Assessing the adequacy of documentation through document quality indicators

Arthur, James D.; Stevens, K. T

doi:10.1109/icsm.1989.65192

Cited by 24 publications

(10 citation statements)

References 5 publications

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“…Documentation quality on the literature review refers to the documentation accompanying a software development [3], whereas the indicator Doc in our model reflects one side of procedures quality. This indicator is staggered from -compliant‖ when all the quality attributes exist to -non-existent‖ where they are all absent (Table III).…”

Section: ) Procedures Quality (Prq) A) Documentation (Doc)mentioning

confidence: 99%

Information System Quality: Managers Perspective

Aouhassi¹,

Hanoune²

2018

ijacsa

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Section: ) Procedures Quality (Prq) A) Documentation (Doc)mentioning

confidence: 99%

Information System Quality: Managers Perspective

Aouhassi¹,

Hanoune²

2018

ijacsa

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“…Nasution and Weistroffer [19] lay down that, a well planned and documented systems development project is more likely to result in a system that meets the expectations of both the intended users and the software engineers. Arthur and Stevens [1] projected that, the investigation focuses on assessing the adequacy of project documentation based on an identified taxonomic structure relating documentation characteristics. Chomal and Saini [5] in their work stated that, if requirements are not properly specified, analyzed and properly documented, then it will lead to software as a failure.…”

Section: Related Literature Reviewmentioning

confidence: 99%

Software Template for Evaluating and Scoring Software Project Documentations

Chomal¹,

Saini²

2015

IJCA

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Significant documentation is been formed with almost all software projects, irrespective of application. Software project documentation is a perspective whose purpose is to communicate information about the software system. For research purpose documentations of final year students of Masters level course have been considered for the research purpose. These documentations consist of the artefacts like requirement analysis, technical environment, database design, structural and object oriented modelling techniques, screen layouts and testing techniques along with test case and data. The results were compiled from 505 large software project documentations developed during a period of academic years from 2001-2002 to 2011-2012. The duration of these software projects was six months. Errors from these software project documentations were found and these errors were classified into 11 broad error categories. After compilation of results and studying various artefacts in software project documentations 103 software attributes were recognized. These software attributes were classified into two broad classes (a) Quantifiable attributes and (b) Non-quantifiable attributes. Out of 103 software attributes, 39 were quantifiable attributes and 64 non-quantifiable attributes. Subsequent to categorization, weights were assigned to these quantifiable software attributes only for which a survey was conducted. The basic goal of assigning weights to these quantifiable attributes was to score software project documentation. Further, software template is been proposed for evaluating and scoring student"s software projects documentation.

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“…Sufficiency means the extent to which the documentation provides enough information about the data so that users do not need to seek information about the data from other channels. One indicator for sufficiency is completeness, which is adapted from the Document Quality Indicators (DQI) for software documentation (Arthur and Stevens, 1989). Completeness in DQI means all the required components are present in the software documentation.…”

Section: Documentation Evaluation Model (Dem) For Social Science Datamentioning

confidence: 99%

Documentation evaluation model for social science data

Niu

Hedstrom

2008

Proc of Assoc for Info

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Information technology and data sharing policies have made more and more social science data available for secondary analysis. In secondary data analysis, documentation plays a critical role in transferring knowledge about data from data producers to secondary users. Despite its importance, documentation of social science data has rarely been the focus of existing studies. In this paper, based on an introduction of the concept of documentation and its role in secondary data analysis, the authors proposed the Documentation Evaluation Model(DEM) for social science data. In the model, two indicators are used to evaluate the documentation for social science data: sufficiency and ease-of-use. Then the authors review the sufficiency problems of documentation, identify three factors that affect the sufficiency of documentation: users, data, and the ease-of-use of documentation, and formulate hypotheses about how those factors affect the sufficiency of documentation. In future research, a survey instrument will be created based on the model and the factors affecting the sufficiency of documentation. The survey instrument will then be applied to the secondary users of social science data. Hypotheses will be tested based on the survey data.

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Assessing the adequacy of documentation through document quality indicators

Cited by 24 publications

References 5 publications

Information System Quality: Managers Perspective

Information System Quality: Managers Perspective

Software Template for Evaluating and Scoring Software Project Documentations

Documentation evaluation model for social science data

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