A program design language based software maintenance tool

Program design languages are an increasingly important method of expressing the detailed design of a software system. Such languages can be modelled using a data structure known as a semantic net. This paper describes a maintenance tool for program design languages based on such a data structure. The tool allows the user to interrogate a semantic net using an interactive procedural language in order to derive information necessary for software maintenance. The technique upon which this tool is based is applicable to the maintenance of activities throughout the software lifecycle.     

An approach to optimizing software development team size

This paper explores the relationship between software size, development effort and team size. We propose an approach aimed at finding the team size where the project effort has its minimum. The approach was applied to the ISBSG repository containing nearly 4000 software projects. Based on the results we provide our recommendation for the optimal or near-optimal team size in seven project groups defined by four project properties.     

On the conversion between IFPUG and COSMIC software functional size units: A theoretical and empirical study

Since 1984 the International Function Point Users Group (IFPUG) has produced and maintained a set of standards and technical documents about a functional size measurement methods, known as IFPUG, based on Albrecht function points. On the other hand, in 1998, the Common Software Measurement International Consortium (COSMIC) proposed an improved measurement method known as full function points (FFP). Both the IFPUG and the COSMIC methods both measure functional size of software, but produce different results. In this paper, we propose a model to convert functional size measures obtained with the IFPUG method to the corresponding COSMIC measures. We also present the validation of the model using 33 software projects measured with both methods. This approach may be beneficial to companies using both methods or migrating to COSMIC such that past data in IFPUG can be considered for future estimates using COSMIC and as a validation procedure.     

Adaptive ridge regression system for software cost estimating on multi-collinear datasets

Cost estimation is one of the most critical activities in software life cycle. In past decades, a number of techniques have been proposed for cost estimation. Linear regression is yet the most frequently applied method in the literature. However, a number of studies point out that linear regression is prone to low prediction accuracy. The low prediction accuracy is due to a number of reasons such as non-linearity and non-normality. One less addressed reason is the multi-collinearities which may lead to unstable regression coefficients. On the other hand, it has been reported that multi-collinearity spreads widely across the software engineering datasets. To tackle this problem and improve regression's accuracy, we propose a holistic problem-solving approach (named adaptive ridge regression system) integrating data transformation, multi-collinearity diagnosis, ridge regression technique and multi-objective optimization. The proposed system is tested on two real world datasets with the comparisons with OLS regression, stepwise regression and other machine learning methods. The results indicate that adaptive ridge regression system can significantly improve the performance of regressions on multi-collinear datasets and produce more explainable results than machine learning methods.     

Robust background maintenance by estimating global intensity level changes for dynamic scenes

The maintenance of relevant backgrounds under various scene changes is very crucial to detect foregrounds robustly. We propose a background maintenance method for dynamic scenes including global intensity level changes caused by changes of illumination conditions and camera settings. If the global level of the intensity changes abruptly, the conventional background models cannot discriminate true foreground pixels from the background. The proposed method adaptively modifies the background model by estimating the level changes. Because there are changes caused by moving objects as well as global intensity level changes, we estimate the dominant level change over the whole image regions by mean shift. Then, the problem caused by saturated pixels are handled by an additional scheme. In the experiments for dynamic scenes, our proposed method outperforms previous methods by adaptive background maintenance and handling of saturated pixels.     

An investigation of the maintenance and support characteristics of commercial software

This study demonstrates an objective method used to evaluate the enhanceability of commercial software. It examines the relationship between enhancement and repair, and suggests that enhancement be considered when developing formal models of defect cause. Another definition of defect-prone software is presented that concentrates attention on software that requires unusually high repair considering the magnitude of planned enhancement.     

VIFOR: A tool for software maintenance

VIFOR is a software tool oriented towards maintenance of medium-to-large Fortran77 programs. With VIFOR, programs can be displayed and edited in two forms: as the code and as the graph. VIFOR also contains transformations in both directions, i.e. from code to graph and from graph to skeletons of code. Hence, it is suitable for re-engineering and maintenance of existing code. Specially designed browsers implement the graphical interface. VIFOR contains a database that is based on a simple but effective data model of Fortran programs. The model contains only four entity classes and three relations, which makes the tool small, and easy to implement and use. A simple query language allows browsing through the database.     

An overview of time-based and condition-based maintenance in industrial application

This paper presents an overview of two maintenance techniques widely discussed in the literature: time-based maintenance (TBM) and condition-based maintenance (CBM). The paper discusses how the TBM and CBM techniques work toward maintenance decision making. Recent research articles covering the application of each technique are reviewed. The paper then compares the challenges of implementing each technique from a practical point of view, focusing on the issues of required data determination and collection, data analysis/modelling, and decision making. The paper concludes with significant considerations for future research. Each of the techniques was found to have unique concepts/principles, procedures, and challenges for real industrial practise. It can be concluded that the application of the CBM technique is more realistic, and thus more worthwhile to apply, than the TBM one. However, further research on CBM must be carried out in order to make it more realistic for making maintenance decisions. The paper provides useful information regarding the application of the TBM and CBM techniques in maintenance decision making and explores the challenges in implementing each technique from a practical perspective.     

A virtual collaborative maintenance architecture for manufacturing enterprises

This paper presents a virtual collaborative maintenance architecture aimed at improving the performance of manufacturing systems. The proposed architecture incorporates maintenance elements such as operational reliability, maintenance economics, human factors in maintenance, maintenance program, and maintenance optimization in a virtual collaborative architecture. An analytical model is proposed to measure the relative performance of the proposed virtual collaborative architecture as well as that of the manufacturing enterprise. A numerical example is also presented to demonstrate the application of the proposed approach.     

Design and implementation of a knowledge-based decision support system for estimating software development work-effort

Up to now, the assessment of work-effort in software engineering is based on statistical methods. Among the best known are COCOMO (Boehm [2]) or SPQR (Jones [6]). Nevertheless it is generally recognized that many qualitative factors enter into the cost of development, such as effectiveness of the team, user's motivation, and accuracy of the specifications. We have designed a Decision Support System (DSS) for estimating the work-effort, in which the processing of the qualitative data is made by an expert system while a function points analysis provides the theoretical work-effort according to the type of software and the past experience. The evaluation is performed at two levels: global and detailed. The global evaluation is made at the beginning of the development according to the data that are, at this moment, available. The detailed evaluation takes place when the design of the software becomes more precise. The software manager can follow the evolution of the changes at the detailed level during the development.In software development, project leaders mostly reason by using their past experience. It therefore follows that a DSS must contain a learning process. We have accordingly designed our system to record the data of the completed developments. These data serve for the new evaluations. At the end of each project, the learning module examines to what extent the already-recorded information must be updated. Thus our system combines statistic data and knowledge-based reasonings.     

RATSNO—an experiment in software adaptability

Adaptable programs are one of the benefits of structured programming. The adaptability of a program is the degree to which it can be transformed into another program that performs a similar, but slightly different, function. While it is clear that the aims of structured programming are best satisfied by the use of modern programming languages, a great number of programmers must use languages such as Fortran. To alleviate this situation, a number of preprocessors have been introduced that give Fortran a more structured facade. This paper describes an experiment performed to test the adaptability of programs written in RATFOR, one of these preprocessors. Judging from the results, the use of a good preprocessor can significantly increase the adaptability of Fortran programs.     

A software integration approach for designing and assessing dependable embedded systems

Embedded systems increasingly entail complex issues of hardware-software (HW-SW) co-design. As the number and range of SW functional components typically exceed the finite HW resources, a common approach is that of resource sharing (i.e., the deployment of diverse SW functionalities onto the same HW resources). Consequently, to result in a meaningful co-design solution, one needs to factor the issues of processing capability, power, communication bandwidth, precedence relations, real-time deadlines, space, and cost. As SW functions of diverse criticality (e.g. brake control and infotainment functions) get integrated, an explicit integration requirement need is to carefully plan resource sharing such that faults in low-criticality functions do not affect higher-criticality functions.On this background, the main contribution of this paper is a dependability-driven framework that helps to conduct the integration of SW components onto HW resources such that the maintenance of system dependability over integration of diverse criticality components is assured by design.We first develop a clustering strategy for SW components into Fault Containment Modules (FCMs) such that error propagation via interaction is minimized. Subsequently, the rules of composition for FCMs with respect to error propagation are developed. To allocate the resulting FCMs to the existing HW resources we provide several heuristics, each optimizing particular attributes thereof. Further, a framework for assessing the goodness of the achieved HW-SW composition as a dependable embedded system is presented. Two new techniques for quantifying the goodness of the proposed mappings are introduced by examples, both based on a multi-criteria decision theoretic approach.     

Software maintenance outsourcing: Issues and strategies

Software maintenance outsourcing is becoming a popular alternative in software industry. Software companies are looking at outsourcing their maintenance and support activities as an area for competitive advantage. There are risks and benefits of introducing subcontractors in the framework of software outsourcing. Reliable maintenance is only possible if adequate measures are taken in advance during project’s development and maintenance planning phase and are documented in the maintenance contract. In this paper, we present and make a justification for a set of recommendations to make such maintenance reliable and cost-effective. We analyze the associated risks and propose some product quality metrics to be monitored during the maintenance phase.     

计算机实验室的管理与维护

本文从计算机机房的管理与维护方面阐述了如何科学的、有效的管理计算机机房,从而为学生学习计算机技术提供良好的学习环境。要保障计算机实践教学,提高教学质量,就必须搞好计算机实验室的管理与维护工作,机房管理与维护主要包括设备的管理和软件及数据的管理与维护。     

浅谈医院信息系统的维护和网络安全管理

随着信息技术的不管发展,医院网络化管理已经成为一种新的趋势。医院信息系统HIS的大规模使用,极大地提高了医务人员的工作效率,带来巨大的经济利益的同时,也为患者带来方便,节省了时间。HIS系统已经成为现代化医院运营必不可少的基础设施,如何构建一个科学、安全的HIS系统成为需要考虑的重要问题。本文从硬件和软件两个方面,分析了医院信息系统的维护和网络安全管理措施。     

Dynamic scheduling of maintenance tasks in the petroleum industry: A reinforcement approach

Petroleum industry production systems are highly automatized. Maintenance of such systems is vital, not only to maintain production efficiency but also to insure minimal safety levels. Maintenance task scheduling is difficult since some tasks are already identified because they must be done repeatedly, and other tasks need to be identified dynamically. In this paper, we present a multi-agent approach for the dynamic maintenance task scheduling for a petroleum industry production system. Agents simultaneously insure effective maintenance scheduling and the continuous improvement of the solution quality by means of reinforcement learning, using the SARSA algorithm. Reinforcement learning allows the agents to adapt, learning the best behaviors for their various roles without reducing the performance or reactivity. To demonstrate the innovation of our approach, we include a computer simulation of our model and the results of experimentation applying our model to an Algerian petroleum refinery.     

Evaluating the productivity of a reference-based programming approach: A controlled experiment

ContextDomain engineering aims at facilitating software development in an efficient and economical way. One way to measure that is through productivity indicators, which refer to the ability of creating a quality software product in a limited period and with limited resources. Many approaches have been devised to increase productivity; however, these approaches seem to suffer from a tension between expressiveness on the one hand, and applicability (or the lack of it) in providing guidance for developers.ObjectiveThis paper evaluates the applicability and efficiency of adopting a domain engineering approach, called Application-based DOmain Modeling (ADOM), in the context of the programming task with Java, and thus termed ADOM-Java, for improving productivity in terms of code quality and development time.MethodTo achieve that objective we have qualitatively evaluate the approach using questionnaires and following a text analysis procedure. We also set a controlled experiment in which 50 undergraduate students performed a Java-based programming task using either ADOM-Java or Java alone.ResultsThe qualitative evaluation reveal that the approach is easy to uses and provides valuable guidance. Nevertheless, it requires training. The outcomes of the experiment indicate that the approach is applicable and that the students that used ADOM-Java achieved better code quality, as well as better functionality and within less time than the students who used only Java.ConclusionThe results of the experiments imply that by providing a code base equipped with reuse guidelines for programmers can increase programming productivity in terms of quality and development time. These guidelines may also enforce coding standards and architectural design.     

Software complexity and software maintenance: A survey of empirical research

A number of empirical studies have pointed to a link between software complexity and software maintenance performance. The primary purpose of this paper is to document what is known about this relationship, and to suggest some possible future avenues of research. In particular, a survey of the empirical literature in this area shows two broad areas of study: complexity metrics and comprehension. Much of the complexity metrics research has focused on modularity and structure metrics. The articles surveyed are summarized as to major differences and similarities in a set of detailed tables. The text is used to highlight major findings and differences, and a concluding remarks section provides a series of recommendations for future research.     

The value of software sizing

Context

One of the difficulties faced by software development Project Managers is estimating the cost and schedule for new projects. Previous industry surveys have concluded that software size and cost estimation is a significant technical area of concern. In order to estimate cost and schedule it is important to have a good understanding of the size of the software product to be developed. There are a number of techniques used to derive software size, with function points being amongst the most documented.

Objective

In this paper we explore the utility of function point software sizing techniques when applied to two levels of software requirements documentation in a commercial software development organisation. The goal of the research is to appraise the value (cost/benefit) which functional sizing techniques can bring to the project planning and management of software projects within a small-to-medium sized software development enterprise (SME).

Method

Functional counts were made at the bid and detailed functional specification stages for each of five commercial projects used in the research. Three variants of the NESMA method were used to determine these function counts. Through a structured interview session, feedback on the sizing results was obtained to evaluate its feasibility and potential future contribution to the company.

Results

The results of our research suggest there is value in performing size estimates at two appropriate stages in the software development lifecycle, with simplified methods providing the optimal return on effort expended.

Conclusion

The ‘Estimated NESMA’ is the most appropriate tool for use in size estimation for the company studied. The use of software sizing provides a valuable contribution which would augment, but not replace, the company’s existing cost estimation approach.