Maximum Commonality Problems: Applications and Analysis

Recently, an agile software development technique called extreme programming has caught the attention of practitioners and researchers in the software industry. A core practice of extreme programming is pair programming , where two developers work on the same piece of code. We introduce the problem...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Management science Jg. 54; H. 1; S. 194 - 207
Hauptverfasser: Dawande, Milind, Kumar, Subodha, Mookerjee, Vijay, Sriskandarajah, Chelliah
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Linthicum, MD INFORMS 01.01.2008
Institute for Operations Research and the Management Sciences
Schriftenreihe:Management Science
Schlagworte:
Algorithmics. Computability. Computer arithmetics
Algorithms
analysis of algorithms
applications
Applied sciences
Approximation
Business studies
Cardinality
Computational complexity
Computer programming
Computer science; control theory; systems
Computer software
Computer systems and distributed systems. User interface
Exact sciences and technology
Graphs
Innovation
Integer programming
Integers
Management science
Personnel management
Programming
Social aspects
Software
Software engineering
Software industry
Studies
suboptimal algorithms
Systems development
Theoretical computing
Trees
Variants
Writers
Zero
United States
Tree(graph)
Software development
analysis of algorithms
Polynomial approximation
Duration
Graph theory
Polynomial method
Approximation algorithm
Extreme programming
Computational complexity
Polynomial time
Integer programming
suboptimal algorithms
Extreme value
Dissemination
NP complete problem
Agile programming
Load balancing
Algorithm analysis
Completion time
Execution time
applications
ISSN:0025-1909, 1526-5501
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Recently, an agile software development technique called extreme programming has caught the attention of practitioners and researchers in the software industry. A core practice of extreme programming is pair programming , where two developers work on the same piece of code. We introduce the problem of assigning pairs of developers to modules so as to maximize the commonality—a measure of the extent to which common developers work on related modules—subject to a load-balancing constraint that is motivated by the need to control the completion time of the project. We consider two variants of this problem. In MCAP n , a developer is teamed up with exactly one other developer to form a pair that works together for the entire duration of the project. In MCAP s , we allow a developer to pair with more than one other developer during the project. This "pair-splitting" version of the problem facilitates knowledge dissemination among developers, but can increase the effort needed for a developer to adjust to the work habits of several partners. The difference between the commonality achieved with and without pair splitting crucially depends on the underlying structure of the problem. For trees, we show that the value of the maximum commonality is the same for both MCAP n and MCAP s . Additionally, we obtain polynomial-time algorithms for both of these variants. For general graphs, both problems MCAP n and MCAP s are shown to be strongly NP-complete. We prove that the maximum commonality for MCAP s is at most 3/2 times the maximum commonality of MCAP n . We also provide polynomial-time algorithms and approximation results for a number of special cases of these problems.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0025-1909
1526-5501
DOI:10.1287/mnsc.1070.0766