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.     

MSR4SM: Using topic models to effectively mining software repositories for software maintenance tasks

ContextMining software repositories has emerged as a research direction over the past decade, achieving substantial success in both research and practice to support various software maintenance tasks. Software repositories include bug repository, communication archives, source control repository, etc. When using these repositories to support software maintenance, inclusion of irrelevant information in each repository can lead to decreased effectiveness or even wrong results.ObjectiveThis article aims at selecting the relevant information from each of the repositories to improve effectiveness of software maintenance tasks.MethodFor a maintenance task at hand, maintainers need to implement the maintenance request on the current system. In this article, we propose an approach, MSR4SM, to extract the relevant information from each software repository based on the maintenance request and the current system. That is, if the information in a software repository is relevant to either the maintenance request or the current system, this information should be included to perform the current maintenance task. MSR4SM uses the topic model to extract the topics from these software repositories. Then, relevant information in each software repository is extracted based on the topics.ResultsMSR4SM is evaluated for two software maintenance tasks, feature location and change impact analysis, which are based on four subject systems, namely jEdit, ArgoUML, Rhino and KOffice. The empirical results show that the effectiveness of traditional software repositories based maintenance tasks can be greatly improved by MSR4SM.ConclusionsThere is a lot of irrelevant information in software repositories. Before we use them to implement a maintenance task at hand, we need to preprocess them. Then, the effectiveness of the software maintenance tasks can be improved.     

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.     

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.     

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.     

Investigating software testing and maintenance reports: Case study

ContextAlthough many papers have been published on software development and defect prediction techniques, problem reports in real projects quite often differ from those described in the literature. Hence, there is still a need for deeper exploration of case studies from industry.ObjectiveThe aim of this study is to present the impact of fine-grained problem reports on improving evaluation of testing and maintenance processes. It is targeted at projects involving several releases and complex schemes of problem handling. This is based on our experience gained while monitoring several commercial projects.MethodExtracting certain features from detailed problem reports, we derive various measures and present analysis models which characterize and visualize the effectiveness of testing and problem resolution processes. The considered reports describe types of problems (e.g. defects), their locations in project versions and software modules, ways of their resolution, etc. The performed analysis is related to eleven projects developed in the same company. This study is an exploratory research with some explanatory features. Moreover, having identified some drawbacks, we present extensions of problem reports and their analysis which have been verified in another industrial case study project.ResultsFine-grained (accurate) problem handling reports provide a wider scope of possible measures to assess the relevant development processes. This is helpful in controlling single projects (local perspective) as well as in managing these processes in the whole company (global perspective).ConclusionDetailed problem handling reports extend the space and quality of statistical analysis, they provide significant enhancement in evaluation and refinement of software development processes as well as in reliability prediction.     

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.     

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。     

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.     

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.     

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。     

Efficient software clustering technique using an adaptive and preventive dendrogram cutting approach

ContextSoftware clustering is a key technique that is used in reverse engineering to recover a high-level abstraction of the software in the case of limited resources. Very limited research has explicitly discussed the problem of finding the optimum set of clusters in the design and how to penalize for the formation of singleton clusters during clustering.ObjectiveThis paper attempts to enhance the existing agglomerative clustering algorithms by introducing a complementary mechanism. To solve the architecture recovery problem, the proposed approach focuses on minimizing redundant effort and penalizing for the formation of singleton clusters during clustering while maintaining the integrity of the results.MethodAn automated solution for cutting a dendrogram that is based on least-squares regression is presented in order to find the best cut level. A dendrogram is a tree diagram that shows the taxonomic relationships of clusters of software entities. Moreover, a factor to penalize clusters that will form singletons is introduced in this paper. Simulations were performed on two open-source projects. The proposed approach was compared against the exhaustive and highest gap dendrogram cutting methods, as well as two well-known cluster validity indices, namely, Dunn’s index and the Davies-Bouldin index.ResultsWhen comparing our clustering results against the original package diagram, our approach achieved an average accuracy rate of 90.07% from two simulations after the utility classes were removed. The utility classes in the source code affect the accuracy of the software clustering, owing to its omnipresent behavior. The proposed approach also successfully penalized the formation of singleton clusters during clustering.ConclusionThe evaluation indicates that the proposed approach can enhance the quality of the clustering results by guiding software maintainers through the cutting point selection process. The proposed approach can be used as a complementary mechanism to improve the effectiveness of existing clustering algorithms.