SPARTACAS: automating component reuse and adaptation

A continuing challenge for software designers is to develop efficient and cost-effective software implementations. Many see software reuse as a potential solution; however, the cost of reuse tends to outweigh the potential benefits. The costs of software reuse include establishing and maintaining a library of reusable components, searching for applicable components to be reused in a design, as well as adapting components toward a proper implementation. We introduce SPARTACAS, a framework for automating specification-based component retrieval and adaptation that has been successfully applied to synthesis of software for embedded and digital signal processing systems. Using specifications to abstractly represent implementations allows automated theorem-provers to formally verify logical reusability relationships between specifications. These logical relationships are used to evaluate the feasibility of reusing the implementations of components to implement a problem. Retrieving a component that is a complete match to a problem is rare. It is more common to retrieve a component that partially satisfies the requirements of a problem. Such components have to be adapted. Rather than adapting components at the code level, SPARTACAS adapts the behavior of partial matches by imposing interactions with other components at the architecture level. A subproblem is synthesized that specifies the missing functionality required to complete the problem; the subproblem is used to query the library for components to adapt the partial match. The framework was implemented and evaluated empirically, the results suggest that automated adaptation using architectures successfully promotes software reuse, and hierarchically organizes a solution to a design problem.     

需求损失下两产品联合生产动态批量决策及预测时阈

研究需求损失下两产品联合生产(采购)动态批量决策问题.在各周期成本变动情形下分析多周期动态批量决策的预测时阈和决策时阈,构建包含联合启动成本、两产品的单独启动成本、库存持有成本、变动生产成本和需求损失成本在内的成本最小化模型.在最优解结构特性的基础上,设计出前向动态规划算法求解问题,通过建立两产品生产点的单调性和建立生产集,给出求解预测时阈和决策时阈的充分条件.通过数值算例分析预测时阈求解的具体过程,表明所构建模型的有效性.     

An integrated expert system/operations research approach for the optimization of waste incinerator siting problems

This research aims at developing an integrated decision support system for the optimization of waste incinerator siting problems. In this integrated approach, both expert system and operations research techniques are used to model the siting problems of waste incinerator. Furthermore, an expert decision support system (EDSS) is implemented for the above problem and thus providing the decision makers a useful tool for decision-making. This EDSS is based on multi-criteria decision analysis in finding the best incinerator site by minimizing costs and environmental impacts. The proposed approach identifies a hierarchy of objectives for the siting problem. First of all, several potential sites need to be screened as a set of feasible alternative sites. Second, those alternative feasible sites will be further evaluated via the multi-criteria decision making methods. For the evaluation process, we solve a 0/1 combinatorial optimization problem at the upper level and proceed the multi-attribute utility function at the lower level to get the optimal solutions. An empirical application of a real world waste incinerator site selection existing in Taichung City, Taiwan is followed in the end. Computational results both of the cost minimization and of the whole systems are also provided.     

A behavioral analysis and verification approach to pattern-based design composition

Integrating software components to produce large-scale software systems is an effective way to reuse experience and reduce cost. However, unexpected interactions among components when integrated into software systems are often the cause of failures. Discovering these composition errors early in the development process could lower the cost and effort in fixing them. This paper introduces a rigorous analysis approach to software design composition based on automated verification techniques. We show how to represent, instantiate and integrate design components, and how to find design composition errors using model checking techniques. We illustrate our approach with a Web-based hypermedia case study.     

A Study of Uncertainty in Software Cost and Its Impact on Optimal Software Release Time

For a development software project, management often faces the dilemma of when to stop testing the software and release it for operation, which requires careful decision-making as it has great impact on both software reliability and project cost. In most existing research on optimal software release problem, the cost considered was the expected cost (EC) of the project. However, what management concerns is the actual cost (AC) of the project rather than the EC. Treatment (such as minimization) of the EC may not ensure a desired low level of the AC, due to the uncertainty (variability) involved in the AC. In this paper, we study the uncertainty in software cost and its impact on optimal software release time in detail. The uncertainty is quantified by the variance of the AC and several risk functions. A risk-control approach to optimal software release problem is proposed. New formulations of the problem which are extensions of current formulations are developed, and solution procedures are established. Several examples are presented. Results reveal that it seems crucial to take account of the uncertainty in software cost in optimal software release problem, otherwise unsafe decision may be reached which could be a false dawn to management.     

Strategy-;driven reuse: Bringing reuse from the Engineering Department to the Executive Boardroom

Organizations have predominantly utilized reuse in Engineering Departments for the purposes of reducing the cost and improving the quality of the software they develop. While these strategies have been successful, we believe that the full potential of reuse can only be tapped when reuse is brought to the Executive Boardroom as well. We propose that organizations tap reuse not only for cutting costs, but also for strategic and wide-;ranging business initiatives such as entering new markets, increasing agility in response to a dynamic marketplace, and competitive positioning and advantage. In order to do so effectively, organizations must harness the potential of reuse by migrating reuse into the company's business and product-;line planning processes. We present a framework for analyzing and changing reuse business practices. Such practices include cost-;reduction reuse, when the organization utilizes reuse for cost savings purposes; reuse-;enabled business, when the organization uses reuse to create new business opportunities; and strategy-;driven reuse, when the organization incorporates reuse in the formulation of its business and product-;line strategy for the purposes of obtaining competitive positioning and advantage. To determine whether or not reuse is the proper software development strategy to pursue, we utilize concepts in competitive software engineering, an integrated approach to software development that is attuned to the competitive demands of the marketplace. First, a framework is established by identifying and analyzing the organization's goals, strengths, and limitations, its market and its competitive environment. Based on these analyses, possible business or product strategies are formulated and one or more are chosen that help achieve the organization's goals. Finally, a development strategy is chosen. Following this choice, each step of the decision cycle should be re-;evaluated to ensure that it is consistent with the chosen development strategy.     

A variable-grouping based genetic algorithm for large-scale integer programming

To effectively reduce the dimensionality of search space, this paper proposes a variable-grouping based genetic algorithm (VGGA) for large-scale integer programming problems (IPs). The VGGA first groups IP’s decision variables based on the optimal solution to the IP’s continuous relaxation problem, and then applies a standard genetic algorithm (GA) to the subproblem for each group of variables. We compare the VGGA with the standard GA and GAs based on even variable-grouping by applying them to solve randomly generated convex quadratic knapsack problems and integer knapsack problems. Numerical results suggest that the VGGA is superior to the standard GA and GAs based on even variable-grouping both on computation time and solution quality.     

考虑道路扩建的区域物流网络设计优化模型

通过对区域物流网络中边、点上费用、容量、流量等的分析,结合实际问题中对道路扩建和物流设施容量设计决策的需要,构建基于物流时间需求的区域物流网络设计数学模型。模型以最小化物流网络构建成本、初期运营成本和物流时间需求惩罚成本为目标,基于网络中物流量的特征给出了约束条件,分析模型的特点开发了改进的拉格朗日松弛算法并予以求解。计算机软件对模型和算法的仿真给出了物流网络构建中各项成本之间的关系,验证了模型和算法的有效性和实用性。     

Optimal price and order size for a reseller under partial backordering

The problem of determining the optimal price and lot size for a reseller is considered in this paper. It is assumed that demand can be backlogged and that the selling price is constant within the inventory cycle. The backlogging phenomenon is modeled without using the backorder cost and the lost sale cost since these costs are not easy to estimate in practice. The case in which the selling price is fixed and therefore, demand is a known constant is also considered. Given the new way of modeling the backlogging phenomenon, the results for the case of constant demand are developed. Analysis is also presented for the reselling situation in which a nonperishable product is sold.Scope and purposePerishable products constitute a sizable component of inventories. A common question in a reselling situation involving a perishable (or a nonperishable) product is: What should be the size of the replenishment? If demand for the product is sensitive to price, then another question is: What should be the selling price? Although the ability to vary price within an inventory cycle is important, in many cases, the reseller may opt for a policy of constant selling price for administrative convenience. In this paper the pricing and/or lot sizing problem faced by a reseller is modeled assuming a general deterioration rate and a general demand function. The model allows for backlogging of demand. When a product is highly perishable, the reseller may need to backlog demand to contain costs due to deterioration. In this sense, perishability and backlogging are complementary conditions. Given that the problem entails revenue and costs, a natural objective function for the model is profit per period. The conventional approach to modeling the backlogging phenomenon requires the use of the backorder cost and the lost sale cost. These costs, however, are difficult to estimate in practice. A new approach is used in which customers are considered impatient. Hence the fraction of demand that gets backlogged at a given point in time is a decreasing function of waiting time. First the subproblem in which price is fixed is solved to determine the optimal inventory policy. The subproblem represents the important case in which the reseller has no flexibility to change the selling price. Then a procedure is developed for determining the optimal quantity and the selling price for the broader problem. The procedure can be implemented on a spreadsheet.     

A dynamic software release model

The determination of optimal software release times constitutes an interesting decision making problem which involves the stochastic structure of the underlying software reliability model, as well as various cost parameters. There is an apparent tradeoff between testing the software further to improve its reliability, and releasing it for operational use to decrease the costs. We propose and analyze in depth a new dynamic model with sufficient generality. After each failure, a debugging activity, possibly imperfect, is undertaken and a decision is made regarding the duration of additional testing. If no failure is observed during this time, then the software is released. Otherwise, the failure is debugged and the decision process is repeated in a dynamic fashion. The problem is formulated using dynamic programming and interesting characterizations of the optimal release policy are presented. The dynamic solution procedure is demonstrated by some numerical illustrations.     

A Case Study on Implementing Modularity in Software Development

In today’s business world, firms are facing pressures to reduce costs, enhance productivity, and maintain quality in new product development. Past studies have provided evidence that modularity can enhance performance of new product development. However, real-life cases on how to implement the concept of modularity are limited. This article aims to propose a model for modularity implementation in the context of embedded software development. The model was applied in a software company in Hong Kong. Results from the case company provide evidence that the average reuse rate of software modules increased from 31% to 71% after the implementation, with productivity increasing by 258%, cost reducing by 70%, and quality increasing by 72%. The practical implications are finally discussed.     

Managing Software Reuse Economics: An Integrated ROI-based Model

Several cost models have been proposed in the past for estimating, predicting, and analyzing the costs of software reuse. In this paper we propose an integrated ROI-based cost model which attempts to encompass existing models. Our approach is to analyze existing models, identify their dimensions of variance, classify the models along these dimensions, then provide an integrated cost model that makes explicit provisions for these dimensions of variance. In this paper, we also discuss in what sense our model encompasses existing models, present a prototype that supports the cost model, and illustrate the model with a sample example.     

On optimization of finite-difference time-domain (FDTD) computation on heterogeneous and GPU clusters

A model for the computational cost of the finite-difference time-domain (FDTD) method irrespective of implementation details or the application domain is given. The model is used to formalize the problem of optimal distribution of computational load to an arbitrary set of resources across a heterogeneous cluster. We show that the problem can be formulated as a minimax optimization problem and derive analytic lower bounds for the computational cost. The work provides insight into optimal design of FDTD parallel software. Our formulation of the load distribution problem takes simultaneously into account the computational and communication costs. We demonstrate that significant performance gains, as much as 75%, can be achieved by proper load distribution.     

H2 near-optimal model reduction

This note considers the problem of finding a stable reduced-order model for a given stable model so that its H₂ model reduction cost differs by less than a prescribed error from the optimal cost, which may or may not be achievable. It is shown that this new version of the long-standing H₂ optimal model reduction problem can be reduced to a well-posed smooth constrained minimization problem whose global solution is guaranteed to exist. In addition, a globally convergent algorithm in the form of an ordinary differential equation is derived     

Mixed coordination method for long-horizon optimal control problems

We present a new approach to solving long-horizon, discrete-time optimal control problems using the mixed coordination method. The idea is to decompose a long-horizon problem into subproblems along the time axis. The requirement that the initial state of a subproblem equal the terminal state of the preceding subproblem is relaxed by using Lagrange multipliers. The Lagrange multipliers and initial state of each subproblem are then selected as high-level variables. The equivalence of the two-level formulation and the original problem is proved for both convex and non-convex cases. The low-level subproblems are solved in parallel using extended differential dynamic programming (DDP). An efficient way to find the gradient and hessian of a low-level objective function with respect to high-level variables is developed. The high-level problem is solved using the modified Newton method. An effective procedure is developed to select initial values of multipliers based on the initial trajectory. The method can convexify the high-level problem while maintaining the separability of an originally non-convex problem. The method performs better and faster than one-level DDP for both convex and non-convex test problems.     

基于构件和总线集成的业务基础平台框架研究

为了提高软件复用的灵活性和软件的开发效率,提出了一个基于构件和总线集成的业务基础平台框架（CBBF）,以结构级的构件定制和复用生成业务过程,以体系结构支撑和集成软件系统。阐述了基于业务基础平台的开发模式;设计了CBBF的体系结构;分析了CBBF实现的关键设计,包括XML总线集成的内核引擎、构件分类、构件模型的形式化描述和构件组装;给出了CBBF的实现细节。实践表明CBBF可以简化软件开发过程,大幅提高软件开发效率。     

非基于软件复用的成本估算模型的复用改造模型及模型系数修正策略

作为软件成本控制管理的重要措施,软件开发成本的估算技术已经成为软件工程领域的一个重要课题。当前基于复用的软件开发正在成为软件工程的主流,但将软件复用考虑进成本估算的模型较少。提出一个基于软件复用的成本估算模型,并应用该模型对COCOMO模型进行复用改造,之后通过实例进行验证。给出了使用存储过程技术对模型参数进行修正的策略,以为各类基于复用的软件开发成本估算提供依据。     

A model and methodologies for the location problem with logistical components

This paper significantly extends traditional facility location models by introducing several logistical cost components such as holding, ordering, and transportation costs in a multi-commodity, multi-location framework. Since location and logistical costs are highly inter-related, the paper provides an integrated model, and seeks to minimize total physical distribution costs by simultaneously determining optimal locations, flows, shipment compositions, and shipment cycle times. Two sophisticated heuristic methodologies, based on Lagrangian relaxation and simulated annealing, respectively, are provided and compared in an extensive computational experiment.Scope and purposeLogistics has recently acquired great significance in industry, in part due to the rapidly growing interest in Supply Chain Management. One of the important open issues in logistics is the effective integration of logistical cost components such as transportation cost with facility location models, since the two are highly inter-related in practice. In particular, locations, flows, shipment compositions, and shipment cycle times are highly inter-dependent. The determination of optimal values of these variables is crucial for minimizing physical distribution costs. This paper proposes an integrated location–consolidation model and provides two sophisticated methodologies to solve the problem. The relative performance of the two methodologies is investigated in an extensive computational experiment.     

Model for Facilities or Vendors Location in a Global Scale Considering Several Echelons in the Chain

The facilities location problem for companies with global operations is very complex and not well explored in the literature. This work proposes a MILP model that solves the problem through minimization of the total logistic cost. Main contributions of the model are the pioneer carrying cost calculation, the treatment given to the take-or-pay costs and to the international tax benefits such as drawback and added value taxes in Brazil. The model was successfully applied to a real case of a chemical industry with industrial plants and sales all over the world. The model application recommended a totally new sourcing model for the company.