Error Categorizing
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institution loginHelpJournalsBooksRegisterJournalsBooksRegisterSign inHelpcloseSign in using your ScienceDirect credentialsUsernamePasswordRemember meForgotten username or password?Sign in via your institutionOpenAthens loginOther institution login Purchase Loading... Export You have category a medication error selected 1 citation for export. Help Direct export Save to ncc merp medication error definition Mendeley Save to RefWorks Export file Format RIS (for EndNote, ReferenceManager, ProCite) BibTeX Text Content ismp medication error classification Citation Only Citation and Abstract Export Advanced search Close This document does not have an outline. JavaScript is disabled on your browser. Please enable JavaScript to medication error index categories use all the features on this page. Journal of Systems and Software Volume 4, Issue 4, November 1984, Pages 289-300 Collecting and categorizing software error data in an industrial environment ☆ Author links open the overlay panel. Numbers correspond to the affiliation list which can be exposed by using the show
Ismp Medication Error Categories
more link. Opens overlay Thomas J. Ostrand ∗∗ Sperry Univac USA Opens overlay Elaine J. Weyuker ∗ Courant Institute of Mathematical Sciences, New York University USA Available online 10 June 2003 Show more Choose an option to locate/access this article: Check if you have access through your login credentials or your institution. Check access Purchase Sign in using your ScienceDirect credentials Username: Password: Remember me Not Registered? Forgotten username or password? OpenAthens login Login via your institution Other institution login doi:10.1016/0164-1212(84)90028-1 Get rights and content AbstractA study has been made of the software errors committed during development of an interactive special-purpose editor system. This product, developed for commercial production use, has been followed during nine months of coding, unit testing, function testing, and system testing. Detected problems and their fixes have been described by testers and debuggers. A new fault categorization scheme was developed from these descriptions and used to classif
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Medication Error Severity Scale
Related fields and sub-fields Bibliometrics· Categorization Censorship· Classification Computer data ncc merp taxonomy of medication errors storage· Cultural studies Data modeling· Informatics Information technology Intellectual freedom Intellectual property· Memory Library and different types of medication errors information science Preservation· Privacy Quantum information science Information science portal v t e Categorization is the process in which ideas and objects are recognized, differentiated, http://www.sciencedirect.com/science/article/pii/0164121284900281 and understood.[1] Categorization implies that objects are grouped into categories, usually for some specific purpose. Ideally, a category illuminates a relationship between the subjects and objects of knowledge. Categorization is fundamental in language, prediction, inference, decision making and in all kinds of environmental interaction. It is indicated that categorization plays https://en.wikipedia.org/wiki/Categorization a major role in computer programming.[2] There are many categorization theories and techniques. In a broader historical view, however, three general approaches to categorization may be identified: Classical categorization Conceptual clustering Prototype theory Contents 1 The classical view 2 Conceptual clustering 3 Prototype theory 4 Miscategorization 5 See also 6 References 7 External links The classical view[edit] Main article: Categories (Aristotle) Classical categorization first appears in the context of Western Philosophy in the work of Plato, who, in his Statesman dialogue, introduces the approach of grouping objects based on their similar properties. This approach was further explored and systematized by Aristotle in his Categories treatise, where he analyzes the differences between classes and objects. Aristotle also applied intensively the classical categorization scheme in his approach to the classification of living beings (which uses the technique of applying successive narrowing questions such as "Is it an animal or vegetable?",
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Maintainability Rating" Research Findings Publications Authors Defect Indicators Work In Progress Structured Programming Single Point of Maintenance Defensive Programming Causes for Concern About IfSQ... Contact The World and IfSQ Site Map Research Findings Relevant to the IfSQ Standards Papers, Presentations and Books Journal Paper: Collecting and Categorizing Software Error Data in an Industrial Environment Thomas J. Ostrand, and Elaine J. Weyuker Recorded 1984 in Journal of Systems and Software, 4, no. 4, November Pages 289-300 Abstract:A study has been made of the software errors committed during development of an interactive special-purpose editor system. This product, developed for commercial production use, has been followed during nine months of coding, unit testing, function testing, and system testing. Detected problems and their fixes have been described by testers and debuggers. A new fault categorization scheme was developed from these descriptions and used to classify the 173 faults that resulted from the project's errors. For each error, we asked the programmers to select its most likely cause, report the stages of the software development cycle in which the error was committed and the problem first noticed, and the circumstances of the problem's detection and isolation, including time required, techniques tried, and successful techniques. The results collected in this study are compared to results from earlier studies, and similarities and differences are noted. Link: Collecting and Categorizing Software Error Data in an Industrial Environment Finding relevant to IfSQ Standards: About 85% of errors can be fixed in a few hours if caught in the development stage More Publications: A An Analysis of Some Commercial PL/1 Programs Analyzing Error-Prone System Structure Applied Software Measurement: Assuring Productivity and Quality Software Assessments, Benchmarks, and Best Practices B - Col Balancing Agility and Discipline: A Guide for the Perplexed Calculating the Return on Investment from More Effective Requirements Management Code Complete Collecting and Categorizing Software Error Data in an Industrial Environment Com - Def Comparing The Effectiveness of Software Testing Strategies A Complexity Measure Debugging Effort Estimation using Software Metrics Software Defect Prevention Using McCabe's Complexity Metric Software Defect Removal Efficiency Des - Ec Design and Code Inspections to Reduce Errors in Program Development Document Inspection as an Agent of Change An Economic Release Decision Model: Insights into Software Project Management Em - Es An Empirical Stu