TY - GEN
T1 - A TraceLab-based solution for creating, conducting, and sharing feature location experiments
AU - Dit, Bogdan
AU - Moritz, Evan
AU - Poshyvanyk, Denys
PY - 2012
Y1 - 2012
N2 - Similarly to other fields in software engineering, the results of case studies involving feature location techniques (FLTs) are hard to reproduce, compare, and generalize, due to factors such as, incompatibility of different datasets, lack of publicly available implementation or implementation details, or the use of different metrics for evaluating FLTs. To address these issues, we propose a solution for creating, conducting, and sharing experiments in feature location based on TraceLab, a framework for conducting research. We argue that this solution would allow rapid advancements in feature location research because it will enable researchers to create new FLTs in the form of TraceLab templates or components, and compare them with existing ones using the same datasets and the same metrics. In addition, it will also allow sharing these FLTs and experiments within the research community. Our proposed solution provides (i) templates and components for creating new FLTs and instantiating existing ones, (ii) datasets that can be used as inputs for these FLTs, and (iii) metrics for comparing these FLTs. The proposed solution can be easily extended with new FLTs (in the form of easily configurable templates and components), datasets, and metrics.
AB - Similarly to other fields in software engineering, the results of case studies involving feature location techniques (FLTs) are hard to reproduce, compare, and generalize, due to factors such as, incompatibility of different datasets, lack of publicly available implementation or implementation details, or the use of different metrics for evaluating FLTs. To address these issues, we propose a solution for creating, conducting, and sharing experiments in feature location based on TraceLab, a framework for conducting research. We argue that this solution would allow rapid advancements in feature location research because it will enable researchers to create new FLTs in the form of TraceLab templates or components, and compare them with existing ones using the same datasets and the same metrics. In addition, it will also allow sharing these FLTs and experiments within the research community. Our proposed solution provides (i) templates and components for creating new FLTs and instantiating existing ones, (ii) datasets that can be used as inputs for these FLTs, and (iii) metrics for comparing these FLTs. The proposed solution can be easily extended with new FLTs (in the form of easily configurable templates and components), datasets, and metrics.
KW - benchmarks
KW - experiments
KW - feature location
KW - TraceLab
UR - http://www.scopus.com/inward/record.url?scp=84865013293&partnerID=8YFLogxK
U2 - 10.1109/icpc.2012.6240489
DO - 10.1109/icpc.2012.6240489
M3 - Conference contribution
AN - SCOPUS:84865013293
SN - 9781467312165
T3 - IEEE International Conference on Program Comprehension
SP - 203
EP - 208
BT - 2012 20th IEEE International Conference on Program Comprehension, ICPC 2012 - Proceedings
PB - IEEE Computer Society
T2 - 2012 20th IEEE International Conference on Program Comprehension, ICPC 2012
Y2 - 11 June 2012 through 13 June 2012
ER -