Software development using formal methods is believed to be a process of successive refinements from abstract specifications into concrete specifications. Refinement rules may be used to demonstrate that the concrete specifications satisfy the corresponding abstract ones. However, there are serious limitations of the refinement rules in both theory and in practical applications. This paper first uses examples to demonstrate the limitations, and then proposes a new software development model for improvement based on our experience. The limitations include (1) the refinement rules are not sufficient to guarantee that a refined specification (or concrete specification) satisfy the user's real requirements if it satisfies the abstract specification, (2) the existing refinement rules are not always applicable in theory during the successive refinements, and (3) the refinement rules are difficult to apply effectively in practice, due to various kinds of uncertainties and resource constraints. The proposed model suggests that system development using formal methods should be divided into two phases: a static development phase and a dynamic development phase, the whole process in each phase phase involving requirements analysis. In order to suit the new model, the existing refinement rules are modified.

article Free Access Share on Authors' response Authors: Walter Tichy Univ. of Karlsruhe, Karlsruche, Germany Univ. of Karlsruhe, Karlsruche, GermanyView Profile , Rolf Adams Univ. of Karlsruhe, Karlsruche, Germany Univ. of Karlsruhe, Karlsruche, GermanyView Profile , Annette Weinert Univ. of Karlsruhe, Karlsruche, Germany Univ. of Karlsruhe, Karlsruche, GermanyView Profile Authors Info & Claims ACM Transactions on Software Engineering and MethodologyVolume 4Issue 2April 1995 pp 217–219https://doi.org/10.1145/210134.210438Published:01 April 1995Publication History 0citation277DownloadsMetricsTotal Citations0Total Downloads277Last 12 Months2Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

We present here a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters. The method, however, requires the input of a number of seeds, either individual pixels or regions, which will control the formation of regions into which the image will be segmented. In this correspondence, we present the algorithm, discuss briefly its properties, and suggest two ways in which it can be employed, namely, by using manual seed selection or by automated procedures.>

When a single software module in a large system is modified, a potentially large number of other modules may have to be recompiled. By reducing both the number of compilations and the amount of input processed by each compilation run, the turnaround time after changes can be reduced significantly. Potential time savings are measured in a medium-sized, industrial software project over a three-year period. The results indicate that a large number of compilations caused by traditional compilation unit dependencies may be redundant. On the available data, a mechanism that compares compiler output saves about 25 percent, smart recompilation saves 50 percent, and smartest recompilation may save up to 80 percent of compilation work. Furthermore, all compilation methods other than smartest recompilation process large amounts of unused environment data. In the project analyzed, the average environment symbols are actually used. Reading only the actually used symbols would reduce total compiler input by about 50 percent. Combining smart recompilation with a reduction in environment processing might double to triple perceived compilation speed and double linker speed, without sacrificing static type safety.

A natural language help (NLH) system answers questions that are entered as typed, natural language sentences.Compared to traditional keyword lookup, natural language input allows greater flexibility and precision.This report describes such a help system, NLH/E, which answers questions formulated in English.Currently, it can process questions about a substantial domain: over 130 functions described in five chapters of the Common Lisp manual.NLH/E is built with a novel caseframe parser that operates with a thesaurus, case inheritance, and noun/verb phrase unifica tion.These features reduce the size of the grammer considerably, making it feasible to build realistic NLH systems.Statistical data about the grammar are included.NLH is a first step towards a reusability expert, i.e., a program that helps a client find reusable software components by engaging in a natural language dialogue.