26202841
An execution-based retrieval of object-oriented components
Software reuse and object-oriented software development is recognized as one of the promising techniques to improve software development. Class components are basic building blocks in objectoriented software development. This paper describes a method of retrieving potentially reusable objected-oriented class components from a class library by executing classes in the class library on a test program based on a user-provided sample behavior of the desired class. The method handles the class hierarchy and uses a strategy maximum number of matched methods and minimum unmatched methods to find the classes close to the desired class. Based on the method, a prototype implementation of the class retrieval tool is implemented for Java classes.
8249874
Software retrieval by samples using concept analysis
Abstract Finding and retrieving software components is one of the tasks of the building-block approach to software reuse. One interesting property of code components unlike other types of software artifacts is that they can be executed. The execution-based retrieval process tends to be too long to be incorporated in practice and faces the problem of non-termination and very long execution time. This paper describes a software component retrieval method using sample input–output behavior of the components (but without actual execution) based on concept analysis. The retrieval uses samples chosen by the developers of the components (rather than generated randomly or provided by the users). Based on the validity relation between components and samples, a concept lattice is constructed for the library by applying formal concept analysis. The user retrieves components by selecting valid samples incrementally for a desired component from a dynamically created menu of samples available in the library. Our method avoids the problems associated with actual execution-based retrieval such as non-termination and very long execution time, and also improves the retrieval time. Our approach can be directly applied to other levels of software components than code components as long as the components can be described in terms of some input–output relation.
15172968
A structured approach to retrieving functions by types
A solid state area imaging apparatus having a photosensor matrix array disposed at a front surface area of a substrate and having a charge transfer arrangement for transferring charges generated in the photosensors of the matrix so as to convert them into a serial signal. It also includes a penetrative charge transfer arrangement for transferring the charge from the front surface area of the substrate to the back surface area of the substrate, and which has a static induction transistor structure. The charges are transferred vertically through a channel formed in the structure of the static induction transistor. This penetrative charge transfer arrangement may be used as a part of the transfer path for generating the serial signal or a path for removing excess charges which are generated in the photosensors.
16981497
Organizing and retrieving class components based on types for reuse
Reusing existing software components improves software development productivity. Classes are basic building blocks in object-oriented programming. One of the central issues in reusing existing classes in object-orient programming is to find suitable reusable classes. This paper describes a method of organizing the OO class library for retrieving classes using type information. The method is based on (i) grouping classes based on the number of methods and the number of arguments of methods in classes and (ii) linking both groups and classes based on potential reusability relationships. This structured reuse library allows the class retrieval process to be done efficiently by narrowing the search space using groups and links. The user can also navigate the reuse library and learn about potential reusability among class components.
30145508
Static Analysis for Optimizing Reference Counting
In reference counting schemes for automatically reclaiming storage, each time a reference to a heap-allocated object is created or destroyed, the reference count of the object needs to be updated. This may involve expensive inter-processor message exchanges in distributed environments. This overhead can be reduced by analyzing the lifetimes of references to avoid unnecessary updatings. We present a compile-time analysis for higher-order functional languages that determines whether the lifetime of a reference exceeds the lifetime of the environment in which the reference was created. Using this statically inferred information, a method for optimizing reference counting schemes is described. Our method can be applied to reference counting schemes in both uniprocessor and multiprocessor environments.
11709593
Transition: Recommending Mobile Content using Content Diffusion and User Preference
An improved release coating for heat transferable laminate and improved method for curing the release coating for heat transferable laminates wherein an ink design layer is transferred from a carrier web onto an article such as a plastic or glass container upon application of heat and pressure. The improved release coating does not contain wax components but exhibits release properties similar to wax based formulations. The improved release contains U-V curable components which are cured by exposure to ultraviolet light after the laminate containing the ink design, is transferred to a receiving article. The heat transferable laminate preferably includes a barrier layer intermediate the release layer and ink design layer. The barrier layer also contains U-V curable components. The barrier layer is cured by exposure to ultraviolet radiation during formation of the laminate structure and prior to transfer of the laminate to a receiving article. The improved release formulation upon curing by ultraviolet radiation produces a hard, glossy, optically clear protective layer exhibiting enhanced resistance to abrasion, scuffing and solvent attack.
38854847
A time-based approach to effective recommender systems using implicit feedback
Recommender systems provide personalized recommendations on products or services to customers. Collaborative filtering is a widely used method of providing recommendations using explicit ratings on items from users. In some e-commerce environments, however, it is difficult to collect explicit feedback data; only implicit feedback is available. In this paper, we present a method of building an effective collaborative filtering-based recommender system for an e-commerce environment without explicit feedback data. Our method constructs pseudo rating data from the implicit feedback data. When building the pseudo rating matrix, we incorporate temporal information such as the user's purchase time and the item's launch time in order to increase recommendation accuracy. Based on this method, we built both user-based and item-based collaborative filtering-based recommender systems for character images (wallpaper) in a mobile e-commerce environment and conducted a variety of experiments. Empirical results show our time-incorporated recommender system is significantly more accurate than a pure collaborative filtering system.
61509689
Blackboard scheduler control knowledge for heuristic classification: Representation and inference
32680230
A methodology for predicting service life and design of reliability experiments
This paper summarizes a methodology for reliability prediction of new products where field data are sparse, and the allowed number & length of experiments are limited. The methodology relies on estimating a set where the unknown parameters are most likely to be found, calculation of an upper bound for the reliability metric of interest conditioned that the parameters reside in the estimated set, and tightening the bounds via design of experiments. Models of failure propagation, failure acceleration, system operations, and time/cycle to failure at various levels of fidelity & expert elicited information may be incorporated to enhance the accuracy of the predictions. The application of the model is illustrated through numerical studies.
3876714
A Time-Based Recommender System Using Implicit Feedback
Recommender systems provide personalized recommendations on products or services to customers. Collaborative filtering is a widely used method of providing recommendations based on explicit ratings on items from other users. However, in some ecommerce environments such as a mobile environment, it is difficult to collect explicit feedback data; only implicit feedback is available. In this paper, we present a method of building an effective collaborative filtering-based recommender system for an e-commerce environment without explicit feedback data. Our method constructs pseudo rating data from the implicit feedback data. When building the pseudo rating matrix, we incorporate temporal information such as the user’s purchase time and the item’s launch time in order to increase recommendation accuracy. Based on this method, we built a recommender system for a mobile e-commerce environment and conducted several experiments. Empirical results show our collaborative filtering-based recommender system to be significantly more accurate than a pure collaborative filtering system. Our approach can be applied to building collaborative filtering-based recommender systems for any ecommerce environment without explicit feedback.