Computer-aided software engineering of expert systems

The problem of automatically reprogramming an expert system either to adjust for solving different types of computational problems or to improve run-time performance is addressed. A computer-aided software engineering (CASE) method using artificial intelligence techniques to instantiate a concrete program from a given abstract expert system architecture is proposed. Our method, called expert system reification, is suitable for use in a large range of problem-solving behaviors. Reification combines meta-level programming with partial evaluation of the program. Expert system reification extends the above blend with a knowledge-based translation module, thus obtaining an efficient and portable expert system version. We demonstrate the method by applying it to STAREX, an electronic circuit pack troubleshooting expert system developed in PROLOG to derive automatically the corresponding C code, which is currently installed at one of the AT&T manufacturing facilities.     

An approach to expert assessment in software engineering

An approach is proposed to the solution of formalized problems of assessment of the activity that produces and maintains software systems (SSs). Such assessment is realized by using expertises that form a new assessment process adequate to the activity needs and specifics with an environment common to the expertises. The following mathematical apparatus is elaborated for expertises: a framework (target functions and executing mechanisms), a model and methods (formalisms for improving the quality and reusing the results of expertises) of an assessment process, and tools for integrating the apparatus into software development management processes. The approach is theoretically justified. Prospects of developing the proposed approach are described. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 151–168, July–August 2009.     

An approach to expert control of interactive software systems

Expert problem-solving strategies in many domains require the use of detailed mathematical techniques coupled with experiential knowledge about how and when to use the appropriate techniques. In many of these domains, such techniques are made available to experts in large software packages. In attempting to build expert systems for these domains, we wish to make use of these packages, and are therefore faced with an important problem: how to integrate the existing software, and knowledge about its use, into a practical expert system. The expert knowledge is used, in dynamic selection and interpretation of appropriate programs and parameters, to reach a successful goal in the problem solving. We describe the framework of a hybrid expert system for representing problem-solving knowledge in these domains. This hybrid system may be characterized as consisting of a production system and mathematical methods. The software package is reorganized as necessary to map it into the mathematical-method representation of a hybrid system. This approach has evolved out of an effort to build an expert system for performing well-log analysis, ELAS (expert log analysis system).     

An agent-based framework for cooperating expert systems in concurrent engineering

This paper describes an agent-based framework with a tandem integration architecture for cooperating distributed, heterogeneous, and autonomous concurrent engineering systems. The approach has been experimented with using the prototype AGENTS system. It is demonstrated that design tools can be dynamically connected and configured to construct highly complex systems on an incremental basis, designing and proving one system at a time without bothering the rest. A major advantage of the approach is the balance between the interoperability and the autonomy of individual systems.     

图书馆管理软件系统的质量评价模型研究

通过对图书馆管理软件系统质量度量指标的分析,将层次分析法应用于指标的权重计算,采用模糊决策法进行质量指标的度量,构建了一个图书馆管理软件系统质量量化评价模型并给出了应用实例.该模型对图书馆管理软件系统的选用、开发、改进等有重要参考价值.     

ESSE: an expert system for software evaluation

Solving software evaluation problems is a particularly difficult software engineering process and many different—often contradictory—criteria must be considered in order to reach a decision. This paper presents ESSE, a prototype expert system for software evaluation that embodies various aspects of the Multiple-Criteria Decision Aid (MCDA) methodology. Its main features are the flexibility in problem modeling and the built-in knowledge about software problem solving and software attribute assessment. Evaluation problems are modeled around top-level software attributes, such as quality and cost. Expert assistants guide the evaluator in feeding values to the decision model. ESSE covers all important dimensions of software evaluation through the integration of different technologies.     

Hard-to-use evaluation criteria for software engineering

Most evaluations of software tools and methodologies could be called “public relations,” because they are subjective arguments given by proponents. The need for markedly increased productivity in software development is now forcing better evaluation criteria to be used. Software engineering must begin to live up to its second name by finding quantitative measures of quality. This paper suggests some evaluation criteria that are probably too difficult to carry out, criteria that may always remain subjective. It argues that these are so important that we should keep them in mind as a balance to the hard data we can obtain and should seek to learn more about them despite the difficulty of doing so.A historical example is presented as illustration of the necessity of retaining subjective criteria. High-level languages and their compilers today enjoy almost universal acceptance. It will be argued that the value of this tool has never been precisely evaluated, and if narrow measures had been applied at its inception, it would have been found wanting. This historical lesson is then applied to the problem of evaluating a novel specification and testing tool under development at the University of Maryland.     

Unifying software engineering and systems engineering

The author describes CMMI (Capability Maturity Model Integration) and the emerging project methods which demonstrate the opportunities for process improvement gains open to organizations. The organization that changes from separated software and system engineering processes to a more unified approach will find itself far more suited to developing dynamically changing, software-intensive systems. Culture change is never easy, but the alternative is even less palatable     

Fuzzy systems and neural networks in software engineering project management

To make reasonable estimates of resources, costs, and schedules, software project managers need to be provided with models that furnish the essential framework for software project planning and control by supplying important management numbers concerning the state and parameters of the project that are critical for resource allocation. Understanding that software development is not a mechanistic process brings about the realization that parameters that characterize the development of software possess an inherent fuzziness, thus providing the rationale for the development of realistic models based on fuzzy set or neural theories.Fuzzy and neural approaches offer a key advantage over traditional modeling approaches in that they aremodel-free estimators. This article opens up the possibility of applying fuzzy estimation theory and neural networks for the purpose of software engineering project management and control, using Putnam's manpower buildup index (MBI) estimation model as an example. It is shown that the MBI selection process can be based upon 64 different fuzzy associative memory (FAM) rules. The same rules are used to generate 64 training patterns for a feedforward neural network. The fuzzy associative memory and neural network approaches are compared qualitatively through estimation surfaces. The FAM estimation surfaces are stepped, whereas those from the neural system are smooth. Also, the FAM system sets up much faster than the neural system. FAM rules obtained from logical antecedent-consequent pairs are maintained distinct, giving the user the ability to determine which FAM rule contributed how much membership activation to a concluded output.     

Structural engineering applications of expert systems

In this paper, several expert systems at various stages of development in structural engineering are reviewed and examined. In addition, attempts are being made to apply expert systems to both the safety evaluations of structures during construction and the choice of methods for constructing bridge structures and these are discussed.     

An evaluation of programming languages and language features for engineering software development

This article addresses the need for engineers to have a working knowledge of the fundamental structures of computer programming languages. In pursuit of this, it briefly looks at the history behind four of the more well-known programming languages. It then attempts to identify, and to look critically at, the attributes of programming languages that significantly affect the production of engineering software. The four traditional procedural programming languages chosen for review are those intended for scientific and general purpose programmin—FORTRAN-77, C, Pascal, and Modula-2. These languages are compared and some general observations are made.The emphasis of this article is on the attributes, characteristics, and components of programming languages that are important to software development and maintenance. Consequently, the comparison itself is of secondary importance, with the actual methodology of comparison given prominence in order that professional engineers who need to develop engineering software are able to make rational decisions about the choice of a programming language. Choosing an appropriate language can be a complex task and many factors must be considered. Therefore, in this article the fundamental structures, constructs, and attributes of programming languages are discussed, with very little attention given to the specific syntax of any particular language.     

A software engineering methodology for rule-based systems

Current expert systems are typically difficult to change once they are built. The authors introduce a method for developing more easily maintainable rule-based expert systems, which is based on dividing the rules into groups and focusing attention on those facts that carry information between rules in different groups. They describe a new algorithm for grouping the rules of a knowledge base automatically and a notation set of software tools for the proposed method. The approach is supported by a study of the connectivity of rules and facts in rule-based systems; it is found that they indeed have the latent structure necessary for the programming methodology. Recent experimental results also support the approach. In contrast to the homogeneous way in which the facts of a rule-based system are usually viewed, this approach shows that certain facts are more important than others with regard to future modifications of the rules     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

An explanation shell for expert systems

We describe a shell for expert systems written in Prolog. The shell provides a consultation environment and a range of explanation capabilities. The design of the shell is modular, making it very easy to extend the shell with extra features required by a particular expert system. The novelty of the shell is twofold. Firstly, it has a uniform design consisting of an integrated collection of meta-interpreters. Secondly, there is a new approach for explaining 'why not,' when a query to the system fails.     

A Software Tool for Constructing Traditional Chinese Medical Expert Systems

It is an urgent task to hnplemeut a lot of expert systems to capture the valuable expertise ofexperienced doctors of traditional Chinese medicine.In order to meet the needs,a software tool isdeveloped.It features a unified diagnosis model,a specially designed knowledge representationlanguage and an efficient but effective inference engine.To implement an expert system,it isonly necessary to input the expert's knowledge expressed in knowledge representation languagewithout the design of any additional software.The time and effort required for implementing anexpert system are thus greatly saved.The software is very compact and can run onmicrocomputers e.g.IBM-PC/XT.Two traditional Chinese medical expert systems have beensuccessfully implemented with the tool.     

Ontology of systems and software engineering

Systems and software engineering have evolved in the last years in a process of consolidation of their specificities as engineering disciplines. This has resulted in research and inquiry on ontological and epistemological issues related to them. Due to the supporting nature of systems and software engineering with regards to other engineering disciplines, these aspects are also relevant to researchers and practitioners in other engineering domains. The contents of this issue provide a selection of research aimed at consolidating ontology of systems and software engineering as a useful and consistent body of knowledge.     

Human software requirements engineering for computer-controlled manufacturing systems

Computers as integral systems components determine the quality of work of operators in industrial production. This paper contributes to improving the design of man-machine systems by proposing a formal aid to human software requirements definition and design. First, the need for considering human requirements is stressed. Since technology is to be considered as ‘non-deterministic’, the designer is faced with a degree of freedom in his design decisions which can be and should be utilized for raising the quality of work of people operating computer-controlled man-machine systems. Then, a hierarchy of human quality criteria applicable for ergonomic judgement of work design measures is derived. Following the principle of prospective work design, these criteria must be considered as design goals just like technical and economic requirements. As a formal aid for making design decisions meeting these comprehensive requirements, the Requirements/Quality Criteria Matrix is proposed. Finally, this method of considering human requirements is illustrated by designing some man-machine interface features for operators of a hypothetical flexible manufacturing system.     

An evaluation of pure spectrum-based fault localization techniques for large-scale software systems

Pure spectrum-based fault localization (SBFL) is a well-studied statistical debugging technique that only takes a set of test cases (some failing and some passing) and their code coverage as input and produces a ranked list of suspicious program elements to help the developer identify the location of a bug that causes a failed test case. Studies show that pure SBFL techniques produce good ranked lists for small programs. However, our previous study based on the iBugs benchmark that uses the Aspect J repository shows that, for realistic programs, the accuracy of the ranked list is not suitable for human developers. In this paper, we confirm this based on a combined empirical evaluation with the iBugs and the Defects4 J benchmark. Our experiments show that, on average, at most ∼40%, ∼80%, and ∼90% of the bugs can be localized reliably within the first 10, 100, and 1000 ranked lines, respectively, in the Defects4 J benchmark. To reliably localize 90% of the bugs with the best performing SBFL metric D^∗, ∼450 lines have to be inspected by the developer. For human developers, this remains unsuitable, although the results improve compared with the results for the Aspect J benchmark. Based on this study, we can clearly see the need to go beyond pure SBFL and take other information, such as information from the bug report or from version history of the code lines, into consideration.