CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
No task left behind?: examining the nature of fragmented work
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
NavTracks: Supporting Navigation in Software Maintenance
ICSM '05 Proceedings of the 21st IEEE International Conference on Software Maintenance
Easing Program Comprehension by Sharing Navigation Data
VLHCC '05 Proceedings of the 2005 IEEE Symposium on Visual Languages and Human-Centric Computing
Building Usage Contexts During Program Comprehension
ICPC '06 Proceedings of the 14th IEEE International Conference on Program Comprehension
Using task context to improve programmer productivity
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
IEEE Transactions on Software Engineering
Detecting Interaction Coupling from Task Interaction Histories
ICPC '07 Proceedings of the 15th IEEE International Conference on Program Comprehension
Characterizing and Understanding Development Sessions
ICPC '07 Proceedings of the 15th IEEE International Conference on Program Comprehension
A framework for clustering evolving data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Comparing episodic and semantic interfaces for task boundary identification
CASCON '07 Proceedings of the 2007 conference of the center for advanced studies on Collaborative research
Logical Coupling Based on Fine-Grained Change Information
WCRE '08 Proceedings of the 2008 15th Working Conference on Reverse Engineering
Evaluating cues for resuming interrupted programming tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recommending change clusters to support software investigation: an empirical study
Journal of Software Maintenance and Evolution: Research and Practice - Working Conference on Reverse Engineering (WCRE 2008)
A degree-of-knowledge model to capture source code familiarity
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Replaying past changes in multi-developer projects
Proceedings of the Joint ERCIM Workshop on Software Evolution (EVOL) and International Workshop on Principles of Software Evolution (IWPSE)
Addressing Concept-Evolution in Concept-Drifting Data Streams
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Micro interaction metrics for defect prediction
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
The Influence of the Task on Programmer Behaviour
ICPC '11 Proceedings of the 2011 IEEE 19th International Conference on Program Comprehension
SmartGroups: Focusing on Task-Relevant Source Artifacts in IDEs
ICPC '11 Proceedings of the 2011 IEEE 19th International Conference on Program Comprehension
Software Evolution Comprehension: Replay to the Rescue
ICPC '11 Proceedings of the 2011 IEEE 19th International Conference on Program Comprehension
Clustering and recommending collections of code relevant to tasks
ICSM '11 Proceedings of the 2011 27th IEEE International Conference on Software Maintenance
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To guide programmer code navigation, previous approaches such as TeamTracks recommend pieces of code to visit by mining the associations between pieces of code in programmer interaction histories. However, these result in low recommendation accuracy. To create more accurate recommendations, we propose NavClus an approach that clusters navigation sequences from programmer interaction histories. NavClus automatically forms collections of code that are relevant to the tasks performed by programmers, and then retrieves the collections best matched to a programmer's current navigation path. This makes it possible to recommend the collections of code that are relevant to the programmer's given task. We compare NavClus' recommendation accuracy with TeamTracks' by simulating recommendations using 4397 interaction histories. The comparative experiment shows that the recommendation accuracy of NavClus is twice as high as that of TeamTracks.