A role-oriented service system architecture for enterprise process collaboration

Workflow management is a key technique for coordinating various business processes. Traditional workflow systems are often built with the client/server architecture, in which, a single workflow server takes the responsibility of the entire operation. This paper discusses a model-driven process enactment environment, which can support an enterprise businesses collaboration. Some key technologies regarding models and the system are discussed in the paper, including the mappings between activities in process models and the service function of applications, how to use XML in the process model, and other workflow engine techniques. A software architecture supporting role-oriented services within the process-driven enterprise enactment environment has been proposed and implemented. The proposed framework has been validated with a case study in the 4PL business system.     

Disincentives for communicating risk: a risk paradox

Problems with the risk management in medium to large software projects have been well documented. For major software projects to be completed successfully, an open and cooperative attitude towards risk must be maintained. Despite this significant incentive, project stakeholders frequently conceal risks. This article identifies reasons in three key areas for such behaviour, and suggests approaches that reduce the motivation for this behaviour thereby providing a basis for effective risk management. Examples drawn from a study, undertaken by the authors, of a medium-sized industry project are used to illustrate many of these issues.     

How to steer an embedded software project: tactics for selecting the software process model

Modern large new product developments (NPD) are typically characterized by many uncertainties and frequent changes. Often the embedded software development projects working on such products face many problems compared to traditional, placid project environments. One of the major project management decisions is then the selection of the project's software process model. An appropriate process model helps coping with the challenges, and prevents many potential project problems. On the other hand, an unsuitable process choice causes additional problems. This paper investigates the software process model selection in the context of large market-driven embedded software product development for new telecommunications equipment. Based on a quasi-formal comparison of publicly known software process models including modern agile methodologies, we propose a process model selection frame, which the project manager can use as a systematic guide for (re)choosing the project's process model. A novel feature of this comparative selection model is that we make the comparison against typical software project problem issues. Some real-life project case examples are examined against this model. The selection matrix expresses how different process models answer to different questions, and indeed there is not a single process model that would answer all the questions. On the contrary, some of the seeds to the project problems are in the process models themselves. However, being conscious of these problems and pitfalls when steering a project enables the project manager to master the situation.     

Best practice fusion of CMMI-DEV v1.2 (PP,PMC, SAM) and PMBOK 2008

ContextThe establishment of effective and efficient project management practices still remains a challenge to software organizations. In striving to address these needs, “best practice” models, such as, CMMI or PMBOK, are being developed to assist organizations interested in improving project management. And, although, those models share overlapping content, there are still differences and, therefore, each of the models offers different advantages.ObjectiveThis paper proposes a set of unified project management best practices by integrating and harmonizing on a high-level perspective PMBOK (4th ed.) processes and CMMI-DEV v1.2 specific practices of the basic project management process areas PP, PMC and SAM.MethodBased on the analysis of both models, a unified set of best practices has been defined by a group of researchers with theoretical and practical expertise on the CMMI framework and software process improvement as well as project management and the PMBOK. The proposed set has been revised by different researchers from different institutions in several review rounds until consensus was achieved.ResultsAs a result, a set of unified best practices is defined and explicitly mapped to the correspondent PMBOK processes and CMMI specific practices of the current versions of both models.ConclusionWe can conclude that an integration and harmonization of both models is possible and may help to implement and assess project management processes more effectively and efficiently, optimizing software process improvement investments.     

Developing a Theory to Explain the Insights Gained Concerning Information Systems and Business Process Behaviour: The ASSESS-IT Project

Business Process (BP) literature promotes the value of business processes as essential gearwheels that help organisations to reach their goals. Similarly, many process design approaches claim that information technology is a major enabler of business process, a view also shared by the Information Systems (IS) community. Despite this, BP and IS approaches do not provide clear guidance on how to coordinate the design of BP and IS. Nor is any indication of which modelling techniques could be used to detect and design IT opportunities within a business process context given.The ASSESS-IT project examined this domain and proposed the use of simulation techniques to achieve BP and IT integration. The outcome of this project gave indication that depicting the dynamic behaviour of IS could be very helpful for BP modellers to predict the impact that the insertion of IS may have on organisational processes. This paper proposes a simulation framework to depict IS behaviour within a BP simulation model, namely BPS/ISS, and tests it using the case study that was part of the ASSESS-IT project.     

PROCESSUS – Integration of SEI CMM and ISO quality models

Integration of the two best-known quality management models for software production and maintenance, the Capability Maturity Model and the ISO 9001 Model (including ISO 9000-3) is of great interest for both the European and the American software market. The definition of a quality management model which would conform to the requirements of both models and use the advantages of each was a key goal of our research work within the project PROCESSUS.1 Research work was conducted in two steps: first, the detailed comparison of both models was made in order to define their common issues and specifics of each model, and secondly, the integrated model based on the results of the comparison was defined. In this paper the comparison method and results are described. Further, a method for the integration and a framework of the integrated model are presented. The core of our work is actually the content of the integrated model. Due to extensive content of the integrated model examples of some parts only are given in the appendix. The integrated model presented in this paper has already been successfully used in organizations which are cooperating in the project PROCESSUS o these organizations achieved the needed maturity for certification to the ISO 9001 standard and a maturity level near level 3 of CMM.     

面向GJB 2725A-2001的评测过程管理平台

设计了一个针对GJB 2725A-2001的测评过程管理平台——QESuite2.0。总结了GJB 2725A-2001及附加文件中与测评过程管理相关概念及模型。在此基础上阐述了流程可裁剪、功能可拆卸、项目可定制、文档可自动生成的总体功能架构及基于该框架的设计思想。给出了系统实现中的技术要点并讨论了后续的研发工作及应用前景。     

Preliminary Data Analysis Methods in Software Estimation

Software is quite often expensive to develop and can become a major cost factor in corporate information systems budgets. With the variability of software characteristics and the continual emergence of new technologies the accurate prediction of software development costs is a critical problem within the project management context. In order to address this issue a large number of software cost prediction models have been proposed. Each model succeeds to some extent but they all encounter the same problem, i.e., the inconsistency and inadequacy of the historical data sets. Often a preliminary data analysis has not been performed and it is possible for the data to contain non-dominated or confounded variables. Moreover, some of the project attributes or their values are inappropriately out of date, for example the type of computer used for project development in the COCOMO 81 (Boehm, 1981) data set. This paper proposes a framework composed of a set of clearly identified steps that should be performed before a data set is used within a cost estimation model. This framework is based closely on a paradigm proposed by Maxwell (2002). Briefly, the framework applies a set of statistical approaches, that includes correlation coefficient analysis, Analysis of Variance and Chi-Square test, etc., to the data set in order to remove outliers and identify dominant variables. To ground the framework within a practical context the procedure is used to analyze the ISBSG (International Software Benchmarking Standards Group data—Release 8) data set. This is a frequently used accessible data collection containing information for 2,008 software projects. As a consequence of this analysis, 6 explanatory variables are extracted and evaluated.     

A soft computing framework for software effort estimation

Accurate software estimation such as cost estimation, quality estimation and risk analysis is a major issue in software project management. In this paper, we present a soft computing framework to tackle this challenging problem. We first use a preprocessing neuro-fuzzy inference system to handle the dependencies among contributing factors and decouple the effects of the contributing factors into individuals. Then we use a neuro-fuzzy bank to calibrate the parameters of contributing factors. In order to extend our framework into fields that lack of an appropriate algorithmic model of their own, we propose a default algorithmic model that can be replaced when a better model is available. One feature of this framework is that the architecture is inherently independent of the choice of algorithmic models or the nature of the estimation problems. By integrating neural networks, fuzzy logic and algorithmic models into one scheme, this framework has learning ability, integration capability of both expert knowledge and project data, good interpretability, and robustness to imprecise and uncertain inputs. Validation using industry project data shows that the framework produces good results when used to predict software cost.     

Managing Software Development Projects for Maximum Productivity

In the area of software development, data processing management often focuses more on coding techniques and system architecture than on how to manage the development. In recent years, ``structured programming' and ``structured analysis' have received more attention than the techniques software managers employ to manage. Moreover, these coding and architectural considerations are often advanced as the key to a smooth running, well managed project. This paper documents a philosophy for software development and the tools used to support it. Those management techniques deal with quantifying such abstract terms as ``productivity,' ``performance,' and ``progress,' and with measuring these quantities and applying management controls to maximize them. The paper also documents the application of these techniques on a major software development effort.     

Project management in a software product line organization

In traditional software engineering project management, managers provide focused guidance to a team responsible for producing a specific result in a specified amount of time. Today, however, organizations are increasingly taking a product line approach to software to exploit product commonalities. Software product line organizations have unique practices and project definitions. These unconventional features offer new challenges and directions for traditional project management. How does the traditional concept of a project - a temporary endeavor aimed at creating a unique product or service - hold up under this new paradigm? In this article, we discuss this question, along with how the idea of a "project" and project management techniques must expand to fit a product line context. In particular, we show how the "overall guidelines, policies, and procedures" that Thayer and Pyster spoke of some years ago remain crucially important in product line organizations today.     

The Cactis project: database support for software environments

The Cactis project is an on-going effort oriented toward extending database support from traditional business-oriented applications to software environments. The main goals of the project are to construct an appropriate model, and develop new techniques to support the unusual data management needs of software environments, including program compilations, software configurations, load modules, project schedules, software versions, nested and long transactions, and program transformations. The ability to manage derived information is common to many of these data needs, and the Cactis database management system has the ability to represent and maintain derived data in a time- and space-efficient fashion. A central contribution of Cactis is its integration of the type constructors of semantic models and the localized behavior capabilities of object-oriented database management systems     

A framework for creating hybrid-open source software communities

Abstract The open source software (OSS) model is a fundamentally new and revolutionary way to develop software. The success of the OSS model is also setting the stage for a structural change in the software industry; it is beginning to transform software industry from manufacturing to a service industry. Despite the success of the OSS model, for‐profit organizations are having difficulty building a business model around the open source paradigm. Whereas there are some isolated empirical studies, little rigorous research has been done on how traditional organizations can implement and benefit from OSS practices. This research explores how organizations can foster an environment similar to OSS to manage their software development efforts to reap its numerous advantages. Drawing on organizational theory, we develop a framework that guides the creation and management of a hybrid‐OSS community within an organization. We discuss the implications of this framework and suggest areas for future research.     

基于CMM2级需求管理过程框架的研究与实现

需求管理是在软件工程过程中对变化的需求进行管理的过程。通过分析当前软件需求管理中存在的主要问题,并在研究CMM2级对需求管理要求的基础上,提出了基于CMM2级的需求管理过程框架,并给出了基于该框架的一个实现方案,最后讨论了实现方案中一些关键技术。     

Visual requirements analytics: a framework and case study

For many software projects, keeping requirements on track needs an effective and efficient path from data to decision. Visual analytics creates such a path that enables the human to extract insights by interacting with the relevant information. While various requirements visualization techniques exist, few have produced end-to-end value to practitioners. In this paper, we advance the literature on visual requirements analytics by characterizing its key components and relationships in a framework. We follow the goal–question–metric paradigm to define the framework by teasing out five conceptual goals (user, data, model, visualization, and knowledge), their specific operationalizations, and their interconnections. The framework allows us to not only assess existing approaches, but also create tool enhancements in a principled manner. We evaluate our enhanced tool support through a case study where massive, heterogeneous, and dynamic requirements are processed, visualized, and analyzed. Working together with practitioners on a contemporary software project within its real-life context leads to the main finding that visual analytics can help tackle both open-ended visual exploration tasks and well-structured visual exploitation tasks in requirements engineering. In addition, the study helps the practitioners to reach actionable decisions in a wide range of areas relating to their project, ranging from theme and outlier identification, over requirements tracing, to risk assessment. Overall, our work illuminates how the data-to-decision analytical capabilities could be improved by the increased interactivity of requirements visualization.     

A framework for software process deployment and evaluation

ContextSoftware Process Engineering promotes the systematic production of software by following a set of well-defined technical and management processes. A comprehensive management of these processes involves the accomplishment of a number of activities such as model design, verification, validation, deployment and evaluation. However, the deployment and evaluation activities need more research efforts in order to achieve greater automation.ObjectiveWith the aim of minimizing the required time to adapt the tools at the beginning of each new project and reducing the complexity of the construction of mechanisms for automated evaluation, the Software Process Deployment & Evaluation Framework (SPDEF) has been elaborated and is described in this paper.MethodThe proposed framework is based on the application of well-known techniques in Software Engineering, such as Model Driven Engineering and Information Integration through Linked Open Data. It comprises a systematic method for the deployment and evaluation, a number of models and relationships between models, and some software tools.ResultsAutomated deployment of the OpenUP methodology is tested through the application of the SPDEF framework and support tools to enable the automated quality assessment of software development or maintenance projects.ConclusionsMaking use of the method and the software components developed in the context of the proposed framework, the alignment between the definition of the processes and the supporting tools is improved, while the existing complexity is reduced when it comes to automating the quality evaluation of software processes.     

Improved estimation of software project effort using multiple additive regression trees

Accurate estimation of software project effort is crucial for successful management and control of a software project. Recently, multiple additive regression trees (MART) has been proposed as a novel advance in data mining that extends and improves the classification and regression trees (CART) model using stochastic gradient boosting. This paper empirically evaluates the potential of MART as a novel software effort estimation model when compared with recently published models, in terms of accuracy. The comparison is based on a well-known and respected NASA software project dataset. The results indicate that improved estimation accuracy of software project effort has been achieved using MART when compared with linear regression, radial basis function neural networks, and support vector regression models.     

Experiences Using Domain Specific Techniques within Multimedia Software Engineering

Domain specific techniques take advantage of the commonalities among applications developed within a certain domain. They are known to improve quality and productivity by incorporating domain knowledge and previous project experiences and promote reuse. This paper describes six domain specific software engineering techniques for developing multimedia applications within the digital library domain. We provide examples of each technique from several projects in which they were used, how the techniques are used within general software engineering practice (in particular, MBASE), how the techniques address some of the particular challenges multimedia software engineering, and the positive impacts we have measured resulting from their use within a graduate level software engineering course.