25,698 research outputs found
Using Counts as Heuristics for the Analysis of Static Models
The upstream activities of software development are often viewed as both the most
important, in terms of cost, and the yet the least understood, and most problematic, particularly in terms of satisfying customer requirements. Business process modelling is
one solution that is being increasingly used in conjunction with traditional software
development, often feeding in to requirements and analysis activities. In addition,
research in Systems Engineering for Business Process Change, highlights the importance
of modelling business processes in evolving and maintaining the legacy systems that
support those processes. However, the major use of business process modelling, is to
attempt to restructure the business process, in order to improve some given aspect, e.g.,
cost or time. This restructuring may be seen either as separate activity or as a pre-cursor
to the development of systems to support the new or improved process. Hence, the
analysis of these business models is vital to the improvement of the process, and as a
consequence to the development of supporting software systems. Supporting this analysis
is the focus of this paper.
Business processes are typically described with static (diagrammatic) models. This paper
proposes the use of measures (counts) to aid analysis and comparison of these static
process descriptions. The proposition is illustrated by showing how measures can be
applied to a commonly used process-modelling notation, Role Activity Diagrams (RADs).
Heuristics for RADs are described and measures suggested which support those
heuristics. An example process is used to show how a coupling measure can be used to
highlight features in RADs useful to the process modeller.
To fully illustrate the proposition the paper describes and applies a framework for the
theoretical validation of the coupling measure. An empirical evaluation follows. This is
illustrated by two case studies; the first based on the bidding process of a large
telecommunications systems supplier, and the second a study of ten prototyping processes
across a number of organisations.
These studies found that roles of the same type exhibited similar levels of coupling across
processes. Where roles did not adhere to tentative threshold values, further investigation
revealed unusual circumstances or hidden behaviour. Notably, study of the prototyping
roles, which exhibited the greatest variation in coupling, found that coupling was highly
correlated with the size of the development team. This suggests that prototyping in large
projects had a different process to that for small projects, using more mechanisms for
communication. Hence, the empirical studies support the view that counts (measures)
may be useful in the analysis of static process models
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Project Controls and Management Systems : current practice and how it has changed over the past decade
Project Controls and Management System (PCMS) refers to an ecosystem of processes, tools and personnel required for the proper planning and execution of capital projects throughout the different phases of design, procurement, construction and startup. This can be divided into different focus areas (functions) that would include Estimating, Planning, Scheduling, Cost Control, Change Management, Progressing, and Forecasting. Various trends such as globalization, contractor specialization and information technology developments have impacted the way PCMS are implemented and made it the subject of extensive research over the past years to investigate how to best utilize those trends. Replicating the research methodology used in a 2011 report published by the Construction Research Institute (CII), this work aims to investigate the current status of PCMS implementation and how it has changed over the past decade. It was concluded that while the original PCMS principles are still valid, adoption has drastically changed in terms of efficiency for the majority of the functions. The research also identifies areas of potential concerns and provides recommendations for further improvement.Civil, Architectural, and Environmental Engineerin
Feature Type Analysis in Automated Genre Classification
In this paper, we compare classifiers based on language model, image, and stylistic features for automated genre classification. The majority of previous studies in genre classification have created models based on an amalgamated representation of a document using a multitude of features. In these models, the inseparable roles of different features make it difficult to determine a means of improving the classifier when it exhibits poor performance in detecting selected genres. By independently modeling and comparing classifiers based on features belonging to three types, describing visual, stylistic, and topical properties, we demonstrate that different genres have distinctive feature strengths.
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