一种嵌入式软件项目估计方法

软件项目估计是CMM2级软件项目策划KPA的基础,是软件开发中的一个重要环节。合理的估计是保证软件项目符合预算和进度要求的前提条件。描述了基于CMM的软件估计的过程,介绍了一种基于嵌入式软件项目的估计方法,并结合具体实例对规模估计、工作量／成本估计、关键计算机资源估计和进度估计的内容进行了细致的阐述。该研究为有效地规划和管理嵌入式软件项目,制定合理可行的软件开发计划提供了有力的支持。     

Knowledge-based risk assessment and cost estimation

A knowledge-based method for software project risk assessment and cost estimation has been implemented on multiple platforms. As an extension to the Constructive Cost Model (COCOMO), it aids in project planning by identifying, categorizing, quantifying and prioritizing project risks. It also detects cost estimate input anomalies and provides risk control advice in addition to conventional COCOMO cost and schedule calculation.The method has been developed in conjunction with a system dynamics model of the software development process, and serves as an intelligent front end to the simulation model. It extends previous research in the knowledge-based cost estimation domain by focusing on risk assessment, incorporating substantially more rules, going beyond standard COCOMO, performing quantitative validation, providing a user-friendly interface, and integrating it with a dynamic simulation model.Results of the validation are promising, and the method is being used at Litton Data Systems and other industrial environments. It will be undergoing further enhancement as part of an integrated capability for software engineering to assist in system acquisition, project planning and risk management.     

DAISY: a decision support design methodology for complex,experience-centered domains

Users at different levels of domain experience have very different needs. For example, a system designed to assist domain novices may frustrate experts and vice-versa. This is one of several challenges specific to building decision support systems for experience-centered domains. A second challenge in working with complex experience-centered domains is that it is hard for non-experts to understand the domain in order to model it. In this paper we present DAISY, the design aid for intelligent support systems. It is a software design methodology for constructing decision support systems in complex, experience-based domains. DAISY address the specialized challenges of these domains by augmenting existing cognitive engineering methodologies. In particular, DAISY provides a method for identifying the specialized needs of users within a specific range of domain experience. Thus, it can help software designers to understand "What does the domain expert need?" or "What does a trained novice need?" To help system designers manage the complexity of modeling unfamiliar experience-centered domains, it provides a tool called a time/activity matrix. To illustrate each of DAISY's steps, we used the development of a decision support system called Fox. Fox assists expert military planners by rapidly generating alternative plans. This is a cognitively difficult, time critical task with life and death consequences     

Package-oriented software engineering: a generic architecture

New methodologies and better techniques are the rule in software engineering, and users of large and complex methodologies benefit greatly from specialized software support tools. However, developing such tools is both difficult and expensive, because developers must implement a lot of functionality in a short time. A promising solution is component-based software development, in particular package-oriented programming (POP). POP fails, however, to satisfy all the requirements of large, complex software engineering tasks. A more generic POP architecture would better serve the development of software engineering environments for large and complex methodologies. Such an architecture emerged from our development experiences with two software engineering research tools: Holmes, a domain analysis support tool; and Egidio, a unified-modeling-language-based business modeling tool. We found this particular architecture simple to understand, easy to implement, and a natural candidate for a generic POP architecture. Our generic architecture satisfies the additional requirements we deem important for larger, more complex software engineering activities. Our experiences show that the strength of this architecture lies in its simplicity and ability to work with multiple users and quickly integrate a wide variety of applications. It is not perfect, but we present it as a first step toward a more general package-oriented architecture to encourage further research in this area     

基于MetaEdit+的元建模

统一建模语言UML的广泛使用大大提升了模型在软件开发中的作用,以模型为核心的软件开发方法逐渐被人们所接受.但由于UML是作为一种通用建模语言而设计的,它既庞大而又复杂,所以不容易为领域专家所学习和掌握,常常使软件设计人员陷入繁重的建模工作而不能脱身.使用面向特定领域的建模语言DSL(Domain Specific La...     

Software Development Cost Modeling and Estimation Through a UNSW Lens

This paper investigates the manner in which Barry Boehm and his work have had an influence upon the research at UNSW into software development cost modeling and estimation. During the period 1979 to the present, faculty and students have investigated cost models for the commercial software development environment, project elapsed time compression, software sizing, estimation accuracy, and analysis of project history databases. This investigation reveals the foresight contained within the Boehm publications and the significant contribution made by these over the last three decades.     

A hybrid approach of goal programming for weapon systems selection

Because weapon systems are perceived as crucial in determining the outcome of a war, selecting weapon systems is a critical task for nations. Just as with other forms of decision analysis involving multiple criteria, selecting a weapon system poses complex, unstructured problems with a huge number of points that must be considered. Some defense analysts have committed themselves to developing efficient methodologies to solve weapon systems selection problems for the Republic of Korea’s (ROK) Armed Forces. In the present study, we propose a hybrid approach for weapon systems selection that combines analytic hierarchy process (AHP) and principal component analysis (PCA) to determine the weights to assign to the factors that go into these selection decisions. These weights are inputted into a goal programming (GP) model to determine the best alternative among the weapon systems. The proposed hybrid approach that combines AHP, PCA and GP process components offsets the shortcomings posed by obscurity and arbitrariness in AHP and therefore can provide decision makers with more reasonable and realistic decision criteria than AHP alone. A case study on weapon system selection for the air force demonstrates the usefulness and effectiveness of the proposed hybrid AHP–PCA–GP approach.     

Model transformations in the UPES/UPSoC development process for embedded systems

Model-based development (MBD) aims at combining modeling languages with model transformers and code generators. Modeling languages, like profiles of the Unified Modeling Language (UML), are increasingly being adopted for specific domains of interest to alleviate the complexity of platforms and express domain concepts effectively. Moreover, system development processes based on automatic model transformations are widely required to improve the productivity and quality of the developed systems. In this paper, we show how MBD principles and automatic model transformations provide the basis for the unified process for embedded systems (UPES) development process and its unified process for system-on-chip (SoC) (UPSoC) subprocess. They have been defined to foster in a systematic and seamless manner a model-based design methodology based on the UML2 and UML profiles for the C/SystemC programming languages, which we developed to improve the current industrial system design flow in the embedded systems and system-on-chip area. This work is supported in part by the project Model-driven methodologies and techniques for embedded systems design and analysis based on UML, Abstract State Machines, and SystemC at STMicroelectronics, AST R&I of Agrate Brianza (MI), Italy.     

The effects of development process modeling and task uncertainty on development quality performance

We examine the impact of development process modeling on outcomes in software development projects, limiting our attention to process and product quality. Modeling the software development process requires a careful determination of tasks and their logical relationships. Essentially, the modeling is undertaken to establish a management framework of the project. We define and interrelate development process modeling, task uncertainty, and development outcomes, as assessed by product and process quality. A survey-based research design was used to collect data to prove our model. The results suggest that development process modeling is positively related to both product and process quality, while task uncertainty is negatively related to them. Development process modeling reduces the negative impact of task uncertainty on quality-oriented development outcomes. Development projects operating with high levels of task uncertainty should consider defining development process models that provide a framework for management of the project by establishing tasks and their logical interrelationships. Such a model should promote shared understanding of the work process among development constituents and enhance resource utilization efficiency.     

Cost models for future software life cycle processes: COCOMO 2.0

Current software cost estimation models, such as the 1981 Constructive Cost Model (COCOMO) for software cost estimation and its 1987 Ada COCOMO update, have been experiencing increasing difficulties in estimating the costs of software developed to new life cycle processes and capabilities. These include non-sequential and rapid-development process models; reuse-driven approaches involving commercial off-the-shelf (COTS) packages, re-engineering, applications composition, and applications generation capabilities; object-oriented approaches supported by distributed middleware; and software process maturity initiatives. This paper summarizes research in deriving a baseline COCOMO 2.0 model tailored to these new forms of software development, including rationale for the model decisions. The major new modeling capabilities of COCOMO 2.0 are a tailorable family of software sizing models, involving Object Points, Function Points, and Source Lines of Code; nonlinear models for software reuse and re-engineering; an exponentdriver approach for modeling relative software diseconomies of scale; and several additions, deletions and updates to previous COCOMO effort-multiplier cost drivers. This model is serving as a framework for an extensive current data collection and analysis effort to further refine and calibrate the model's estimation capabilities.     

Application of Metamodel Inference with Large-Scale Metamodels

In software engineering, new technologies and methodologies have been developed with the aim of simplifying the software development process and improving software productivity. Model-driven engineering is considered as one potential alternative to the classical code-based approach to software development. A current challenge in model-driven engineering is the model evolution problem, which is focused on maintaining the relationships among modeling artifacts in the presence of change. A variety of model-driven technologies have been widely researched and applied both in academia and industry to address the model evolution problem. Reverse engineering technologies have been applied in many areas including software engineering to address issues of software evolution. This paper describes one application of reverse engineering, using an approach that uses Metamodel Inference from Models (MIM) to address a specific aspect of the model co-evolution problem related to metamodel evolution. In order to illustrate the problem clearly, a set of examples are used to present our experimental results from applying MIM on diverse industry-focused domains.     

A semi-automated filtering technique for software process tailoring using neural network

It is widely known that implementation of the software development process to fit a given environment is the key to develop software at the lowest cost and highest quality. In general, applying an off-the-shelf software development process or an organizational process to a specific project can cause a lot of overhead if no effort is made to customize the given generic processes. Even though the process tailoring activities are done before starting a project, they are not given high importance. These activities depend on several process engineers who have a lot of experience and knowledge about process tailoring. Because of this dependence on human experience, it takes a long time to have a tailored process fit the project. To decide whether a specific task should be part of a given project or not is very time-consuming. Therefore, we suggest a semi-automated process tailoring method, which uses the artificial-neural network-based learning theory to reduce this time. We have demonstrated the effectiveness of our process filtering technique with a case study using process tailoring historical data as learning data.     

A software reuse measure: Monitoring an enterprise-level model driven development process

The purpose of the research discussed here is to establish a metric for the measurement of reuse in a generic enterprise-level model context and to use this approach to create a specific metric for a company. The paper demonstrates how a software development firm can monitor the reuse success in the development process using the measure. Traditionally, the reuse rate is defined as the percentage of the development effort retrieved as code segments from a software repository. The metric proposed here extends this definition to include reuse of generic enterprise-level model components. An example is given of the successful assessment of a reuse percentage for a software developer's actual project.     

Enabling control software generation by using mechatronics modeling primitives

Mechatronic systems are characterized by the synergetic integration of mechanic, electronic, software and control design aspects. The development of control software requires data and information from all design domains in order to create the required integrated functionality. This paper proposes a method that combines function modeling and multi-domain modeling primitives to generate control software automatically. An architecture model, based on the Function-Behavior-State modeling paradigm, provides the decomposition and flow of both functionality and implementation, which serves as input to a knowledge-based engineering application. The control software is subsequently extracted from a virtual product model composed of instantiated modeling primitives. A case study of a mobile robot shows how for a specific application the modeling are defined and how a high-level function model for an environment mapping mission is translated into directly implementable software code. This approach could be extended to real-life mechatronic products, and will improve consistency and reduce development time and cost.     

基于数传电台的靶用型无人机测控系统

靶用型无人机简称靶机,模拟航空飞行器的飞行性能和外部特性,用于防空探测系统和防空武器系统的功能和性能测试.由于靶机是一种消耗性资源,为其研制专用测控系统,价格昂贵且通用性受限.本着低成本、通用化和小型化的原则,以数传电台为核心硬件,设计了适用于靶机的测控系统.详细论述了该测控系统的总体设计、硬件设计和软件设计,并对测控作用距离进行了分析.该测控系统已在多型靶机上得到了成功应用.     

软件成本估算技术比较及趋势分析

总结软件成本估算的研究应用情况, 对比分析软件成本估算的6种估算方法、6种建模技术、12种估算工具,在此基础上,提出软件成本估算的发展趋势,为关联研究和应用提供了参考.     

Improving the COCOMO model using a neuro-fuzzy approach

Accurate software development cost estimation is important for effective project management such as budgeting, project planning and control. So far, no model has proved to be successful at effectively and consistently predicting software development cost. A novel neuro-fuzzy Constructive Cost Model (COCOMO) is proposed for software cost estimation. This model carries some of the desirable features of a neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, the proposed model can be interpreted and validated by experts, and has good generalization capability. The model deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimates. In addition, it allows input to have continuous rating values and linguistic values, thus avoiding the problem of similar projects having large different estimated costs. A detailed learning algorithm is also presented in this work. The validation using industry project data shows that the model greatly improves estimation accuracy in comparison with the well-known COCOMO model.     

非成熟领域软件复用过程模型

将一个软件企业或开发团队实现有组织的软件复用分为4个阶段,针对可复用资源积累阶段的特点,提出了非成熟领域软件复用过程模型,应用系统分析设计与领域分析适当结合,经数次迭代,逐步积累领域知识,使面向提交的应用系统开发平滑过渡到基于复用地开发,使该领域尽快成熟.该过程模型还考虑了应用系统开发时效和软件开发团队运营成本问题,此阶段软件复用不强调领域工程,应用系统开发是面向提交的,但需要使用基于构件的软件开发.