Knowledge management in different software development approaches

Broderick Crawford, Carlos Castro, Eric Monfroy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations


In this paper we present some ideas, concepts and experiences related with our work of implementing solvers to combinatorial optimization problems. We have been designing, implementing and using solvers for important kind of problems, and painfully, the process of developing them is not optimal at all. The most used practice, which is based on trial and error, often incurs an enormous amount of resources. Clearly, this is a Software Engineering problem, then to find better ways of developing optimization algorithms, solvers and metaheuristics is our interest too. The software development community has a wide spectrum of methodologies when it decides to implement a software project. From the more traditional Tayloristic practices to Agile methods. Software development is a knowledge intensive activity and the knowledge creation and sharing are crucial parts of the software development processes. This paper presents a comparative analysis between knowledge sharing approaches of Agile and Tayloristic software development teams sprinkled with concerns about the development of Metaheuristics.

Original languageEnglish
Title of host publicationAdvances in Information Systems - 4th International Conference, ADVIS 2006, Proceedings
PublisherSpringer Verlag
Number of pages10
ISBN (Print)3540462910, 9783540462910
StatePublished - 2006
Event4th International Conference on Advances in Information Systems, ADVIS 2006 - Izmir, Turkey
Duration: 18 Oct 200620 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4243 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Advances in Information Systems, ADVIS 2006


  • Agile development
  • Knowledge management
  • Knowledge sharing
  • Metaheuristics
  • Optimization algorithms
  • Reusability


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