R. W. Schwanke. An intelligent tool for re-engineering software modularity. In Proceedings of the 13th International Conference on Software Engineering (ICSE 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....In contrast, this experiment demonstrates compliance verification for a highly abstract and subjective design principle: high cohesion and low coupling. Lacking a standard measure of cohesion and coupling, the design principle is best treated heuristically, rather than by a set of formal rules[24]. Motivation We are interested in application specific customization of subsystems in Choices. Thus, it is desirable that the subsystems be as self contained and independent of one another as possible, so that modifying a subsystem has minimal unanticipated side effects on its neighbors. In ....

....the analysis for heuristic guidelines is rather human dependent, and the certainty of compliance is much less. 6 Related work Other systems for monitoring an implementation s faithfulness to its design models appear to have focused on either static or dynamic verification, but not both[16, 15, 24, 13]. We improve on these systems by systematic provision of numerous static and dynamic visual perspectives, and by considering a wide range of design commitments, from concrete implementation level rules to configuration level principles like subsystem cohesion and coupling. In particular, our work ....

R. Schwanke. An Intelligent Tool for Reengineering Software Modularity. In Proceedings of the 13th International Conference on Software Engineering, May 1991.

....be used to classify these mechanisms. 2.4.1 Degree of automation We propose to distinguish between automated, partially automated, and manual change support. In the domain of software re engineering, numerous attempts have been made to automate, or partially automate, software maintenance tasks [43, 9, 19, 48, 33]. Typically, these are semantics preserving transformations of the software system. In reality, however, these automated evolutions incorporate some form of manual verification and thus, can only be considered partially automated. Within the specific domain of refactoring (i.e. restructuring of ....

R. W. Schwanke. An intelligent tool for re-engineering software modularity. In Proceedings Int'l Conf. Software Engineering, pages 83--92. IEEE Computer Society Press, 1991.

....techniques that have been successfully applied to system modularization. Similar to our approach, many clustering techniques work in a bottom up fashion by using information extracted from the source code to produce high level structural views of the system organization. Rigi [10] and Arch [13] are two such tools. These tools, however, require significant user input to direct their respective clustering algorithms. Hutchens and Basili [5] present a fully automatic clustering technique based on data bindings. They present several techniques for clustering related procedures into ....

R. Schwanke. An intelligent tool for re-engineering software modularity. In Proc. 13th Intl. Conf. Software Engineering, May 1991.

.... has proposed several approaches to deal with this challenge by de ning techniques that partition the structure of a software system into subsystems (clusters) Most of these techniques determine clusters (subsystems) using either source code component similarity [42] sets of heuristic rules [48], concept analysis and clustering metrics [3, 27, 35, 56] or information available from the system implementation such as module, directory, and or package names [4] Although the above mentioned software clustering techniques have been shown to produce good results on certain types of systems, ....

Schwanke, R. W. An intelligent tool for re-engineering software modularity. In Proceedings of the 13th International Conference on Software Engineering (May 1991), pp. 83-92.

....this analysis. Many of the clustering techniques published in the literature can be categorized by the way they establish clusters. Hutchens and Basili [7] developed an algorithm that clusters procedures into modules by measuring the interaction between pairs of procedures. Schwanke et al. [16, 17] introduced the notion of using design principles such as low coupling and high cohesion to create clusters. Choi and Scacchi [4] describe a clustering technique based on maximizing the cohesiveness of clusters by evaluating the exchange of resources between modules. Hausi Muller et al. 15] ....

R. Schwanke. An intelligent tool for re-engineering software modularity. In Proc. 13th Intl. Conf. Software Engineering, May 1991.

....by the way they create clusters. A survey article published by Wiggerts [41] is a good starting point to learn about software clustering. Hutchens and Basili [15] developed an algorithm that clusters procedures into modules by measuring the interaction between pairs of procedures. Schwanke et al. [32, 33] introduced the notion of using design principles such as low coupling and high cohesion to create clusters. Choi and Scacchi [9] describe a clustering technique based on maximizing the cohesiveness of clusters by evaluating the exchange of resources between modules. Muller et al. [27] implemented ....

R. Schwanke. An intelligent tool for re-engineering software modularity. In Proc. 13th Intl. Conf. Software Engineering, May 1991.

.... has proposed several approaches to deal with this challenge by defining techniques that partition the structure of a software system into subsystems (clusters) Most of these techniques determine clusters (subsystems) using either source code component similarity [42] sets of heuristic rules [48], concept analysis and clustering metrics [3, 27, 35, 56] or information available from the system implementation such as module, directory, and or package names [4] Although the above mentioned software clustering techniques have been shown to produce good results on certain types of systems, ....

SCHWANKE, R. W. An intelligent tool for re-engineering software modularity. In Proceedings of the lSth International Conference on Software Engineering (May 1991), pp. 83-92.

....software implementation. These metrics can be used to reconstruct the actual SA as compared to the planned SA. The analysis of the actual SA can be used to evaluate whether the new actual SA deviates from the planned SA. An early example of such an approach is Schwanke s re engineering tool [17]. The tool uses a concept of similarity based on Parna s information hiding principle, but is not specifically designed for object oriented systems. The tool supports two services: clustering, which identifies similar procedures that should be grouped in a module, and a maverick analysis, which ....

Schwanke, R. W. "An intelligent tool for reengineering software modularity". In Proceedings of the 13 International Conference on Software Engineering, pp. 8392, 1991.

....shows the member function that has been deleted. 4. Applications This section presents some examples of how Chava can be applied to either software systems or analysis of websites. 4.1. Clustering We have been working with several other researchers to study the use of clustering techniques [21, 18, 27] on software repositories to discover high level software structures from existing code. We applied Bunch [20] the clustering tool developed in this purpose, to the Java software repository we created for a proxy server called iPROXY [24] and obtained the cluster diagram shown in Figure 8. The ....

R. Schwanke. An Intelligent Tool For Re-Engineering Software Modularity. In Proc. 13th Intl. Conf. Software Engineering, May 1991.

....(concrete) designs by grouping related procedures and variables into modules. Progressively, as software systems grew in size, the new problem of recovering design level (abstract) designs by grouping sets of modules into hierarchies of subsys tems became pertinent. Schwanke s ARCH tool [34] introduced concepts such as low coupling and highcohesion into the design recovery problem. The Rigi system [27] by Muller et al., pioneered the concepts of isolating omnipresent modules, grouping modules with common clients and suppliers, and grouping modules that have similar names. The last ....

R. Schwanke. An intelligent tool for re-engineering software modularity. In Prom 13th Intl. Conf. Software Engineering, May 1991.

....is also based on similarity metrics between sot tware components and defines similarity metrics that combine structural and semantic information. The structural information is defined using a resource flow graph representation of the source code and semantic information uses the work of Schwanke [44]. Schwanke s work is based on Pamas s [39] information hiding principle and on Tversky s [48] research. The work proposed here differs in that the clusters are used as a parameter to the metrics. Other research that clusters sot tware components includes work by Anquetil [3, 4] Wiggerts [49] ....

Schwanke, R. W., "An intelligent tool for re-engineering software modularity", in Proceedings of 13th International Conference on Software Engineering, 1991, pp. 83-92.

....paper and in the work of Macoridis et al. More work is required to compare the results produced by these two approaches. Other work on software re modularization has adopted analytical solutions based upon formal concept analysis and clustering metrics [9, 21, 11] and sets of heuristic rules [18]. More work is required to assess the comparative performance of these non search based approaches with the search based strategy introduced here. Some metrics for coupling and cohesion [20, 17, 1, 8] have attempted to give a more continuous real valued quantitative metric based on a variety of ....

Schwanke, R. W. An intelligent tool for reengineering software modularity. In Proceedings of the 13th International Conference on Software Engineering (May 1991), pp. 83-92.

....a good knowledge of the system being analyzed as the oracle. This is similar to the typical assessment that has been used in many reverse engineering studies where the output from a subsystem classification recovery technique is compared by a tester with the corresponding expected classification [6, 11]. One waytouseexpertstoverifytheBF s is to first request them to highlight code segments which they think are related to each feature. Such information then serves as the basis for the verification. An obvious difficulty of this approach is whether there exists any such expert. For small ....

R. Schwanke, "An intelligent tool for reengineering software modularity," in Proceedings of the 13th IEEE International Conference on Software Engineering, 1991.

....to similarity measures between attributes. In addition, context information affecting the algorithm performance is now handled in a separate step (clean up phase) Finally, a wider test suite is analyzed. Among the works about model implementation compliance checking that have been proposed [13, 14, 15, 17, 18] in literature, here we concentrate on those closest to our approach, i.e. those that explicitly address the problem of checking design against implementation and are applicable in the object oriented domain. The work by Meyers, Duby and Reiss [14] differs from ours both in the objective and in ....

R. Schwanke. An intelligent tool for reengineering software modularity. In Proceedings of the International Conference on Software Engineering, 1991.

....match and the maximum likelihood classi cation algorithms, rather than being produced by a manual cleaning of design and code representations. Among the works about model implementation compliance checking that have been proposed [Luckham et al. 1987; Meyers et al. 1993; Murphy et al. 1995; Schwanke 1991; Se ka et al. 1996] in the literature, here we concentrate on those closest to our approach, i.e. those that explicitly address the problem of checking design against implementation and are applicable in the object oriented domain. The work by Meyers, Duby and Reiss [Meyers et al. 1993] di ers ....

Schwanke, R. (1991), \An Intelligent Tool for Reengineering Software Modularity," In Proceedings of the International Conference on Software Engineering , pp. 83-92.

....has remained almost constant. More study will be necessary to investigate the reason of discrepancies in data members and operations between classes with equal name in the design and code. 6. Related Works Among the works about model implementation compliance checking that have been proposed [12, 16, 13, 14, 17] in literature, here we concentrate on those closest to our approach, i.e those that explicitly address the problem of checking design against implementation and are applicable in the object oriented domain. The work by Meyers, Duby and Reiss [13] differs from ours both in the objective and in ....

R. Schwanke. An intelligent tool for reengineering software modularity. In Proceedings of the International Conference on Software Engineering, 1991.

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R. W. Schwanke. An intelligent tool for re-engineering software modularity. In Proceedings of the 13th International Conference on Software Engineering (ICSE 1991.

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R. W. Schwanke. An intelligent tool for re-engineering software modularity. In Proc. ICSE, pages 83--92. IEEE, 1991.

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R. W. Schwanke, "An intelligent tool for re-engineering software modularity ". In 13th Intl. Conf. Softw. Eng., pp. 83--92, May 1991.

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R. W. Schwanke. An intelligent tool for re-engineering software modularity. In Proceedings of the 13th International Conference on Software Engineering, pages 83--92, Austin, Texas, United States, May 1991.

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R. W. Schwanke. An intelligent tool for re-engineering software modularity. In Proceedings Int'l Conf. Software Engineering, pages 83--92. IEEE Computer Society Press, 1991.

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R. Schwanke. An intelligent tool for re-engineering software modularity. In Proc. 13th Intl. Conf. Software Engineering, May 1991.

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R. Schwanke. An intelligent tool for re-engineering software modularity. In Proc. 13th Intl. Conf. Software Engineering, May 1991.

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R. Schwanke. An intelligent tool for re-engineering software modularity. In IEEE Conf. on Software Maintenance - 1991.

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Schwanke, R. W., "An intelligent tool for re-engineering software modularity", in Proceedings of 13th International Conference on Software Engineering, 1991, pp. 83-92.

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