P. Mi and W. Scacchi, A knowledge-based environment for modeling and simulating software engineering processes, ACM Trans. Knowl. Data Eng., 2(3), 1990, 283--289.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....and shut down operations) The PML tool support offered by most PSEEs is similar to what is currently provided by OIKOS, EPOS, and SPADE 1. Some environments offer also some more innovative features. For instance, Articulator offers tools supporting knowledge acquisition and process simulation [55]. All systems have editors to build and maintain process models and to enact these. The latter implies a concurrent distributed run time environment to support real, non toy processes. However, there is often little support for visualization, viewing, explanation, simulation, etc. This kind of ....

P. Mi and W. Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, Vol. 2, No. 3, March 1990.

....are recorded in multi layered design histories. In [2] reuse information is organized in frameworks used mainly for the design phase. In LaSSIE [10] information relating to software development is stored in frames structures, and a retrieval system is provided on the basis of frame contents. In [23], multi agent development is explicitly represented as a meta model using a knowledge based formalism; knowledge acquisition and query mechanisms are taken into account as a basis for simulation of software behaviour. The approach presented in this paper consists of tools supporting requirements ....

P. Mi, W. Scacchi, "A Knowledge-based Environment for Modeling and Simulating Software Engineering", IEEE Trans. on Knowledge and Data Engineering, vol. 2, n.3, Sept. 1990

....control; our support for recovery is clearly not powerful enough for all ETMs. Several researchers are currently investigating recovery for ETMs [27] TML behaves according to a task model, described through some modeling formalism, such as rules [96, 17] Petri nets [8, 43] task graphs [110, 80], or workflow [79] A task model describes the set of tasks and activities allowed for users of the system. TML manages all steps and activities generated as each user request is processed, thus TML contains the semantic information for all tasks. ECC is the concurrency control component, ....

Peiwei Mi and Walt Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, 2(3):283--294, September 1990. 249

....condition expression is true) the state transition is taken and the actions are performed, moving the process to the next state. However, there are no means to actually execute software development tools or to store product data, so the process execution can only effect a simulation. Articulator [14] simulates a process by symbolically executing tasks according to the task precedence structure specified in the process model. The simulation proceeds as long as task conditions are satisfied at each step; otherwise, the simulated process stops, reports the problem, and waits for input or ....

Peiwei Mi and Walt Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, 2(3):283--294, September 1990.

....and relies on its inferential capabilities. The rule based tools that supports project management suggest that such an approach can be used for designing and implementing the development environments of large scale software systems. In fact, a definition of the software process is the following [132]: the software process is a collection of related activities, seen as a coherent process subject to reasoning, involved in the production of a software product. These activities take place inside a so called process centered environment that should actively enact the cooperation of all the ....

P. Mi and W. Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, 2(3):283--294, September 1990.

....from the environment implemented by Tcl Tk. ## ####### #### This work has relationships with knowledge based software engineering (KBSE) and ontology engineering. From the eld of KBSE, USC group has developed a knowledge based environment for software engineering processes, called Articulator [9] and SMART [8] The environments modify software process plans with faults, by diagnosing, replanning and rescheduling them using several types of knowledge and strategies. Schlumberger group(G. Arango et al. tries to reuse and evolve software design processes based on a kind of retrieve and ....

P. Mi and W. Scacchi, \A knowledge-based environment for modeling and simulating software engineering processes," IEEE Transaction on Knowledge and Data Engineering, Vol.2, No.3, pp.283-294, 1990.

.... are four main activities in the process life cycle: process modeling, process analysis, process enactment, and process execution status monitoring and control [2] 5] Previous approaches to providing automated support for the process lifecycle have focused attention on subsets of the lifecycle [8], 6] 4] The SMART architecture represents the first attempt to provide comprehensive support for the entire process life cycle [2] SMART, however, does not provide robust support for execution status monitoring and process redesign based on feedback status analysis driven feedback. This paper ....

P. Mi. and W. Scacchi, "A Knowledge-Based Environment for Modeling and Simulating Software Engineering Processes", IEEE Transactions on Knowledge and Data Engineering, Vol. 2, No. 3, Sept. 1990, pp. 283-294.

.... with a fixed set of quantitative models such as a model for effort (facet 3: variable non stochastic, facet 4: fixed non stochastic) DesignNet models are mainly built for planning, estimating, and guiding software projects (facet 5: planning, estimating, guidance) Articulator Mi and Scacchi [19] propose a software process modeling and simulation system called Articulator. The Articulator is a knowledge based approach and uses a meta model of software processes. It supports the analysis of software processes by providing software process simulation functionality. User defined queries can ....

Peiwei Mi and Walt Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, 2(3):283--294, September 1990.

.... the Virtual Design Team simulator for civil engineering projects [Levitt et al. 1994] designing organizations for decision making under stress [Lin and Carley, 1993] the Business Process Handbook project [Malone et al. 1993] computer based modeling of software engineering processes [Mi and Scacchi, 1990] , the ACTION system for re engineering electronic small parts manufacturing organizations [Hulthage, 1994] and the work I will describe in this dissertation on modeling computational agent environments and designing new coordination mechanisms. 12 1.5 Chapter Summary A coordination problem ....

P. Mi and W. Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Transactions on Knowledge and Data Engineering, 2(3):283--294, September 1990.

....structure of development projects, though they singularly lack an appreciation of the wider organisational context. Recent research into process modelling is of interest here, as this aims to offer a means for understanding the full environment in which a system is developed (see [Lyytinen 1987, Mi Scacchi 1990, Jarke et al. 1993] In a comprehensive analysis of the cause of software errors, recommendations were made for modularising responsibility and promoting informal communication [Lutz 1993] Our investigations independently consolidate these recommendations, as they make it apparent that ....

Mi, P. and Scacchi, W. (1990). A Knowledge-Based Environment for Modeling and Simulating Software Engineering Processes, IEEE Transactions on Knowledge and Data Engineering, Volume 2, Number 3, September, pp. 283-294.

....available for subsequent examination and review. Each of these highlighted items point to the public availability of data that can be collected, analyzed, and rerepresented within narrative ethnographies or computational process models (Curtis, Kellner, and Over 1992, Kling and Scacchi 1982, Mi and Scacchi 1990, Scacchi 1998,1999) Significant examples of each kind of data can be readily provided for presentation at the Workshop and in the full paper. Comparative case study framework The software development practices of the four communities we chose to examine can be compared and contrasted in a ....

P. Mi and W. Scacchi, A Knowledge-based Environment for Modeling and Simulating Software Engineering Processes. IEEE Trans. Knowledge and Data Engineering, 2(3), 283-294, Sept 1990.

.... modeling, analysis, walkthrough, redesign, and enactment across a distributed virtual enterprise of cooperating networked enterprises [Noll and Scacchi 1999, Scacchi and Noll 1997] The design of PML was based on compatibility with the software process meta model that we had previously developed [Mi and Scacchi 1990, 1996, Scacchi 1999] Accordingly, agents (people or programs) perform processes that use tools to require resources in order to provide intermediate or final products. Process resource requirements and provision are specified using predicate expressions that serve as pre conditions or ....

....and thus the potential exists for different simulation components to exchange common objects, but establish their meaning locally. This is in marked contrast to the use of process meta models, which support process simulation and interoperability through a centralized semantic data model [Mi and Scacchi 1990, 1996] Maintaining and updating a centralized semantic model is much easier than maintaining distributed simulation object semantics local to each simulation. The effort required to maintain and evolve distributed object semantics does not scale with the incorporation of more simulation ....

P. Mi and W. Scacchi. A Knowledge-Based Environment for Modeling and Simulating Software Engineering Processes. IEEE Trans. Knowledge and Data Engineering, 2(3):283-294, 1990.

....involved in model composition. Finally, we conclude and add some additional remarks regarding our current efforts. 2 Background In the domain of large scale software development, many new product, process, and decision support models have been proposed [DBe90, EJe91, GP 92, HL88, Kai88, MS90, OB92, RD91, SPW92, WS88] These models are used to facilitate different aspects of software development when employed within support systems we call process centered software development support environments (PSDSEs) These models also facilitate the archiving and reuse of product, process, ....

.... environments (PSDSEs) These models also facilitate the archiving and reuse of product, process, and decision making artifacts [WS88, MLS92] through sharing the object classes among software developers, as well as query and reasoning about relations between modeled objects and their attributes [MS90, RD91] For example, Ramesh and Dhar [RD91] advocate the need for a PSDSE that records and organizes for retrieval the kinds of decisions made and rationales employed when building large software systems. Since different models and PSDSEs usually deal with only one particular aspect of software ....

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P. Mi and W. Scacchi. A Knowledge-based Environment for Modeling and Simulating Software Engineering Processes. IEEE Trans. on Knowledge and Data Engineering, 2(3):283--294, Sept 1990.

....is also required to integrate process representation, data management, and tool invocation. Recent progress in software process modeling and process integration has made process driven software development a very promising, yet realistic engineering technique for the software engineering community [Boe86, HK89, Kai88, MS90, MS91]. When knowledge based process representations are utilized, management and reuse of the classes and instances of the representations becomes a necessity. To this end, a knowledgebased process library provides a solution the problem of process management and reuse. A knowledge based process ....

....we present a knowledge based approach to organize, access and reuse software processes. We describe the initial design and prototype implementation for a knowledgebased software process library called SPLib. SPLib supports an extended version of the Articulator meta model of software processes [MS90] and provides knowledge based operations to access and reuse of software processes. As such, we first discuss two types of related work that lead to the SPLib: one that relates a knowledge based approach to our study of software process reuse; the other that describes how software process modeling ....

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P. Mi and W. Scacchi. A Knowledge-based Environment for Modeling and Simulating Software Engineering Processes. IEEE Trans. on Knowledge and Data Engineering, 2(3):283--294, Sept 1990.

....model consisting of activities, composite activities, products and tools. SDA is unique in that it only addresses the early phase of design and that it uses a model based approach to the design and construction of an environment. The DSF project has been developing and using the Articulator [57], which is a knowledge based environment for modeling, analyzing, and simulating software production processes. The Articulator uses a hierarchical object oriented representation of agent roles, products (or resources) and tasks, which can be either partially ordered or triggered through ....

....use is similar in scope to Adele 2, but they both lack support for a persistent object store, other than the underlying file system. However, the SMART environment [31] can semi automatically generate SynerVision process program code via transformations on Articulatorbased software process models [57], while Process WEAVER allows modeled process states to be attributed with Unix shell commands, which can subsequently be executed under user direction. Last, both OIKOS [3] and OPM [85] propose object oriented approaches to process programming. The idea in these two efforts is to show how ....

P. Mi and W. Scacchi. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Trans Knowledge and Data Engineering, 2(3):283--294, March 1990.

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P. Mi and W. Scacchi, A knowledge-based environment for modeling and simulating software engineering processes, IEEE Trans. Knowledge and Data Engineering, 2(3):283--294, 1990.

....these objects are linked through many kinds of relations. Altogether, SPMs serve as a repository of information on the status of development processes and activities that get manipulated throughout a software development project. Readers can find a detailed definition of SPMs elsewhere, such as in [MS90]. An SPM specifies an activity hierarchy that describes a decomposition of development activities and resource requirements including software artifacts, tools, developers, and other critical resources. We follow the scheme presented in [MS90] An activity hierarchy represents decomposition of an ....

....a detailed definition of SPMs elsewhere, such as in [MS90] An SPM specifies an activity hierarchy that describes a decomposition of development activities and resource requirements including software artifacts, tools, developers, and other critical resources. We follow the scheme presented in [MS90]. An activity hierarchy represents decomposition of an SPM into a hierarchy of smaller activities called tasks and actions. Levels of decomposition can be arbitrary depending on the complexity of the process. The top level description of an SPM is a task which is recursively decomposed into a set ....

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P. Mi and W. Scacchi. A Knowledge-based Environment for Modeling and Simulating Software Engineering Processes. IEEE Trans. on Knowledge and Data Engineering, 2(3):283--294, Sept 1990.

....base of problem solving heuristics and implements them. Then articulation reschedules the necessary resources so overall plan execution is able to continue according to the modified plan. Our articulation approach is prototyped in a multi agent knowledge based system, called the Articulator [MS90, MS91b, Mi92]. In what follows, we first give an overview of articulation in Section 2 which integrates diagnosis, replanning, and rescheduling. In Section 3, we briefly discuss plan representation in the Articulator. We present these issues and specify the problem space, the solution space, and the ....

....Second, a repair suggestion is forwarded to a user whose responsibility is to study sets of repair suggestions gathered from repeated plan executions and realize necessary modifications or repairs to the original process model. The Articulator is implemented in the form of a knowledge based system[MS90]. The knowledge and experience of articulation abstracted from empirical studies of human articulation behavior are represented as knowledge schemata and inference rules[MS91b, Mi92] The Articulator has 4 modules that together perform support articulation: ffl The problem space that embodies ....

[Article contains additional citation context not shown here]

P. Mi and W. Scacchi. A Knowledge-based Environment for Modeling and Simulating Software Engineering Processes. IEEE Trans. on Knowledge and Data Engineering, 2(3):283--294, Sept 1990.

No context found.

P. Mi and W. Scacchi, A knowledge-based environment for modeling and simulating software engineering processes, ACM Trans. Knowl. Data Eng., 2(3), 1990, 283--289.

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Pciwci Mi and Walt Scacchi (1990). A Knowledge-Based Environment for Modeling and Simulating Software Engineering Processes: IEEE Transactions on Knowledge and Data Enginccring,Vol.2,No.3:283-294.

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MI,P.AND SCACCHI, W. 1990. A knowledge-based environment for modeling and simulating software engineering processes. IEEE Trans. Knowl. Data Eng. 2, 3 (Mar.).

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