Cassandra: proactive conflict minimization through optimized task scheduling

Software conflicts arising because of conflicting changes are a regular occurrence and delay projects. The main precept of workspace awareness tools has been to identify potential conflicts early, while changes are still small and easier to resolve. However, in this approach conflicts still occur an...

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Vydáno v:Proceedings of the 2013 International Conference on Software Engineering s. 732 - 741
Hlavní autoři: Kasi, Bakhtiar Khan, Sarma, Anita
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Piscataway, NJ, USA IEEE Press 18.05.2013
Edice:ACM Conferences
Témata:
Software and its engineering > Software creation and management > Designing software > Software implementation planning > Software design techniques
Software and its engineering > Software creation and management > Software development process management
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Scheduling algorithms
Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms > Scheduling algorithms
Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning > Sequential decision making
ISBN:1467330760, 9781467330763
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Shrnutí:Software conflicts arising because of conflicting changes are a regular occurrence and delay projects. The main precept of workspace awareness tools has been to identify potential conflicts early, while changes are still small and easier to resolve. However, in this approach conflicts still occur and require developer time and effort to resolve. We present a novel conflict minimization technique that proactively identifies potential conflicts, encodes them as constraints, and solves the constraint space to recommend a set of conflict-minimal development paths for the team. Here we present a study of four open source projects to characterize the distribution of conflicts and their resolution efforts. We then explain our conflict minimization technique and the design and implementation of this technique in our prototype, Cassandra. We show that Cassandra would have successfully avoided a majority of conflicts in the four open source test subjects. We demonstrate the efficiency of our approach by applying the technique to a simulated set of scenarios with higher than normal incidence of conflicts.
ISBN:1467330760
9781467330763
DOI:10.5555/2486788.2486884