The Experts below are selected from a list of 127221 Experts worldwide ranked by ideXlab platform
Bart Van Rompaey - One of the best experts on this subject based on the ideXlab platform.
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trace visualization for program comprehension a Controlled Experiment
International Conference on Program Comprehension, 2009Co-Authors: B Cornelissen, Andy Zaidman, Arie Van Deursen, Bart Van RompaeyAbstract:Understanding software through dynamic analysis has been a popular activity in the past decades. One of the most common approaches in this respect is execution trace analysis: among our own efforts in this context is EXTRAVIS, a tool for the visualization of large traces. Similar to other trace visualization techniques, our tool has been validated through anecdotal evidence, but should also be quantitatively evaluated to assess its usefulness for program comprehension. This paper reports on a first Controlled Experiment concerning 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 21% decrease in time and a 43% increase in correctness for the latter group.
B Cornelissen - One of the best experts on this subject based on the ideXlab platform.
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a Controlled Experiment for program comprehension through trace visualization
IEEE Transactions on Software Engineering, 2011Co-Authors: B Cornelissen, Andy Zaidman, A Van DeursenAbstract: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 these tasks in terms of time spent and solution correctness. The results are statistically significant in both regards, showing a 22 percent decrease in time requirements and a 43 percent increase in correctness for the group using trace visualization.
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trace visualization for program comprehension a Controlled Experiment
International Conference on Program Comprehension, 2009Co-Authors: B Cornelissen, Andy Zaidman, Arie Van Deursen, Bart Van RompaeyAbstract:Understanding software through dynamic analysis has been a popular activity in the past decades. One of the most common approaches in this respect is execution trace analysis: among our own efforts in this context is EXTRAVIS, a tool for the visualization of large traces. Similar to other trace visualization techniques, our tool has been validated through anecdotal evidence, but should also be quantitatively evaluated to assess its usefulness for program comprehension. This paper reports on a first Controlled Experiment concerning 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 21% decrease in time and a 43% increase in correctness for the latter group.
Dror G Feitelson - One of the best experts on this subject based on the ideXlab platform.
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how programmers read regular code a Controlled Experiment using eye tracking
Empirical Software Engineering, 2017Co-Authors: Ahmad Jbara, Dror G FeitelsonAbstract:Regular code, which includes repetitions of the same basic pattern, has been shown to have an effect on code comprehension: a regular function can be just as easy to comprehend as a non-regular one with the same functionality, despite being significantly longer and including more control constructs. It has been speculated that this effect is due to leveraging the understanding of the first instances to ease the understanding of repeated instances of the pattern. To verify and quantify this effect, we use eye tracking to measure the time and effort spent reading and understanding regular code. The Experimental subjects were 18 students and 2 faculty members. The results are that time and effort invested in the initial code segments are indeed much larger than those spent on the later ones, and the decay in effort can be modeled by an exponential model. This shows that syntactic code complexity metrics (such as LOC and MCC) need to be made context-sensitive, e.g. by giving reduced weight to repeated segments according to their place in the sequence. However, it is not the case that repeated code segments are actually read more and more quickly. Rather, initial code segments receive more focus and are looked at more times, while later ones may be only skimmed. Further, a few recurring reading patterns have been identified, which together indicate that in general code reading is far from being purely linear, and exhibits significant variability across Experimental subjects.
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How Programmers Read Regular Code: A Controlled Experiment Using Eye Tracking
2015 IEEE 23rd International Conference on Program Comprehension, 2015Co-Authors: Ahmad Jbara, Dror G FeitelsonAbstract:Regular code, which includes repetitions of the same basic pattern, has been shown to have an effect on code comprehension: a regular function can be just as easy to comprehend as an irregular one with the same functionality, despite being longer and including more control constructs. It has been speculated that this effect is due to leveraging the understanding of the first instances to ease the understanding of repeated instances of the pattern. To verify and quantify this effect, we use eye tracking to measure the time and effort spent reading and understanding regular code. The results are that time and effort invested in the initial code segments are indeed much larger than those spent on the later ones, and the decay in effort can be modeled by an exponential or cubic model. This shows that syntactic code complexity metrics (such as LOC and MCC) need to be made context-sensitive, e.g. By giving reduced weight to repeated segments according to their place in the sequence.
Andy Zaidman - One of the best experts on this subject based on the ideXlab platform.
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a Controlled Experiment for program comprehension through trace visualization
IEEE Transactions on Software Engineering, 2011Co-Authors: B Cornelissen, Andy Zaidman, A Van DeursenAbstract: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 these tasks in terms of time spent and solution correctness. The results are statistically significant in both regards, showing a 22 percent decrease in time requirements and a 43 percent increase in correctness for the group using trace visualization.
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trace visualization for program comprehension a Controlled Experiment
International Conference on Program Comprehension, 2009Co-Authors: B Cornelissen, Andy Zaidman, Arie Van Deursen, Bart Van RompaeyAbstract:Understanding software through dynamic analysis has been a popular activity in the past decades. One of the most common approaches in this respect is execution trace analysis: among our own efforts in this context is EXTRAVIS, a tool for the visualization of large traces. Similar to other trace visualization techniques, our tool has been validated through anecdotal evidence, but should also be quantitatively evaluated to assess its usefulness for program comprehension. This paper reports on a first Controlled Experiment concerning 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 21% decrease in time and a 43% increase in correctness for the latter group.
Arie Van Deursen - One of the best experts on this subject based on the ideXlab platform.
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trace visualization for program comprehension a Controlled Experiment
International Conference on Program Comprehension, 2009Co-Authors: B Cornelissen, Andy Zaidman, Arie Van Deursen, Bart Van RompaeyAbstract:Understanding software through dynamic analysis has been a popular activity in the past decades. One of the most common approaches in this respect is execution trace analysis: among our own efforts in this context is EXTRAVIS, a tool for the visualization of large traces. Similar to other trace visualization techniques, our tool has been validated through anecdotal evidence, but should also be quantitatively evaluated to assess its usefulness for program comprehension. This paper reports on a first Controlled Experiment concerning 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 21% decrease in time and a 43% increase in correctness for the latter group.
