Preface. I Programming1. An ERLANG Tutorial2. Sequential Programming. 3. Programming with Lists. 4. Programming with Tuples. 5. Concurrent Programming. 6. Distributed Programming. 7. Error Handling. 8. Programming Robust Applications. 9. Miscellaneous Items. II Applications10. Databases. 11. Distributed Programming Techniques. 12. Distributed Data. 13. Operating Systems. 14. Real Time Control. 15. Telephony. 16. An ASN l Compiler: 17. Graphics. 18. Object-Oriented Programming.

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Concurrent Programming in Erlang

Software productivity has been steadily increasing over the past 30 years, but not enough to close the gap between the demands placed on the software industry and what the state of the practice can deliver; nothing short of an order of magnitude increase in productivity will extricate the software industry from its perennial crisis. Several decades of intensive research in software engineering and artificial intelligence left few alternatives but software reuse as the (only) realistic approach to bring about the gains of productivity and quality that the software industry needs. In this paper, we discuss the implications of reuse on the production, with an emphasis on the technical challenges. Software reuse involves building software that is reusable by design and building with reusable software. Software reuse includes reusing both the products of previous software projects and the processes deployed to produce them, leading to a wide spectrum of reuse approaches, from the building blocks (reusing products) approach, on one hand, to the generative or reusable processor (reusing processes), on the other. We discuss the implication of such approaches on the organization, control, and method of software development and discuss proposed models for their economic analysis. Software reuse benefits from methodologies and tools to: (1) build more readily reusable software and (2) locate, evaluate, and tailor reusable software, the last being critical for the building blocks approach. Both sets of issues are discussed in this paper, with a focus on application generators and OO development for the first and a thorough discussion of retrieval techniques for software components, component composition (or bottom-up design), and transformational systems for the second. We conclude by highlighting areas that, in our opinion, are worthy of further investigation. >

Reusing software: issues and research directions

In order to support the maintenance of an object-oriented software system, the quality of its design must be evaluated using adequate quantification means. In spite of the current extensive use of metrics, if used in isolation metrics are oftentimes too fine grained to quantify comprehensively an investigated design aspect (e.g., distribution of system's intelligence among classes). To help developers and maintainers detect and localize design problems in a system, we propose a novel mechanism - called detection strategy - for formulating metrics-based rules that capture deviations from good design principles and heuristics. Using detection strategies an engineer can directly localize classes or methods affected by a particular design flaw (e.g., God Class), rather than having to infer the real design problem from a large set of abnormal metric values. We have defined such detection strategies for capturing around ten important flaws of object-oriented design found in the literature and validated the approach experimentally on multiple large-scale case-studies.

Detection strategies: metrics-based rules for detecting design flaws

Requirements capture is arguably the most important step in software engineering, and yet the most difficult and the least formalized one [Phalp and Shepperd 2000] Enterprises build information systems to support their business processes Software engineering research has typically focused on the development process, starting with user requirements—if that—with business modeling often confused with software system modeling [Isoda 2001] Researchers and practitioners in management information systems have long recognized that understanding the business processes that an information system must support is key to eliciting the needs of its users (see eg, Eriksson and Penker 2000]), but lacked the tools to model such business processes or to relate such models to software requirements Researchers and practitioners in business administration have long been interested in modeling the processes of organizations for the purposes of understanding, analyzing, and improving such processes [Hammer and Champy 1993], but their models were often too coarse to be of use to software engineers The advent of ecommerce and workflow management systems, among other things, has led to a convergence of interests and tools, within the broad IT community, for modeling and enabling business processes In this article we present an overview of business process modeling languages We first propose a categorization of the various languages and then describe representative languages from each family

Business process modeling languages: Sorting through the alphabet soup

Conceptual models or semantic data models were developed to capture the meaning of an application domain as perceived by someone. Moreover, concepts employed in semantic data models have recently been adopted in object-oriented approaches to systems analysis and design. To employ conceptual modeling constructs effectively, their meanings have to be defined rigorously. Often, however, rigorous definitions of these constructs are missing. This situation occurs especially in the case of the relationship construct. Empirical evidence shows that use of relationships is often problematical as a way of communicating the meaning of an application domain. For example, users of conceptual modeling methodologies are frequently confused about whether to show an association between things via a relationship, an entity, or an attribute. Because conceptual models are intended to capture knowledge about a real-world domain, we take the view that the meaning of modeling constructs should be sought in models of reality. Accordingly, we use ontology, which is the branch of philosophy dealing with models of reality, to analyze the meaning of common conceptual modeling constructs. Our analysis provides a precise definition of several conceptual modeling constructs. Based on our analysis, we derive rules for the use of relationships in entity-relationship conceptual modeling. Moreover, we show how the rules resolve ambiguities that exist in current practice and how they can enrich the capacity of an entity-relationship conceptual model to capture knowledge about an application domain.

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An ontological analysis of the relationship construct in conceptual modeling

Object-oriented analysis

Many organizations fail to implement or reap the benefits of information systems (IS) projects. The social care sector is not yet a great user of information technology (IT) and the thinking about IS is generally less well-developed than, for instance, in the health care sector. Research in health informatics indicates that there are special problems in creating integrated solutions and achieving the uptake of systems. This project was therefore undertaken with the benefit of experience of previous projects in health and social services and in the expectation that attention to participative design and people factors would be the key determinants of success. The paper describes the outcomes and draws conclusions about the special characteristics of IS projects in social services.

https://link.springer.com/content/pdf/10.1080%2F026839697345026.pdf

Gill Smith

Papers

Object-oriented analysis

Developing and implementing IS: a case study analysis in social services

Business process re-engineering: the use of process redesign and IT to transform corporate performance