Proceedings. 12th IEEE International Workshop on Program Comprehension, 2004.
DOI: 10.1109/wpc.2004.1311049
|View full text |Cite
|
Sign up to set email alerts
|

Challenges and requirements for an effective trace exploration tool

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
12
0

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 16 publications
(13 citation statements)
references
References 22 publications
0
12
0
Order By: Relevance
“…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%
See 1 more Smart Citation
“…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%
“…It is integrated in the IDE to enable easy navigation between different views [22]. SEAT should be considered as a research vehicle in which the authors explored some critical features of trace visualization tools.…”
Section: -2005mentioning
confidence: 99%
“…These program exploration tools should identify those parts of the program that are likely to be interesting from a program understanding point of view [15,12]. For instance, in the case of objectoriented programs -which is the main focus of our workprogram exploration tools should reveal those classes that form core parts of the design.…”
Section: Introductionmentioning
confidence: 99%
“…In general, the data tend to be very large due to the existence of loops and recursion, making handling and analysis difficult. In order to contribute to the solution of this problem, one can considered the techniques of (HAMOU-LHADJ; LETHBRIDGE; FU, 2004) that dedicate compression of the volume of traces, making the understanding of structure easier.…”
Section: Dynamic Analysismentioning
confidence: 99%
“…Algorithm 1 is the pseudocode for extracting reduced subtrees from execution traces. In the second phase, traces are compressed removing parts that are identical, typically because of loops or recursion in method calls FU, 2004). So, the expected result of this compression is that the resulting larger subtrees contain more calls to distinct methods, instead of an absolute higher number of calls that could represent high number of calls to a few distinct methods.…”
Section: Phase 2 -Reducing the Size Of The Tracesmentioning
confidence: 99%