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Prediction of software maintenance costs.

Morrison, David J (2001) Prediction of software maintenance costs. PhD thesis, Edinburgh Napier University.

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    Abstract/Description

    This thesis is concerned with predicting the costs of maintaining a computer program
    prior to the software being developed. The ubiquitous nature of software means that
    software maintenance is an important activity, and evidence exists to support the
    contention that it is the largest and most costly area of endeavour within the software
    domain. Given the levels of expenditure associated with software maintenance, an
    ability to quantify future costs and address the determinants of these costs can assist in
    the planning and allocation of resources. Despite the importance of this field only a
    limited understanding of the factors that determine future maintenance costs exists,
    and maintenance estimation is more frequently applied to existing software.
    A hypothesis has been postulated that suggests the inherent maintainability of the
    software, the scale of the activity and the degree of change that pertains will
    determine future software maintenance costs. The variables that contribute to the
    maintainability of the software have been explored through a survey of past projects,
    which was undertaken using a questionnaire. This was designed with assistance from
    three separate teams of professional software engineers. The questionnaire requires 69
    numerical or ordinal responses to a series of questions pertaining to characteristics
    including program structure, computer architecture, software development
    methodology, project management processes and maintenance outcomes.
    Factor analysis methods were applied and five of the most powerful predictors are
    identified. A linear model capable of predicting maintainability has been developed.
    Validation was undertaken through a series of follow-up interviews with several
    survey respondents, and by further statistical analysis utilising hold-out samples and
    structural equation modelling. The model was subsequently used to develop
    predictive tools intended to provide management support by both providing a
    categorical assessment of future maintainability, and a quantitative estimate of
    probable maintenance costs. The distinction between essential corrective
    maintenance, and other elective forms of maintenance is considered.
    Conclusions are drawn regarding the efficacy and limitations of tools that can be
    developedt o supportm anagemendt ecisionm aking. Subjectt o further work with a
    largers ampleo f projects,p referablyf rom within a singleo rganisationi,t is concluded
    i
    that useful tools could be developed to make both categorical ('acceptable' versus
    'not acceptable') and static (initial) quantitative predictions. The latter is dependent on
    the availability of a software development estimate. Some useful predictive methods
    have also been applied to dynamic (continuing) quantitative prediction in
    circumstances where a trend develops in successive forecasts.
    Recommendationfosr furtherw ork arep rovided.T hesei nclude:
    U Factor analysis and linear regression has been applied to a sample of past software
    projects from a variety of application areas to identify important input variables
    for use in a maintainability prediction model. Maintainability is regarded as an
    important determinant of maintenance resource requirements. The performance of
    these variables within a single organisation should be confirmed by undertaking a
    further factor analysis and linear regression on projects from within the target
    organisation.
    u The robustness of model design within this target organisation should be
    considered by applying a sensitivity analysis to the input variables.
    u This single organisation maintainability predictor model design should be
    validated by confirmatory interviews with specialists and users from within the
    target organisation.
    u Aggregate scale has been identified as another predictor of overall maintenance
    resource requirements, and the relationship between development and
    maintenance effort explored for the general case. It is desirable that development
    and corrective maintenance scale relationships should be explored within a single
    organisation. Within this environment the association between standardised effort
    and maintainability should be confirmed, and the value of the logistic model as a
    descriptor of the relationship verified.
    u The approacht o quantifying non-correctivem aintenanceth at has been outlined
    requiresf iirther developmentT. he relationshipb etweena nnualc hanget raffic and
    maintenancec ostss houldb e modelled,a ssuminga prior knowledgeo f the scale
    and maintainability determinants.
    uA sensitivity analysis should be applied to the predictive system that has been
    developed, recognising the potential for error in the values of the input variables
    that may pertain.
    uA goal of this further research should be the development of a suite of soft tools,
    designed to enable the user to develop a software maintenance estimation system.

    Item Type: Thesis (PhD)
    Additional Information: I would like to acknowledge the help and assistance of the following people: Dr Robert Raeside, Department of Mathematics, Napier University u Michelle Ledgard, 600 Lathes u Kathleen O'Connell, Ellison Machine Tool & Robotics Company
    Uncontrolled Keywords: software maintenance; financial expenditure; resources;
    University Divisions/Research Centres: The Business School > School of Accounting, Economics and Statistics
    Dewey Decimal Subjects: 500 Science > 510 Mathematics > 519 Probabilities & applied mathematics
    000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science > 004.2 Systems analysis, design & performance
    600 Technology > 650 Management & public relations > 658 General management
    Library of Congress Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
    Q Science > QA Mathematics > QA76 Computer software
    Item ID: 3601
    Depositing User: Mrs Lyn Gibson
    Date Deposited: 05 Feb 2010 15:15
    Last Modified: 12 Jan 2011 04:54
    URI: http://researchrepository.napier.ac.uk/id/eprint/3601

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