Software Engineering and Programming Languages
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Cost/benefit analysis for incorporating human factors in the software lifecycle
New software engineering techniques and the necessity to improve the user interface in increasingly interactive software environments have led to a change in traditional software development methods. Methodologies for improvement of the interface design, an overview of the human factors element, and cost/benefit aspects are explored.
Relational database design using an object-oriented methodology
Of the many approaches to relational database design, the Object Modeling Technique (OMT) is particularly effective. A comprehensive explanation and two applications show the semantic improvement of OMT over other approaches.
Linear hashing and spiral storage are two dynamic hashing schemes originally designed for external files. This paper shows how to adapt these two methods for hash tables stored in main memory. The necessary data structures and algorithms are described, the expected performance is analyzed mathematically, and actual execution times are obtained and compared with alternative techniques. Linear hashing is found to be both faster and easier to implement than spiral storage. Two alternative techniques are considered: a simple unbalanced binary tree and double hashing with periodic rehashing into a larger table. The retrieval time of linear hashing is similar to double hashing and substantially faster than a binary tree, except for very small trees. The loading times of double hashing (with periodic reorganization), a binary tree, and linear hashing are similar. Overall, linear hashing is a simple and efficient technique for applications where the cardinality of the key set is not known in advance.
Distributed programming in Argus
Argus—a programming language and system developed to support the implementation and execution of distributed programs—provides mechanisms that help programmers cope with the special problems that arise in distributed programs, such as network partitions and crashes of remote nodes.
Special section on operating systems
This special collection of articles examines recent research in operating systems, focusing on particular systems and projects that are seminal and representative. The areas these articles cover include distributed operating systems, heterogeneous computer systems, distributed programming, and real-time systems.
The V distributed System was developed at Stanford University as part of a research project to explore issues in distributed systems. Aspects of the design suggest important directions for the design of future operating systems and communication systems.
Interconnecting heterogeneous computer systems
A software structure created by the Heterogeneous Computer Systems (HCS) Project at the University of Washington was designed to address the problems of heterogeneity that typically arise in research computing environments.
The Cedar File System (CFS) is a workstation file system that provides access to both a workstation's local disk and to remote file servers via a single hierarchical name space. CFS supports a group of cooperating programmers by allowing them to both manage local naming environments and to share consistent versions of collections of software.
We present a novel, yet straightforward linear-time algorithm for merging two sorted lists in a fixed amount of additional space. Constant of proportionality estimates and empirical testing reveal that this procedure is reasonably competitive with merge routines free to squander unbounded additional memory, making it particularly attractive whenever space is a critical resource.
On synchronization in hard-real-time systems
The design of software for hard-real-time systems is usually difficult to change because of the constraints imposed by the need to meet absolute real-time deadlines on processors with limited capacity. Nevertheless, a new approach involving a trio of ideas appears to be helpful for those who build software for such complex applications.
Connectionist networks can be used as expert system knowledge bases. Furthermore, such networks can be constructed from training examples by machine learning techniques. This gives a way to automate the generation of expert systems for classification problems.
NPATH: a measure of execution path complexity and its applications
Software engineering is a discipline in search of objective measures for factors that contribute to software quality. NPATH, which counts the acyclic execution paths through a function, is an objective measure of software complexity related to the ease with which software can be comprehensively tested.
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