Visual representations of executing programs

Reiss, Steven P.

doi:10.1016/j.jvlc.2007.01.003

Cited by 28 publications

(19 citation statements)

References 32 publications

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“…Similar to other works (e.g., [5,6,12]) in the domain of trace analysis for program comprehension we use the following definition of execution phases: "a program [execution] phase is a portion of the program that exhibits common behavior at a level the programmer would recognize" [5]. In such context, we want to be able to take an execution trace (generated from exercising one or more particular features) and identify a set of high-level tasks (i.e.…”

Section: What Is An Execution Phase?supporting

confidence: 83%

“…The phases in this case are the key steps of the algorithm. At a lower level of abstraction the execution phases of a program written in a specific programming language are portions of the program execution that collaborate with each other to implement a specific task ( [5,6]). The lowest level of abstraction of a program is presented as machine code.…”

Section: What Is An Execution Phase?mentioning

confidence: 99%

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A Novel Approach Based on Gestalt Psychology for Abstracting the Content of Large Execution Traces for Program Comprehension

Pirzadeh

Hamou-Lhadj

2011

2011 16th IEEE International Conference on Engineering of Complex Computer Systems

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The analysis of execution traces can reveal important information about the behavioral aspects of complex software systems, hence reducing the time and effort it takes to understand and maintain them. Traces, however, tend to be considerably large which hinders their effective analysis. Existing traces analysis tools rely on some sort of visualization techniques to help software engineers make sense of trace content. Many of these techniques have been studied and found to be limited in many ways. In this paper, we present a novel trace analysis technique that automatically divides the content of a large trace into meaningful segments that correspond to the program's main execution phases such as initializing variables, performing a specific computation, etc. These phases can simplify significantly the exploration of large traces by allowing software engineers to first understand the content of a trace at a high-level before they decide to dig into the details. Our phase detection method is inspired by Gestalt laws that characterize the proximity, similarity, and continuity of the elements of a data space. We model these concepts in the context of execution traces and show how they can be used as gravitational forces that yield the formation of dense groups of trace elements, which indicate candidate phases. We applied our approach to two software systems. The results are very promising.

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Section: What Is An Execution Phase?supporting

confidence: 83%

Section: What Is An Execution Phase?mentioning

confidence: 99%

A Novel Approach Based on Gestalt Psychology for Abstracting the Content of Large Execution Traces for Program Comprehension

Pirzadeh

Hamou-Lhadj

2011

2011 16th IEEE International Conference on Engineering of Complex Computer Systems

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“…OVATION; TPTP* preliminary; user feedback general understanding [15] SCENE* preliminary software reuse [6], [16] ISVIS* case study architecture reconstruction, feature location [17], [18] SCED; SHIMBA case study debugging; various comprehension tasks [19] FORM case study detailed understanding; distributed systems [20] JAVAVIS preliminary; user feedback educational purposes; detailed understanding [21], [4], [22], [23] SEAT small case studies; user feedback general understanding [24], [25], [26], [27] SCENARIOGRAPHER multiple case studies detailed understanding; distributed systems; feature analysis; large-scale software [28], [29], [30] small case study quality control; conformance checking [10] multiple case studies general understanding [31] case study trace comparison; feature analysis [32] case study feature analysis [33] case study architecture reconstruction; conformance checking; behavioral profiles [34] TRACEGRAPH industrial case study feature analysis [35], [36] SDR; JRET* multiple case studies detailed understanding through test cases [37] FIELD; JIVE; JOVE multiple case studies performance monitoring; phase detection [38] --API understanding [39], [7] EXTRAVIS* multiple case studies fan-in/-out analysis; feature analysis; phase detection [40] OASIS user study various comprehension tasks [41] small case studies general understanding; wireless sensor networks March 8, 2010 DRAFT Cornelissen, Zaidman, van Deursen -A Controlled Experiment for Program Comprehension…”

Section: A Execution Trace Analysismentioning

confidence: 99%

A Controlled Experiment for Program Comprehension through Trace Visualization

Cornelissen

Zaidman

Deursen

2011

IIEEE Trans. Software Eng.

114

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Software maintenance activities require a sufficient level of understanding of the software at hand that unfortunately is not always readily available. Execution trace visualization is a common approach in gaining this understanding, and among our own efforts in this context is EXTRAVIS, a tool for the visualization of large traces. While many such tools have been evaluated through case studies, there have been no quantitative evaluations to the present day. This paper reports on the first controlled experiment to quantitatively measure the added value of trace visualization for program comprehension.We designed eight typical tasks aimed at gaining an understanding of a representative subject system, and measured how a control group (using the Eclipse IDE) and an experimental group (using both Eclipse and EXTRAVIS) performed in terms of correctness and time spent. The results are statistically significant in both regards, showing a 22% decrease in time needed for the given tasks, and a 43% increase in correctness of the results for the group using trace visualization. Index TermsProgram comprehension, dynamic analysis, controlled experiment.B. Cornelissen is with the Software Improvement Group, A.J.

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“…However, most trace extraction and visualization efforts to date (e.g., [14,31,33,49,53,56,57]) consider the trace at the code level. In contrast, our traces are abstracted to the model level; we only trace events that are relevant to the model defined by the user, and our traces embed information about the progress of the model, its states etc., which do not always exist explicitly in the code of the reference program.…”

Section: Execution Trace Visualizationmentioning

confidence: 99%

On tracing reactive systems

Maoz

Harel

2010

Softw Syst Model

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We present a rich and highly dynamic technique for analyzing, visualizing, and exploring the execution traces of reactive systems. The two inputs are a designer's interobject scenario-based behavioral model, visually described using a UML2-compliant dialect of live sequence charts (LSC), and an execution trace of the system. Our method allows one to visualize, navigate through, and explore, the activation and progress of the scenarios as they "come to life" during execution. Thus, a concrete system's runtime is recorded and viewed through abstractions provided by behavioral models used for its design, tying the visualization and exploration of system execution traces to model-driven engineering. We support both event-based and real-time-based tracing, and use details-on-demand mechanisms, multi-scaling grids, and gradient coloring methods. Novel model exploration techniques include semanticsbased navigation, filtering, and trace comparison. The ideas are implemented and tested in a prototype tool called the Tracer.

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Visual representations of executing programs

Abstract: Abstract

Cited by 28 publications

References 32 publications

A Novel Approach Based on Gestalt Psychology for Abstracting the Content of Large Execution Traces for Program Comprehension

A Novel Approach Based on Gestalt Psychology for Abstracting the Content of Large Execution Traces for Program Comprehension

A Controlled Experiment for Program Comprehension through Trace Visualization

On tracing reactive systems

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