20452185
A methodology for test selection
Software creation requires not only testing during the development cycle by the development staff, but also independent testing following the completion of the implementation. However in the latter case, the amount of testing that can be carried out is often limited by time and resources. At the very most, independent testing can be expected to provide 100% test coverage of the test requirements (or specifications) associated with the software element with the minimum of effort. This paper describes a methodology employing integer programming by which the amount of testing required to provide the maximum possible test coverage of the test requirements (for the given test set) is assured while at the same time minimizing the total number of tests to be included in a test suite. A collateral procedure provides recommendations on which tests might be eliminated if less than 100% test coverage of the test requirements is permitted. This latter procedure will be useful in determining the risk of not running the minimum set of tests for 100% test coverage. A third process selects from the test matrix the set of tests to be applied to the system following maintenance modification of any test requirements-- that is, to provide a submatrix for regression testing. The potential benefits for applying the integer programming technique in test data selection is also discussed.
20141160
A method for analyzing properties of hierarchical predicate transition nets
Hierarchical high level Petri nets have been proposed in recent years as a powerful formal method for modeling large concurrent and distributed systems but they are even more difficult to analyze than flat high level Petri nets, which are also lacking effective analysis methods themselves. A method for analyzing properties of hierarchical predicate transition Petri nets is proposed. The method employs two temporal induction techniques, one for safety properties and the other for liveness properties, without using temporal logic formalism. Within each induction technique, a hybrid reasoning technique combining net structural and behavioral reasoning, and ordinary first order logic reasoning is used.
28965788
A useful approach to developing reverse engineering metrics
If software metrics are useful in a forward software engineering environment, they are vital in a reverse engineering environment. We are endeavouring to discover approaches to developing reverse engineering metrics for software engineers who need them for reverse engineering legacy systems. The major contribution of the paper is the presentation of a systematic research base and a hierarchical approach to the development of software metrics for reverse engineering. Measurement is fundamental to the software engineering discipline as a whole. A software metric is a quantitative measure of the degree to which a system, component, or process possesses a given attribute (N.E. Fenton and S.L. Pfleeger, 1996). Software reverse engineering is the process of analysing a subject system to: identify the system's components and their interrelationships; and create representations of the system at a higher level of abstraction (E.J. Chikofsky and J.H. Cross II, 1990). The goal of developing reverse engineering metrics is to identify measures that are needed for assessing the status of reverse engineering projects, products, processes and resources, and helping engineers to understand both what is happening and what will happen during reverse engineering procedures. Consequently, these concrete reverse engineering measures make more visible to us aspects of process and product in reverse engineering, in particular, the product of specifications and the process of abstractions and transformations. This makes it possible to control reverse engineering projects. Aspects of measurement in reverse engineering are outlined.
28830107
Introducing software architecture specification and analysis in SAM through an example
Abstract Software architecture study has become one of the most active research areas in software engineering in the recent years. Although there have been many published results on specification and analysis method of software architectures, information on sound systematic methodology for modeling and analyzing software architectures is lacking. In this article, we present a formal systematic software architecture specification and analysis methodology called SAM and show how to apply SAM to specify a command control (C2) system and to analyze its real-time constraints.
19528385
A semi-formal approach to assist software design with reuse
Design with reuse has been accepted as a cost-effective way to software development. Software reuse covers the process of identification, representation, retrieval, adaptation, and integration of reusable software components. In this paper, we propose a semi-formal approach to software reuse. The approach consists of the following major steps: (1) software components are annotated with formal information, (2) the software components are then translated into predicate transition nets, and (3) consistency checking of the reusable and new components is carried out using the reachability analysis technique of predicate transition (PrT) nets. The approach is demonstrated through an example.
14218377
A Methodology for Constructing Predicate Transition Net Specifications
In this paper, a methodology for constructing hierarchical and structured predicate transition net specifications is developed, which includes new systematic notation extensions for supporting various transformation techniques upon predicate transition nets and several rules for applying such transformation techniques. The levelling technique in data-flow diagrams is adapted in the refinement and the abstraction techniques, and the state decomposition idea in state-charts is employed in designing various label formulation operators. The methodology is illustrated through the specification of a lift system. The methodology can significantly reduce the constructing complexity and enhance the comprehensibility of large predicate transition net specifications.
5709930
Document clustering using locality preserving indexing
We propose a novel document clustering method which aims to cluster the documents into different semantic classes. The document space is generally of high dimensionality and clustering in such a high dimensional space is often infeasible due to the curse of dimensionality. By using locality preserving indexing (LPI), the documents can be projected into a lower-dimensional semantic space in which the documents related to the same semantics are close to each other. Different from previous document clustering methods based on latent semantic indexing (LSI) or nonnegative matrix factorization (NMF), our method tries to discover both the geometric and discriminating structures of the document space. Theoretical analysis of our method shows that LPI is an unsupervised approximation of the supervised linear discriminant analysis (LDA) method, which gives the intuitive motivation of our method. Extensive experimental evaluations are performed on the Reuters-21578 and TDT2 data sets.
20004613
Disk Embeddings of Planar Graphs
Abstract 
Given a planar graph $G=(V,E)$ and a rooted forest ${\FF}=(V_{\FF}, A_{\FF})$ 
with leaf set $V$, we wish to decide whether $G$ has a plane embedding $\GG$ 
satisfying the following condition: There are $|V_{\FF}|-|V|$ pairwise noncrossing 
Jordan curves in the plane one-to-one corresponding to the nonleaf vertices of 
${\FF}$ such that for every nonleaf vertex $f$ of ${\FF}$, the interior of the curve 
$\JJ_f$ corresponding to $f$ contains all the leaf descendants of $f$ in ${\FF}$
but contains no other leaves of ${\FF}$. 
This problem arises from theoretical studies in geographic database systems. 
It is unknown whether this problem can be solved in polynomial time. 
This paper presents an almost linear-time algorithm for a nontrivial special case 
where the set of leaf descendants of each nonleaf vertex $f$ in ${\FF}$ induces 
a connected subgraph of $G$. 


1437223
A Fast General Methodology for Information - Theoretically Optimal Encodings of Graphs
We propose a fast methodology for encoding graphs with informationtheoretically minimum numbers of bits. The methodology is applicable to general classes of graphs; this paper focuses on simple planar graphs. Specifically, a graph with property ? is called a ?-graph. If ? satisfies certain properties, then an n-node ?-graph G can be encoded by a binary string X such that (1) G and X can be obtained from each other in O(n log n) time, and (2) X has at most s(n)+o(s(n)) bits for any function s(n) = ?(n) so that there are at most 2s(n)+o(s(n)) distinct n-node ?-graphs. Examples of such ? include all conjunctions of the following sets of properties: (1) G is a planar graph or a plane graph; (2) G is directed or undirected; (3) G is triangulated, triconnected, biconnected, merely connected, or not required to be connected; and (4) G has at most l1 (respectively, l2) distinct node (respectively, edge) labels. These examples are novel applications of small cycle separators of planar graphs and settle several problems that have been open since Tutte's census series were published in 1960's.
13876948
A framework for incremental deployment strategies for router-assisted services
Incremental deployment of a new network service or protocol is typically a hard problem, especially when it has to be deployed in the routers. First, an incrementally deployable protocol is needed. Second, a study of the performance impact of incremental deployment should be carried out to evaluate deployment strategies. Choosing the wrong strategy can be disastrous, as it may inhibit reaping the benefits of an otherwise robust service, and prevent widespread adoption. Unfortunately, to date there has been no systematic evaluation of incremental deployment for such services. Our research work is focused on the second aspect, namely the performance impact of incremental deployment of router-assisted services. We take the first step to define a framework for evaluating incrementally deployable services, which consists of three parts: (a) selection and classification of deployment strategies; (b) definition of performance metrics; and (c) systematic evaluation of deployment strategies. As a case study for our framework, we evaluate the performance of router-assisted reliable multicast protocols. Although our framework is still evolving, our results clearly demonstrate that the choice of a strategy has a substantial impact on performance, and thus affirms the need for systematic evaluation of incremental deployment. Our case study includes two router-assisted reliable multicast protocols, namely PGM and LMS. We make several interesting observations: (a) the performance of different deployment strategies varies widely; for example, with some strategies, both PGM and LMS approach full deployment performance with as little as 5% of the routers deployed, but with other strategies up to 80% deployment may be needed to approach the same level; (b) our sensitivity analysis reveals relatively small variation in the results in mos
9650912
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded in a high dimensional Euclidean space, we propose a relevance feedback scheme which is naturally conducted only on the image manifold in question rather than the total ambient space. While images are typically represented by feature vectors in Rn, the natural distance is often different from the distance induced by the ambient space Rn. The geodesic distances on manifold are used to measure the similarities between images. However, when the number of data points is small, it is hard to discover the intrinsic manifold structure. Based on user interactions in a relevance feedback driven query-by-example system, the intrinsic similarities between images can be accurately estimated. We then develop an algorithmic framework to approximate the optimal mapping function by a Radial Basis Function (RBF) neural network. The semantics of a new image can be inferred by the RBF neural network. Experimental results show that our approach is effective in improving the performance of content-based image retrieval systems.