Peiwei Mi

A knowledge-based environment for modeling and simulating software engineering processes

The design and representation schemes used in constructing a prototype computational environment for modeling and simulating multiagent software engineering processes are described. This environment is called the articulator. An overview of the articulators architecture identifying five principal components is provided. Three of the components, the knowledge metamodel, the software process behavior simulator, and a knowledge base querying mechanism, are detailed and examples are included. The conclusion reiterates what is unique to this approach in applying knowledge engineering techniques to the problems of understanding the statics and dynamics of complex software engineering processes. >

Process integration in CASE environments

Research in CASE environments has focused on two kinds of integration: tool and object. A higher level of integration, process integration, which represents development activities explicitly in a software process model to guide and coordinate development and to integrate tools and objects, is proposed. Process integration uses software process models (SPMs) a process driver, a tool set, and interfaces for both developers and managers to form the backbone of a process-driven CASE environment. The developers interface, a working environment that lets developers enact an SPM, and the managers interface which gives managers and analysts the tools to define, monitor, and control the SPMs that developers are working on concurrently are discussed. The Softman environment experiment, an implementation of process-driven CASE environments with existing CASE environments, is reviewed.<<ETX>>

A meta-model for formulating knowledge-based models of software development

Abstract In this paper, we introduce a knowledge-based meta-model which serves as a unified resource model for integrating characteristics of major types of objects appearing in software development models (SDMs). The URM consists of resource classes and a web of relations that link different types of resources found in different kinds of models of software development. The URM includes specialized models for software models for software systems, documents, agents, tools, and development processes. The URM has served as the basis for integrating and interoperating a number of process-centered CASE environments. The major benefit of the URM is twofold: First, it forms a higher level of abstraction supporting SDM formulation that subsumes many typical models of software development objects. Hence, it enables a higher level of reusability for existing support mechanisms of these models. Second, it provides a basis to support complex reasoning mechanisms that address issues across different types of software objects. To explore these features, we describe the URM both formally and with a detailed example, followed by a characterization of the process of SDM composition, and then by a characterization of the life cycle of activities involved in an overall model formulation process.

Modeling Articulation Work in Software Engineering Processes

Current software process modeling techniques do not generally support articulation work. Articulation work is the diagnosis, recovery and resumption of development activities that unexpectedly fail. It is an integral part of software process enactment since software processes can sometimes fail or breakdown. This paper presents a knowledge-based model of articulation work in software engineering processes. I t uses empirically-grounded heuristics t o address three problems in articulation work: diagnosing failed development activities, determining appropriate recovery, and resuming software processes. We first investigate the role and importance of articulation work with respect t o planned software development activities. We then outline a knowledge-based model of articulation work. The model has been implemented in a knowledgebased software process modeling environment called the Articulator. Combining the available software process modeling techniques and the model of articulation leads to a better foundation in process improvement and evolution.

Process Life Cycle Engineering: A Knowledge-Based Approach and Environment

We describe our approach and mechanisms to support the engineering of organizational processes throughout their life cycle, and our current understanding of what activities are included in the process life cycle. We then go on to discuss our approach, computational mechanisms, and experiences in supporting many of these life cycle activities, as well as compare it to other related efforts. Along the way, we present examples drawn from a recent study that uses the approach and the mechanisms of our knowledge-based process engineering environment to support the (re)engineering of corporate financial operations in a mid-size consumer products organization.© 1997 John Wiley & Sons, Ltd.

The SMART approach for software process engineering

Describes a methodology for software process engineering and an environment, SMART, that supports it. SMART supports a process life-cycle that includes the modeling, analysis, and execution of software processes. SMARTs process monitoring capabilities can be used to provide feedback from the process execution to the process model. SMART represents the integration of three separately developed process mechanisms, and it uses two modeling formalisms (object-oriented data representation and imperative-style programming language) to bridge the gap between process modeling, analysis, and execution. SMART demonstrates the meta-environment concept, using a process modeling formalism as input specification to a generator that produces process-centered software engineering environments (PSEEs). Furthermore, SMART supports a team-oriented approach for process modeling, analysis, and execution.<<ETX>>

Articulation: an integrated approach to the diagnosis, replanning, and rescheduling of software process failures

The paper presents an integrated approach to articulate software process plans that fail. Articulation repairs a plan when a diagnosed failure occurs and reschedules changes that ensure the plans continuation. In implementing articulation, we combine diagnosis, replanning, and rescheduling into a powerful mechanism supporting adaptive process-based software development. Use of articulation in plan execution supports recovery and repair of anticipated failures, as well as revising and improving the plans to become more effective. We also describe how a prototype knowledge-based system we developed implements the articulation approach.<<ETX>>

A knowledge-based software process library for process-driven software development

The authors present a knowledge-based process library (SPLib) that supports the organization, access, and reuse of software processes. SPLib consists of a knowledge base of software process representations. It also provides a set of process operations that support browsing, searching, composition, and abstraction. These operations reason about the content of software processes as well as maintain proper interdependency relationships among the software processes. To demonstrate the use of SPLib in process-driven software development, a usage scenario is provided where SPLib facilitates the access and reuse of software processes.<<ETX>>

Articulation: Supporting Dynamic Evolution Of Software Engineering Processes

Software process modeling is aimed at understanding and facilitating software development processes. A software process model (SPM) is an abstract representation of a software engineering process. In recent years, SPMs have been proven to be a powerful tool for describing procedural knowledge of software development activities. Enactment of an SPM enables software developers to carry out development activities according to the SPM [DOWSO, MS91a]. As such, the SPM acts as a plan that anticipates types of development activities involved, their performance sequence, and the resources and tools needed to perform them. Software development under the guidance of an SPM becomes an organized execution of the SPM. However, enactment of SPMs fails to handle unexpected events that interrupt software development. This interruption is called a breakdown. A number of empirical studies of software development have revealed both the frequent occurrence of such breakdowns and a recurring type of activity that resolves or mitigate these descriptions [BS87, OSS871. Such breakdowns regularly occur when SPMs are enacted by teams of people who must coordinate and communicate their use of shared development resources [BS89]. This type of resolution or recover activity is called articulation [MS91]. The importance of studying articulation is twofold: from the point view of process enactment, it helps software developers to solve unexpected breakdowns and to continue their tasks; more importantly, from the point view of process modeling, it provides a robust mechanism to accommodate and to dynamically evolve SPMs to a particular engineering environment. This paper outlines a knowledge-based approach to model articulation and dynamic evolution of SPMs during their enactment, which is based on our previous work of software process modeling [MSgO]. At the end, we will briefly discuss the impact of the articulation model on the dynamism of SPMs.