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DEFINING RISK ASSESSMENT CONFIDENCE LEVELS FOR USE IN PROJECT MANAGEMENT COMMUNICATIONS
Title
DEFINING RISK ASSESSMENT CONFIDENCE LEVELS FOR USE IN PROJECT MANAGEMENT COMMUNICATIONS.
Creator
Johnson, Gary, Pet-Armacost, Julia, University of Central Florida
Abstract / Description
A review of the literature regarding risk management and effective risk communications identified that very few researchers have addressed risk assessment confidence levels when using risk scoring methods. The focus of this research is to develop a definition of risk assessment confidence levels for use in internal project management communications and to evaluate its usefulness. This research defines risk assessment confidence level as "The degree of certainty that the likelihood or...
Show moreA review of the literature regarding risk management and effective risk communications identified that very few researchers have addressed risk assessment confidence levels when using risk scoring methods. The focus of this research is to develop a definition of risk assessment confidence levels for use in internal project management communications and to evaluate its usefulness. This research defines risk assessment confidence level as "The degree of certainty that the likelihood or consequence score (assigned by the risk assessor) reflects reality." A specific level of confidence is defined based on the types of analyses that were conducted to determine the risk score. A survey method was used to obtain data from a representative sample of risk assessment professionals from industry and academia to measure their opinion on the usefulness of the defined risk assessment confidence levels. The survey consisted of seven questions related to usefulness--four questions addressed the importance of stating confidence levels in risk assessments and three addressed the usableness of the proposed confidence level. Data were collected on the role and experience level of each of the respondents and the survey also included a comment section to obtain additional feedback. The survey generated 364 respondents representing a broad variety of roles associated with decision making and risk management with experience levels from fairly new to experienced risk assessors. The survey data were analyzed by calculating the proportion of respondents who gave negative, neutral and positive responses to the survey questions. An examination of the roles of the survey respondents indicated that no single group was dominant. A non-parametric Kruskal-Wallis test generally failed to reject the hypothesis that the means of the survey response distributions were identical. There was one exception which indicated that there are differences based on role and by inspection of the responses, it appears that decision makers, academics, and others more strongly support the need for confidence level information to reduce the difficulty in making risk based decisions in projects. The survey responses at a confidence level of 95% have a range of errors from 3.84 to 4.97%. Based on the results of the survey, 77 – 83% of those surveyed indicated agreement that knowing the confidence the assessors have in their assessment is important and would improve a management decision. The survey showed that 60 – 86% of the respondents agreed that the confidence levels and their definitions as presented in the survey were usable. The question with the lowest agreement (60%) was related to the way in which the individual levels were defined. The ad-hoc comments provided in the survey were divided into eleven groups based on similarity of the subject of the comment and then examined for common themes. These added additional insight into the results and useful information for future research efforts. This research validates that the use of risk assessment confidence levels is considered to be useful in project risk management. The research also identified several potential areas for future work, including determining the appropriate number of confidence levels that should be defined, refining the definition of the individual confidence level definitions, examining historical perspectives of whether the risk assessments were accurate, examining the concept of shiftability of risk assessments, further research on communication of variability of risk assessments, and research into the usefulness of risk matrices.
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Date Issued
2008
Identifier
CFE0002352, ucf:47791
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002352
Detecting Semantic Method Clones in Java Code using Method IOE-Behavior
Title
Detecting Semantic Method Clones in Java Code using Method IOE-Behavior.
Creator
Elva, Rochelle, Leavens, Gary, Johnson, Mark, Orooji, Ali, Hughes, Charles, University of Central Florida
Abstract / Description
The determination of semantic equivalence is an undecidable problem; however, this dissertation shows that a reasonable approximation can be obtained using a combination of static and dynamic analysis. This study investigates the detection of functional duplicates, referred to as semantic method clones (SMCs), in Java code. My algorithm extends the input-output notion of observable behavior, used in related work [1, 2], to include the effects of the method. The latter property refers to the...
Show moreThe determination of semantic equivalence is an undecidable problem; however, this dissertation shows that a reasonable approximation can be obtained using a combination of static and dynamic analysis. This study investigates the detection of functional duplicates, referred to as semantic method clones (SMCs), in Java code. My algorithm extends the input-output notion of observable behavior, used in related work [1, 2], to include the effects of the method. The latter property refers to the persistent changes to the heap, brought about by the execution of the method. To differentiate this from the typical input-output behavior used by other researchers, I have coined the term method IOE-Behavior; which means its input-output and effects behavior [3]. Two methods are defined as semantic method clones, if they have identical IOE-Behavior; that is, for the same inputs (actual parameters and initial heap state), they produce the same output (that is result- for non-void methods, and final heap state).The detection process consists of two static pre-filters used to identify candidate clone sets. This is followed by dynamic tests that actually run the candidate methods, to determine semantic equivalence. The first filter groups the methods by type. The second filter refines the output of the first, grouping methods by their effects. This algorithm is implemented in my tool JSCTracker, used to automate the SMC detection process. The algorithm and tool are validated using a case study comprising of 12 open source Java projects, from different application domains and ranging in size from 2 KLOC (thousand lines of code) to 300 KLOC. The objectives of the case study are posed as 4 research questions:1. Can method IOE-Behavior be used in SMC detection?2. What is the impact of the use of the pre-filters on the efficiency of the algorithm?3. How does the performance of method IOE-Behavior compare to using only input-output for identifying SMCs?4. How reliable are the results obtained when method IOE-Behavior is used in SMC detection? Responses to these questions are obtained by checking each software sample with JSCTracker and analyzing the results.The number of SMCs detected range from 0 45 with an average execution time of 8.5 seconds. The use of the two pre-filters reduces the number of methods that reach the dynamic test phase, by an average of 34%. The IOE-Behavior approach takes an average of 0.010 seconds per method while the input-output approach takes an average of 0.015 seconds. The former also identifies an average of 32% false positives, while the SMCs identified using input-output, have an average of 92% false positives. In terms of reliability, the IOE-Behavior method produces results with precision values of an average of 68% and recall value of 76% on average.These reliability values represent an improvement of over 37% (for precision) of the values in related work [4]. Thus, it is my conclusion that IOE-Behavior can be used to detect SMCs in Java code with reasonable reliability.
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Date Issued
2013
Identifier
CFE0004835, ucf:49689
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004835