Software reuse: ostriches beware

When it comes to software reuse, many software executives, like ostriches, are pushing their heads deeper into the sand. The author discusses some active reuse programs in several companies. The number of companies employing active reuse is high enough to establish that reuse on this scale is possible at the current state of the software art     

An empirical study of a software reuse reference model

In software engineering there is a need for technologies that will significantly decrease effort in developing software products, increase quality of software products and decrease time-to-markets. The software development industry can be improved by utilizing and managing software reuse with an “empirically validated reference model” that can be customized for different kinds of software development enterprises. Our research thesis is that software development based on a software reuse reference model improves the competitive edge and time-to-market of many software development enterprises. The definition and study of such a model has been carried out using four steps. First, the reference model developed here is based on the existing software reuse concepts. Second, this reference model is an empirical study which uses both legacy studies and lessons learned studies. Third, the impact of the reference model on software development effort, quality, and time-to-market is empirically derived. Fourth, an initial set of successful cases, which are based on the software reuse reference model utilization, are identified. The main contribution of this paper is a reference model for the practice of software reuse. A secondary contribution is an initial set of cases from software development enterprises which are successful in the practice of reuse in terms of decreased effort, increased quality and a high correlation in their application of our software reuse reference model activities.     

Software reuse at Motorola

High initial costs and a slow return on investment can make software reuse a tough sell. The author chronicles the ups and downs of implementing software reuse in a corporation that, despite its bottom-up, grass-roots culture, enlisted top management's intervention to proceed. Based on experience, she recommends that any group trying to implement reuse should first get support from top management and provide reuse training for engineers; second, provide incentives to support the program until reuse becomes part of the culture; and third, provide tools to help engineers     

An empirical study of software reuse with special attention to Ada

Over the past several decades, numerous software technologies have been developed for overcoming the software crisis. Among these technologies, reuse has been recognized as one of the most important software technologies. Recently, it has gained substantial attention as a possible solution to the software crisis in Ada and other software communities. The purpose of this empirical study is to examine how organizations actually exploit reuse technologies and evaluates how reuse factors affect the rate of reuse in an organization. This study is an attempt to enhance the measurement of the rate of reuse and the effectiveness of reuse by establishing conceptual foundations in the literature for reuse and conducting an empirical investigation of organizations using Ada technology. This study differentiated software reuse into six criteria: domain, human, tool, organization, software metrics, and environment. The results of this study show that the rate of reuse significantly depends upon reuse capability, software development effort, object-oriented design capability, repository development effort, Ada technology capability, and domain capability     

Software reuse: The Brazilian industry scenario

This paper aims at identifying some of the key factors in adopting an organization-wide software reuse program. The factors are derived from practical experience reported by industry professionals, through a survey involving 57 Brazilian small, medium and large software organizations. Some of them produce software with commonality between applications, and have mature processes, while others successfully achieved reuse through isolated, ad hoc efforts. The paper compiles the answers from the survey participants, showing which factors were more associated with reuse success. Based on this relationship, a guide is presented, pointing out which factors should be more strongly considered by small, medium and large organizations attempting to establish a reuse program.     

Software reuse research: status and future

This paper briefly summarizes software reuse research, discusses major research contributions and unsolved problems, provides pointers to key publications, and introduces four papers selected from The Eighth International Conference on Software Reuse (ICSR8).     

Software reuse in-the-small: automating group rewarding

In this paper we present a model-independent, multi-level, closed loop approach to software reuse that makes tuning of reuse systems mostly automatic, and includes a reward system for development of reusable components. The proposed techniques are shown to be suitable for development in-the-small by fixing some locally measured reuse coefficients for small teams.     

Software reuse in product populations

Consumer products are becoming increasingly software intensive. The software complexity of individual products grows, while the diversity of products increases and the lead time must decrease. Software reuse is the answer to this, not only within a family but also between families of consumer products. We have devised an approach based upon a software component technology to enable reuse. This paper describes that approach, and it zooms in on two important aspects of component-based development. One aspect concerns the prediction of system properties from properties of components, which we illustrate using thread synchronization as example. The other aspect concerns branching of our software in our configuration management systems, where our analysis leads to the discovery that we may be constantly rewriting our own code and to the definition of the turn-over factor to quantify this. We end this paper with a brief validation of our approach.     

An oblique-extrema-based approach for empirical mode decomposition

It has been found that envelopes established by extrema in the empirical mode decomposition cannot always depict the local characteristics of a signal very well. This is due in part to the slight oscillations characterized as hidden scales which are almost left untreated during the sifting process. When involving hidden scales, the intrinsic mode function usually contains at a given instance multiple oscillation modes. In view of this, based on inflection points this paper presents a new decomposition algorithm called ‘oblique-extrema empirical mode decomposition’ to settle these problems. With this algorithm, any signal can be decomposed into a finite number of ‘oblique-extrema intrinsic mode functions’ which may possess better-behaved Hilbert transforms and produce more accurate instantaneous frequencies. It can suppress the effect of hidden scales and gets one step further in extracting finer scales. Experimental results demonstrate good performances of this new method.     

An empirical approach to studying software evolution

With the approach of the new millennium, a primary focus in software engineering involves issues relating to upgrading, migrating, and evolving existing software systems. In this environment, the role of careful empirical studies as the basis for improving software maintenance processes, methods, and tools is highlighted. One of the most important processes that merits empirical evaluation is software evolution. Software evolution refers to the dynamic behaviour of software systems as they are maintained and enhanced over their lifetimes. Software evolution is particularly important as systems in organizations become longer-lived. However, evolution is challenging to study due to the longitudinal nature of the phenomenon in addition to the usual difficulties in collecting empirical data. We describe a set of methods and techniques that we have developed and adapted to empirically study software evolution. Our longitudinal empirical study involves collecting, coding, and analyzing more than 25000 change events to 23 commercial software systems over a 20-year period. Using data from two of the systems, we illustrate the efficacy of flexible phase mapping and gamma sequence analytic methods, originally developed in social psychology to examine group problem solving processes. We have adapted these techniques in the context of our study to identify and understand the phases through which a software system travels as it evolves over time. We contrast this approach with time series analysis. Our work demonstrates the advantages of applying methods and techniques from other domains to software engineering and illustrates how, despite difficulties, software evolution can be empirically studied     

支持地球科学的软件复用(英文)

地球科学研究中数据的准备、分发、访问、处理和分析都依赖于计算机软件。科学结果的重复通常需要复用同样的软件。同样,科学数据的有效分发、访问或者分析也都需要进行软件复用。地球科学软件开发社区已经意识到了软件复用的价值,并且在社区内大力鼓励和培育软件复用。因此,他们成立了 NASA 地球科学数据系统( ESDS) 软件复用工作组( WG) 来支持社区成员之间的软件复用。工作组开发了软件复用门户来发布软件复用相关的信息、资源,并且提供培训来提高和改进整个社区的软件复用实践。工作组还开发了一个复用支持系统( RES) 原型系统来支持可复用软件的访问。此外, 工作组还制定了复用成熟度级别, 从而提高了评估和选择可复用软件的能力。     

基于PowerBuilder的软件重用研究

研究了基于PowerBuilder软件的重用技术,通过PowerBuilder对象重用、全局函数重用和外部对象重用这三个方面实现软件重用,应用PowerBuilder软件重用技术能提高软件开发效率,设计出高质量、低成本的软件系统。     

A performance comparison of event calendar algorithms: An empirical approach

We propose a suite of tests based on two-state Markov chains for experimentally assessing the dynamic performance of a variety of simulation event calendar implementations. In contrast to previous studies based on the standard hold model for evaluation of performance statically, the proposed Markov hold model is more general and can be used to examine how different implementations respond dynamically to dependent sequences of insertion and deletion requests. The Markov hold model is used to conduct tests based on random, stressed, and correlated input sequences of requests, with performance measures including completion times, sensitivity to correlations, sensitivity to duplication, and efficiency of data-handling. We apply these tests to fourteen different event calendar implementations. To demonstrate the utility of the proposed model, we also include a comparison of the event calendar algorithms on a token ring protocol with bursty Markovian packet-traffic.     

Evaluating machine learning classification for financial trading: An empirical approach

Technical and quantitative analysis in financial trading use mathematical and statistical tools to help investors decide on the optimum moment to initiate and close orders. While these traditional approaches have served their purpose to some extent, new techniques arising from the field of computational intelligence such as machine learning and data mining have emerged to analyse financial information. While the main financial engineering research has focused on complex computational models such as Neural Networks and Support Vector Machines, there are also simpler models that have demonstrated their usefulness in applications other than financial trading, and are worth considering to determine their advantages and inherent limitations when used as trading analysis tools. This paper analyses the role of simple machine learning models to achieve profitable trading through a series of trading simulations in the FOREX market. It assesses the performance of the models and how particular setups of the models produce systematic and consistent predictions for profitable trading. Due to the inherent complexities of financial time series the role of attribute selection, periodic retraining and training set size are discussed in order to obtain a combination of those parameters not only capable of generating positive cumulative returns for each one of the machine learning models but also to demonstrate how simple algorithms traditionally precluded from financial forecasting for trading applications presents similar performances as their more complex counterparts. The paper discusses how a combination of attributes in addition to technical indicators that has been used as inputs of the machine learning-based predictors such as price related features, seasonality features and lagged values used in classical time series analysis are used to enhance the classification capabilities that impacts directly into the final profitability.     

An empirical semantics approach to reasoning about communication

When designing multiagent systems, one can often avail of an existing specification of communication rules (in the form of protocols, ACL semantics, etc.). The question that then arises naturally is how to design appropriate agents to operate on such a specification. Moreover, if the multiagent system in question exhibits the characteristics of an open system, the problem is complicated even further by the fact that adherence to a supposedly agreed specification cannot be ensured on the side of other agents.This paper presents an architecture for dealing with a generic type of pre-specified communication patterns (containing surface structure and logical constraint specifications) based on an empirical semantics model of communication. By combining existing expectations about the use of communication with empirical observation, this model allows for a flexible adaptation to evolving communication semantics.The architecture itself is based on the InFFrA social reasoning framework and the concept of interaction frames. When interpreted according to the empirical semantics approach, interaction frames that represent classes of interaction situations can be used to conduct decision-theoretic reasoning about communication.After introducing the abstract architecture and giving a formal model for its probabilistic semantics, the results of an experimental validation of the approach in a complex domain are presented to illustrate its effectiveness.     

An unconstrained optimization approach to empirical mode decomposition

Empirical mode decomposition (EMD) is an adaptive (data-driven) method to decompose non-linear and non-stationary signals into AM-FM components. Despite its well-known usefulness, one of the major EMD drawbacks is its lack of mathematical foundation, being defined as an algorithm output. In this paper we present an alternative formulation for the EMD method, based on unconstrained optimization. Unlike previous optimization-based efforts, our approach is simple, with an analytic solution, and its algorithm can be easily implemented. By making no explicit use of envelopes to find the local mean, possible inherent problems of the original EMD formulation (such as the under- and overshoot) are avoided. Classical EMD experiments with artificial signals overlapped in both time and frequency are revisited, and comparisons with other optimization-based approaches to EMD are made, showing advantages for our proposal both in recovering known components and computational times. A voice signal is decomposed by our method evidencing some advantages in comparison with traditional EMD and noise-assisted versions. The new method here introduced catches most flavors of the original EMD but with a more solid mathematical framework, which could lead to explore analytical properties of this technique.     

Semantic enrichment process: An approach to software component reuse in modernizing enterprise systems

In today’s dynamic business environments, organizations are under pressure to modernize their existing software systems in order to respond to changing business demands. Service oriented architectures provide a composition framework to create new business functionalities from autonomous building blocks called services, enabling organizations to quickly adapt to changing conditions and requirements. Characteristics of services offer the promise of leveraging the value of enterprise systems through source code reuse. In this respect, existing system components can be used as the foundation of newly created services. However, one problem to overcome is the lack of business semantics to support the reuse of existing source code. Without sufficient semantic knowledge about the code in the context of business functionality, it would be impossible to utilize source code components in services development. In this paper, we present an automated approach to enrich source code components with business semantics. Our approach is based on the idea that the gap between the two ends of an enterprise system—(1) services as processes and (2) source code—can be bridged via similarity of data definitions used in both ends. We evaluate our approach in the framework of a commercial enterprise systems application. Initial results indicate that the proposed approach is useful for annotating source code components with business specific knowledge.