotlight [18] TagSEA [19] DepDigger [12] RegViz [20] Stacksplorer [21] Traceclipse [22] TraceME [9] GUITA [23] Impromptu HUD [11] in situ profiler [1] Senseo [13] sparklines [24] CnP [25] HeatMaps [26] iTrace [8] Deep Intellisense [27] Miler [28] Rationalizer [29] 101companies [30] Code Bubbles [31] CoderChrome [10] Graphical overlays may be shown to visually connect the current method definition with the left column and method calls in the source code view to items in the right column. Traceclipse [22] and TraceME [9] are traceability management recovery tools.…”

Section: B Codementioning

confidence: 99%

Labeling Source Code with Metadata: A Survey and Taxonomy

Sulír¹,

Porubãn²

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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Source code is a primary artifact where programmers are looking when they try to comprehend a program. However, to improve program comprehension efficiency, tools often associate parts of source code with metadata collected from static and dynamic analysis, communication artifacts and many other sources. In this article, we present a systematic mapping study of approaches and tools labeling source code elements with metadata and presenting them to developers in various forms. We selected 25 from more than 2,000 articles and categorized them. A taxonomy with four dimensions-source, target, presentation and persistence-was formed. Based on the survey results, we also identified interesting future research challenges.

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Section: B Codementioning

confidence: 99%

Labeling Source Code with Metadata: A Survey and Taxonomy

Sulír¹,

Porubãn²

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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“…We choose to directly show source code to the user, as this provides the highest code proximity [19]. In their interviews, Brandt and Zaidman observed the developers navigating through the code using "jump-to-definition", a common strategy during code comprehension [20]- [23]. To let the developers keep the mental context of the methods they viewed, we show methods as rectangular nodes on a plane and use arrows to show calling relationships, similar to the Code Bubbles metaphor [24].…”

Section: Design Rationalementioning

confidence: 99%

How Does This New Developer Test Fit In? A Visualization to Understand Amplified Test Cases

Brandt

Zaidman

2022

2022 Working Conference on Software Visualization (VISSOFT)

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Developer testing, the practice of software engineers programmatically checking that their own components behave as they expect, has become the norm in today's software projects. With the constantly growing size and complexity of software projects and with the rise of automated test generation tools, understanding a test case is becoming more and more important compared to writing test cases from scratch.This holds especially in the area of developer-centric test amplification, where a tool automatically generates new test cases to improve a developer-maintained test suite. To investigate how visualization can help developers understand and judge test cases, we present the TESTIMPACTGRAPH, a visualization of the call tree and coverage impact of a JUnit test case proposed for amplification. It empowers the developer to drill down into the behavior of a test case, as well as providing them a clear view on how the proposed test case contributes to the coverage of the overall test suite. In a think-aloud study we investigate which information developers seek from the TESTIMPACTGRAPH, how its features can support them in accessing this information, and observations regarding the coverage impact of test cases. We infer ten actionable recommendations on how developer tests can be visualized to help developers understand their behavior and impact.

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