XPLanner: A knowledge-based decision support system for facility management and planning

Han, S-Y; Kim, T J; Adiguzel, Ilker

doi:10.1068/b180205

Cited by 6 publications

(3 citation statements)

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“…Because of this staff heterogeneity, instead of migrating to uniform processes for creating the artifacts with highly integrated tools like VersionOne [9] or Mingle [10], which, natively, offer solid traceability support among the artifacts created within the tools, people want to stick to the tools they are used to (e.g. detailed requirements specification using text editors like Microsoft Word and Open Office; Enterprise Architect [11], Rational Software Architecture [12] for designing the architecture; Rally [13], XPlanner [14] for managing agile artifacts like User Stories, Sprints, task allocation, etc). This scenario offers the basis for motivating the challenge we address in this work, which is to guarantee noninvasive traceability: ensuring artifacts traceability without drastic changes in the manner that people create the development artifacts.…”

Section: Introductionmentioning

confidence: 99%

A Non-invasive Approach to Trace Architecture Design, Requirements Specification and Agile Artifacts

Antonino

Keuler

Germann

et al. 2014

2014 23rd Australian Software Engineering Conference

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Agile processes emphasize iterative delivery rather than assuming the definition of all detailed requirements and architecture up front. This "just enough" approach generally considers user stories and acceptance tests as sufficient documentation for successful system development. However, industry practices have shown that this minimalism is appropriate for projects with short duration and small co-located teams. In the development of large systems, the "just enough" documentation goes beyond the traditional set recommended by the Agile evangelists, due to the diversity of elements to be considered, as for instance geographic distribution of the teams, necessity to comply with industry regulations, strict IT governance programs, integration of the system being developed with others, or even the presence of not-so-agile people in the teams. In this context,a more complex set of artifacts is required to ensure the proper development of systems, such as more detailed requirements documents and architectural specification. In this regard, to support the agile development of large systems, we introduce TraceMan -Traceability Manager as a mechanism for ensuring traceability among user stories, traditional requirements documents, test specifications, architecture design, and source code. We also present an experience report on how TraceMan has been used in the daily activities at John Deere Intelligent Solutions Group (ISG) to support traceability among development artifacts.

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Section: Introductionmentioning

confidence: 99%

A Non-invasive Approach to Trace Architecture Design, Requirements Specification and Agile Artifacts

Antonino

Keuler

Germann

et al. 2014

2014 23rd Australian Software Engineering Conference

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“…If one is keen enough to further the art and science of one's own field, anything is worth a try. Hence several articles have been published in Environment and Planning B on the application of expert systems to environmental planning, for example, those by Borri et al (1994), Han et al (1991), Leary (1988), and Davis and Grant (1987). But sure enough, the more successful applications have tended to be in the less ambiguous, more procedurally exact areas of planning, such as interpretation of planning legislation and identification of what is possible under a set of building regulations.…”

Section: Revivalmentioning

confidence: 99%

Guest Editorial

Wyatt¹

1996

Environ Plann B Plann Des

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Transcending the retreat from rationalityOne of the aims of this issue is to provide something for planning practitioners. Unlike their academic cousins, planning practitioners have seldom had the luxury of 'retreating from rationality'. They have always had a job to do, rationally; in this job they were once comprehensively assisted by researchers into computer-aided planning techniques. Yet the intensity of academia's retreat from rationality and the popularity of its rejection of 'rational comprehensiveness' have tended to inhibit such assistance for at least two decades.Recently, however, there have been signs of a regrouping. New forms of 'organic' computing have emerged and their application to planning problems has been widespread. They therefore have the potential to restore academia's technical assistance back to something like the levels enjoyed by practitioners during the 1950s and 1960s. Accordingly, although it hardly proclaims that a second quantitative revolution is almost at hand (Openshaw, 1993), this special issue attempts to present, clearly, some cutting-edge techniques which have great promise.The techniques of interest can be loosely grouped under the umbrella term of 'connectionist' computing techniques. Each focuses on connections within data. They include simulated neural networks, which 'learn' to connect inputs with their associated outputs, and genetic algorithms, which connect parts of some problem solutions to parts of other problem solutions in order to 'breed' improved solutions. They also include cellular automata, which connect the simple behaviours of individual elements in order to generate complex models of the overall system.To appreciate fully the true potential of these techniques, it is necessary to understand how their planning applications evolved. And all applications were able to evolve only because of at least four decades of progress within three separate disciplines-computer-aided planning, artificial intelligence, and connectionist computing itself. Each of these fields passed through similar phases of euphoria in the 1950s and 1960s, disillusion during the 1970s and 1980s, and revival throughout the 1990s. But there were differences in the depths of unpopularity to which their techniques sank during the dark days, there were differences in their levels of 'born again' enthusiasm during the 1990s, and so today there are differences in the nature and potential of their respective contributions.Accordingly, in this editorial essay I will trace the evolution of each field. The conclusion is that connectionist-type computer-aided planning is far less ambitious, and more modest, than the modelling which occurred during the heady days of the 1960s.But I will also argue that the chances of a genuinely productive partnership between humanist and boffin are far greater this time around. Moreover, I will suggest there are signs that computer-based comprehensive contributions to planning, as distinct from the segmented and restricted contributions of today, may one day becom...

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“…Analytical models and associated utility programs in his framework were developed and executed by using Arc/Info AML language. It has been demonstrated that such an approach can provide a more effective problem-solving method, and an intelligent interface can stimulate planners to employ mathematical models more easily and effectively (Han et al, 1991). Another advantage is that expert system techniques are particularly useful for developing conceptual methods and making it possible to incorporate expert knowledge to complement existing algebraic and algorithmic models in SDSS (Arentze et al, 1996).…”

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confidence: 99%

Component-Based Approach in the Development of a Knowledge-Based Planning Support System (KBPSS). Part 1: The Architecture of KBPSS

Yeh

Qiao

2004

Environ Plann B Plann Des

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Urban planners need to have a flexible, interactive, and intelligent computer-based tool to support their use of analytical models and to structure their planning process. Existing spatial information systems have not developed appropriate procedures and mechanisms to enable easy construction and manipulation of models within their system environment, and to allow various information resources to be shared by different application systems and platforms. Recent research and development of planning support systems (PSS) provide a range of interesting concepts and frameworks that can be adopted by system developers to design a multifunctional and planning-specific decision support system to meet the multifaceted needs of the planning process. In this paper we aim to go beyond the current approaches of PSS and spatial decision support systems (SDSS) in designing a knowledge-based PSS (KBPSS) that uses the component-based software development (CBSD) approach. We introduce the features of CBSD and its technical advantages in the design of a multifunctional PSS. An architecture of a component-based KBPSS is subsequently proposed which incorporates four essential component systems: MapObjects GIS, Database Manager database management system, ModelObjects model-management system, and KBSAgents knowledge-based system. The first two components are based on proprietary components systems and can be easily adapted into the KBPSS environment. The ModelObjects and KBSAgents components were developed by the authors. Based on these components and their associated information layers, two application subsystems are constructed: a Model and Knowledge Development System and an Intelligent Model Selection System. These application systems can be used to assist users and model developers to build new models or to select predefined models from an existing model library for their problems. In order to implement these functions, we propose and define a number of procedures and techniques for component communication and model and knowledge development.

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XPLanner: A knowledge-based decision support system for facility management and planning

Cited by 6 publications

References 0 publications

A Non-invasive Approach to Trace Architecture Design, Requirements Specification and Agile Artifacts

A Non-invasive Approach to Trace Architecture Design, Requirements Specification and Agile Artifacts

Guest Editorial

Component-Based Approach in the Development of a Knowledge-Based Planning Support System (KBPSS). Part 1: The Architecture of KBPSS

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