Cocomo II as productivity measurement: a case study at KBC.

Software productivity is generally measured as the ratio of size over effort, whereby several techniques exist to measure the size. In this paper, we propose the innovative approach to use an estimation model as productivity measurement. This approach is applied in a case-study at the ICT-department of a bank and insurance company. The estimation model, in this case Cocomo II, is used as the norm to judge about productivity of application development projects. This research report describes on the one hand the set-up process of the measurement environment and on the other hand the measurement results. To gain insight in the measurement data, we developed a report which makes it possible to identify productivity improvement areas in the development process of the case-study company.

A New Calibration for Function Point Complexity Weights

Function Point (FP) is a useful software metric that was first proposed twenty-five years ago, since then, it has steadily evolved into a functional size metric consolidated in the well-accepted Standardized International Function Point Users Group (IFPUG) Counting Practices Manual - version 4.2. While software development industry has grown rapidly, the weight values assigned to count standard FP still remain same, which raise critical questions about the validity of the weight values. In this paper, we discuss the concepts of calibrating Function Point, whose aims are to estimate a more accurate software size that fits for specific software application, to reflect software industry trend, and to improve the cost estimation of software projects. A FP calibration model called Neuro-Fuzzy Function Point Calibration Model (NFFPCM) that integrates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic is proposed. The empirical validation using International Software Benchmarking Standards Group (ISBSG) data repository release 8 shows a 22% accuracy improvement of mean MRE in software effort estimation after calibration

DEMAND-RESPONSIVE AIRSPACE SECTORIZATION AND AIR TRAFFIC CONTROLLER STAFFING

This dissertation optimizes the problem of designing sector boundaries and assigning air traffic controllers to sectors while considering demand variation over time. For long-term planning purposes, an optimization problem of clean-sheet sectorization is defined to generate a set of sector boundaries that accommodates traffic variation across the planning horizon while minimizing staffing. The resulting boundaries should best accommodate traffic over space and time and be the most efficient in terms of controller shifts. Two integer program formulations are proposed to address the defined problem, and their equivalency is proven. The performance of both formulations is examined with randomly generated numerical examples. Then, a real-world application confirms that the proposed model can save 10%-16% controller-hours, depending on the degree of demand variation over time, in comparison with the sectorization model with a strategy that does not take demand variation into account. Due to the size of realistic sectorization problems, a heuristic based on mathematical programming is developed for a large-scale neighborhood search and implemented in a parallel computing framework in order to obtain quality solutions within time limits. The impact of neighborhood definition and initial solution on heuristic performance has been examined. Numerical results show that the heuristic and the proposed neighborhood selection schemes can find significant improvements beyond the best solutions that are found exclusively from the Mixed Integer Program solver's global search. For operational purposes, under given sector boundaries, an optimization model is proposed to create an operational plan for dynamically combining or splitting sectors and determining controller staffing. In particular, the relation between traffic condition and the staffing decisions is no longer treated as a deterministic, step-wise function but a probabilistic, nonlinear one. Ordinal regression analysis is applied to estimate a set of sector-specific models for predicting sector staffing decisions. The statistical results are then incorporated into the proposed sector combination model. With realistic traffic and staffing data, the proposed model demonstrates the potential saving in controller staffing achievable by optimizing the combination schemes, depending on how freely sectors can combine and split. To address concerns about workload increases resulting from frequent changes of sector combinations, the proposed model is then expanded to a time-dependent one by including a minimum duration of a sector combination scheme. Numerical examples suggest there is a strong tradeoff between combination stability and controller staffing

Parenting Assessment Manual Software within Forensic Parenting Assessments: A Descriptive Study of Application and Perceived Value

Decisions being made within care proceedings can result in potentially life altering outcomes for families whereby children can be separated from their carers and placed for adoption. Judges and magistrates utilising forensic parenting assessments (FPAs) to help make these decisions need to be able to rely on consistently good practices to inform them; however, there are indications that the quality of FPAs can vary with many not meeting forensic guidelines. This study is about Parenting Assessment Manual Software (PAMS) which is a standardised parenting assessment package that can be incorporated into FPAs. It has established a presence in FPAs despite very limited research on its use or value. This mixed methods project administered an online survey (n=54) and telephone interviews (n=11) to practitioners who have incorporated PAMS into their FPAs in order to explore the process and value in doing so. This study found variations in how PAMS was being incorporated into FPAs resulting in the identification of 3 different ways in which PAMS was used; PAMS Informed, Full PAMS and PAMS Plus FPAs. It has also found a full continuum of practitioner opinion on the use of PAMS within FPAs; although most participants preferred to use PAMS than not. Finally, results indicate that there are minimal differences in a PAMS versus a non-PAMS FPA; however, certain types of FPAs using PAMS require the application of better practice guidelines, may take longer than non-PAMS counterparts and possibly include more parent-child observations. This study provides recommendations regarding the implementation of PAMS when it is incorporated into an FPA and develops knowledge around the use of PAMS within FPAs for the consideration of social workers, legal professionals, health practitioners, family support workers and any other interested parties

Slava Ukraini: a psychobiographical case study of Volodymyr Zelenskyy’s public diplomacy discourse

Volodymyr Zelenskyy\u27s public diplomacy during the Russo-Ukrainian conflict was examined in this dissertation. Zelenskyy’s discourse emphasized his action-oriented traits, Ukrainian identity, and nationalism. The study employed LTA, and LIWC-22, for natural language processing analyses of Zelenskyy\u27s public speeches and diplomatic discourse. Zelenskyy demonstrated agency, adaptability, collaboration, and positive language patterns, suggesting confidence and optimism, according to the data. In addition, the research emphasizes how domestic and international factors influence state behavior, as well as how political demands, cultural, historical, and political factors influence Zelenskyy\u27s decision-making. This dissertation sheds light on a global leader\u27s psychobiographical characteristics, beliefs, and motivations during a crisis, thereby advancing leadership and conflict resolution. By incorporating transformational leadership theory into LTA, researchers can gain a better understanding of effective leadership and how it develops strong connections with followers. LTA, LIWC-22, and qualitative coding were used to identify themes and trends in Zelenskyy\u27s speeches. The findings show Zelenskyy\u27s linguistic and leadership traits in public diplomacy, emphasizing the importance of understanding leaders\u27 traits in foreign policy decision-making. Psychobiographical profiles aid scholars in understanding a leader\u27s political views on conflict, their ability to influence events, and how they accomplish their objectives. As a result, perceptions of the state as an actor, as well as foreign policy decisions, must consider the effect of individual leaders. Conclusions include the Brittain-Hale Foreign Policy Analysis Model, based on a heuristic qualitative coding framework; HISTORICAL

Symmetric and Asymmetric Data in Solution Models

This book is a Printed Edition of the Special Issue that covers research on symmetric and asymmetric data that occur in real-life problems. We invited authors to submit their theoretical or experimental research to present engineering and economic problem solution models that deal with symmetry or asymmetry of different data types. The Special Issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, seventeen papers were accepted and published. The authors proposed different solution models, mainly covering uncertain data in multicriteria decision-making (MCDM) problems as complex tools to balance the symmetry between goals, risks, and constraints to cope with the complicated problems in engineering or management. Therefore, we invite researchers interested in the topics to read the papers provided in the book