Understanding factors contributing to the escalation of software maintenance costs

Research output: Chapter in Book/Entry/PoemConference contribution

1 Scopus citations

Abstract

We examine the main drivers of software maintenance effort and cost. We use the 'Distributed Cognition' framework to hypothesize about how 'discovery work' in maintenance is effected by two types of cost drivers: system attributes (size, complexity, age, etc.) and personnel attributes (number of maintainers, location dispersion, etc.). We test our hypotheses using archival data about over 5,000 maintenance projects carried out between 2009 and 2011 on 412 different operational systems in a large financial institution. We find that personnel attributes are significantly more influential than system attributes. In particular, a marginal change in personnel factors is associated with effort growing much faster than cost, indicating an escalating marginal cost of spreading maintenance work across more maintainers and site locations. We also find, counter to expectation, that two system attributes are negatively linked to maintenance effort and cost. Implications of these findings for research and practices are discussed.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems (ICIS 2013)
Subtitle of host publicationReshaping Society Through Information Systems Design
Pages3125-3139
Number of pages15
StatePublished - 2013
EventInternational Conference on Information Systems, ICIS 2013 - Milan, Italy
Duration: Dec 15 2013Dec 18 2013

Publication series

NameInternational Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design
Volume4

Other

OtherInternational Conference on Information Systems, ICIS 2013
Country/TerritoryItaly
CityMilan
Period12/15/1312/18/13

Keywords

  • Cost drivers
  • Discovery work
  • Distributed cognition
  • Personnel attributes
  • Software maintenance
  • System attributes

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Library and Information Sciences

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