A methodology for the selection of requirements engineering techniques

The complexity of software projects as well as the multidisciplinary nature of requirements engineering (RE) requires developers to carefully select RE techniques and practices during software development. Nevertheless, the selection of RE techniques is usually based on personal preference or existing company practice rather than on characteristics of the project at hand. Furthermore, there is a lack of guidance on which techniques are suitable for a certain project context. So far, only a limited amount of research has been done regarding the selection of RE techniques based on the attributes of the project under development. The few approaches that currently exist for the selection of RE techniques provide only little guidance for the actual selection process. We believe that the evaluation of RE techniques in the context of an application domain and a specific project is of great importance. This paper describes a Methodology for Requirements Engineering Techniques Selection (MRETS) as an approach that helps requirements engineers select suitable RE techniques for the project at hand. The MRETS has three aspects: Firstly, it aids requirements engineers in establishing a link between the attributes of the project and the attributes of RE techniques. Secondly, based on the evaluation schema proposed in our research, MRETS provides an opportunity to analyze RE techniques in detail using clustering. Thirdly, the objective function used in our approach provides an effective decision support mechanism for the selection of RE techniques. This paper makes contributions to RE techniques analysis, the application of RE techniques in practice, RE research, and software engineering in general. The application of the proposed methodology to an industrial project provides preliminary information on the effectiveness of MRETS for the selection of RE techniques.     

形式描述语言COOZ的集成支撑环境COOZ—Tools

介绍支持面向对象的形式描述语言ＣＯＯＺ的集成支撑环境ＣＯＯＺ－Ｔｏｏｌｓ的设计原则、系统结构、功能、特点和关键的实现技术。ＣＯＯＺ是Ｚ语言的面向对象扩充,从而将形式化语言和面向对象机制有机结合起来。ＣＯＯＺ－Ｔｏｏｌｓ支持基于ＣＯＯＺ的软件开发,它主要由如下工具组成：规格说明编辑、浏览工具、语法语义检查工具、联机帮助工具、项目管理工具。     

Exploiting organizational knowledge in developing IS project cost and schedule estimates: An empirical study

Project management is vital to the effective application of organizational resources to competing demands within and across projects. The effective application of project management, however, is predicated upon accurate estimates of the project budget and schedule. This study assesses primary and supporting activities that exploit knowledge within an organization's memory to develop project schedule durations and budgets. The study further assesses the subsequent impact of predictability on project success. Two hundred and sixteen survey responses from IT professionals with project management responsibilities were analyzed. Results found use of the primary activities of using parametric estimating techniques (use of formal models), bottom-up estimating techniques (formulating estimates at the task level), and the support activities of team reliance, realistic targets, and professional experience all impact the predictability of estimates for project cost and duration. Predictability in turn was found to directly impact project success with regards to meeting cost and duration objectives. While use of analogous estimating techniques (using similar previous projects) was not found to be useful for project managers with more experience, it was used by project managers with less experience in determining predictability.     

Re-estimating software effort using prior phase efforts and data mining techniques

Software effort estimation has played an important role in software project management. An accurate estimation helps reduce cost overrun and the eventual project failure. Unfortunately, many existing estimation techniques rely on the total project effort which is often determined from the project life cycle. As the project moves on, the course of action deviates from what originally has planned, despite close monitoring and control. This leads to re-estimating software effort so as to improve project operating costs and budgeting. Recent research endeavors attempt to explore phase level estimation that uses known information from prior development phases to predict effort of the next phase by using different learning techniques. This study aims to investigate the influence of preprocessing in prior phases on learning techniques to re-estimate the effort of next phase. The proposed re-estimation approach preprocesses prior phase effort by means of statistical techniques to select a set of input features for learning which in turn are exploited to generate the estimation models. These models are then used to re-estimate next phase effort by using four processing steps, namely data transformation, outlier detection, feature selection, and learning. An empirical study is conducted on 440 estimation models being generated from combinations of techniques on 5 data transformation, 5 outlier detection, 5 feature selection, and 5 learning techniques. The experimental results show that suitable preprocessing is significantly useful for building proper learning techniques to boosting re-estimation accuracy. However, there is no one learning technique that can outperform other techniques over all phases. The proposed re-estimation approach yields more accurate estimation than proportion-based estimation approach. It is envisioned that the proposed re-estimation approach can facilitate researchers and project managers on re-estimating software effort so as to finish the project on time and within the allotted budget.     

基于场景的笔式界面设计工具的设计和实现*

设计实现了一个基于数字笔的用户界面设计工具,该工具以面向笔式界面领域,基于场景的设计思想来设计系统中的界面场景组织关系以及场景之间的动态切换方式,设计者与工具间的交互自然流畅、快捷高效。通过手势识别技术,该工具可以将场景的设计结果转换为内部的界面描述语言,并通过相应的解释最终构造生成笔式用户界面。该工具可以快速生成界面原型,从而有效地提高了笔式交互系统的设计和开发效率。