17757852
Predicting fault detection effectiveness
Regression methods are used to model software fault detection effectiveness in terms of several product and testing process measures. The relative importance of these product/process measures for predicting fault detection effectiveness is assessed for a specific data set. A substantial family of models is considered, specifically, the family of quadratic response surface models with two way interaction. Model selection is based on "leave one out at a time" cross validation using the predicted residual sum of squares (PRESS) criterion. Prediction intervals for fault detection effectiveness are used to generate prediction intervals for the number of residual faults conditioned on the observed number of discovered faults. High levels of assurance about measures like fault detection effectiveness (residual faults) require more than just high (low) predicted values, they also require that the prediction intervals have high lower (low upper) bounds.
31350744
Redesigning legacy systems into the object-oriented paradigm
Object-oriented/sup 1/ languages support many modern programming paradigms such as information hiding, inheritance, polymorphism, and dynamic binding. As a result, software systems implemented in OO languages are more reusable and reliable than those in non-OO. Many legacy software systems were created before OO programming became popular and needed to be redesigned and updated to OO programs. The process of abstracting OO designs from the procedural source code was often done manually or with limited assistance from program structural diagrams. Most reengineering focuses on the functionality of the original program, and the OO redesign often results in a completely new design based on the designers' understanding of the original program. Such an approach is not sufficient, for it not only takes time and effort for designers to become familiar with the original program, but the approach itself is also mistake-prone due to the human involvement. This paper presents a computer-aided semi-automatic method that abstracts OO designs from the original procedural source code. More specifically, it is a method for OO redesign based on program structural diagrams, visualization, and execution slice. We conducted a case study by applying this method to an inventory management software system. Results indicate that our method can effectively and efficiently abstract an appropriate OO design out of the original C code as well as re-generate part of the system in C++ code based on this new OO design.
206572113
Measuring distance between program features
We present a metric to determine the distance between the features of a software system. Such a measurement can elucidate how features of the system being examined are close to each other. We first use an execution slice-based technique to identify a set of code (basic blocks in our case) that is used to implement each feature. Then, depending on whether the execution frequency of each block is considered during the construction of such sets of code, a static as well as a dynamic distance is computed for each pair of features. These two types of distance differ in that the former computes the distance between two features only by how these features are implemented in the system, while the latter also takes into account how each feature is executed based on a user's operational profile. In other words, the static distance quantitatively gives the closeness of two features from the system implementation point of view, whereas the dynamic distance presents such closeness from the users' execution point of view. To illustrate the use of our metric, we report a case study on a Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE). The results of our study suggest that the distance metric discussed in this paper can provide a good measurement, in a quantitative way, of how close two program features are. Such information can also serve as a good start to understanding how a modification made to one feature is likely to affect other features.
30609851
An integrated solution for creating dependable software
Software testing and maintenance are the two most expensive phases of the software life cycle. Why, in general, are customers not satisfied with the quality of software? Studies have shown that approximately 20% of a software system is responsible for 80% of the faults and over the lifetime of an average software system as much as 70% of the cost is estimated to be dedicated to testing and maintenance. Clearly an appropriate methodology ought to be employed to address these high-leverage concerns. With the increased emphasis on software quality and the pressure to deliver software faster and cheaper such a methodology should encompass software design, architecture, development, testing, and maintenance as a whole and provide an integrated solution that leads to the creation of more dependable software. In addition, it is also crucial to have a set of effective tools with user-friendly interfaces available to software practitioners to apply this methodology in real-life contexts. We explain how to take advantage of sophisticated analysis of the dynamic behavior of the software being developed to help programmers, as well as testers, accomplish their assignments more effectively and efficiently.
13223545
Quantifying the closeness between program components and features
Abstract One of the most important steps towards effective software maintenance of a large complicated system is to understand how program features are spread over the entire system and their interactions with the program components. However, we must first be able to represent an abstract feature in terms of some concrete program components. In this paper, we use an execution slice-based technique to identify the basic blocks which are used to implement a program feature. Three metrics are then defined, based on this identification, to determine quantitatively , the disparity between a program component and a feature, the concentration of a feature in a program component, and the dedication of a program component to a feature. The computations of these metrics are automated by incorporating them in a tool ( χ Suds), which makes the use of our metrics immediately applicable in real-life contexts. We demonstrate the effectiveness of our technique by experimenting with a reliability and performance evaluator. Results of our study suggest that these metrics can provide an indication of the closeness between a feature and a program component which is very useful for software programmers and maintainers to better understand the system at hand.
39945640
Smart debugging software architectural design in SDL
Statistical data show that it is much less expensive to correct software bugs at the early design stage rather than the late stage of the development process when the final system has already been implemented and integrated together. The use of slicing and execution histories as an aid in software debugging is well established for programming languages like C and C++; however, it is rarely applied in the field of software design specification. We propose a solution by applying the source code level technologies to debugging software designs represented in a high-level specification and description language such as SDL. More specifically, we extend execution slice-based heuristics from source code-based debugging to the software design specification level. Suspicious locations in an SDL specification are prioritized by their likelihood of containing faults. Locations with a higher priority should be examined first rather than those with a lower priority as the former are more likely to contain the faults. A debugging tool, SmartD/sub DSL/, with user-friendly interfaces was developed to support our method. An illustration is provided to demonstrate the feasibility of using our method to effectively debug an architectural design.
17918314
SilkRoad II: a multi-paradigm runtime system for cluster computing
A parallel programming paradigm dictates the way in which an application is to be expressed. It also restricts the algorithms that may be used in the application. Unfortunately, runtime systems for parallel computing often impose a particular programming paradigm. For a wider choice of algorithms, it is desirable to support more than one paradigm. In this paper we consider SilkRoad II, a variant of the Cilk runtime system for cluster computing. What is unique about SilkRoad II is its memory model which supports multiple paradigms with the underlying software distributed shared memory. The RC-dag memory consistency model of SilkRoad II is introduced. Our experimental results show that the stronger RC-dag can achieve performance comparable to LC of Cilk while supporting a bigger set of paradigms with rather good performance.
1444557
Conditional entropy coding of VQ indexes for image compression
Block sizes of practical vector quantization (VQ) image coders are not large enough to exploit all high-order statistical dependencies among pixels. Therefore, adaptive entropy coding of VQ indexes via statistical context modeling can significantly reduce the bit rate of VQ coders for given distortion. Address VQ was a pioneer work in this direction. In this paper we develop a framework of conditional entropy coding of VQ indexes (CECOVI) based on a simple Bayesian-type method of estimating probabilities conditioned on causal contexts, CECOVI is conceptually cleaner and algorithmically more efficient than address VQ, with address-VQ technique being its special case. It reduces the bit rate of address VQ by more than 20% for the same distortion, and does so at only a tiny fraction of address VQ's computational cost.
1096223
Vascular segmentation in three-dimensional rotational angiography based on maximum intensity projections
Three-dimensional rotational angiography (3D-RA) is a relatively new and promising technique for imaging blood vessels. In this paper, we propose a novel 3D-RA vascular segmentation algorithm, which is fully automatic and very computationally efficient, based on the maximum intensity projections (MIP) of 3D-RA images. Validation results on 13 clinical 3D-RA datasets reveal that, according to the agreement between the segmentation results and the ground truth, our method (a) outperforms both the maximum a posteriori-expectation maximization (MAP-EM)-based method and the MAP-Markov random field (MAP-MRF)-based segmentation method, and (b) works comparably to the optimal global thresholding method. Experimental results also show that our method can successfully segment major vascular structures in 3D-RA and produce a lower false positive rate than that of the MAP-EM-based and MAP-MRF-based methods.
3492450
A framework for data prefetching using off-line training of Markovian predictors
An important technique for alleviating the memory bottleneck is data prefetching. Data prefetching solutions ranging from pure software approach by inserting prefetch instructions through program analysis to purely hardware mechanisms have been proposed. The degrees of success of those techniques are dependent on the nature of the applications. The need for innovative approach is rapidly growing with the introduction of applications such as object-oriented applications that show dynamically changing memory access behavior In this paper, we propose a novel framework for the use of data prefetchers that are trained off-line using smart learning algorithms to produce prediction models which captures hidden memory access patterns. Once built, those prediction models are loaded into a data prefetching unit in the CPU at the appropriate point during the runtime to drive the prefetching. On average by using table size of about 8KB size, we were able to achieve prediction accuracy of about 68% through our own proposed learning method and performance was boosted about 37% on average on the benchmarks we tested. Furthermore, we believe our proposed framework is amenable to other predictors and can be done as a phase of the profiling-optimizing-compiler.
13948106
Design of clocked circuits using UML
Clocking is an essential component of any embedded system design. However, traditional design techniques are either short of clocking support or too complex for users. The Unified Modeling Language (UML) has been proposed as design tool in real time system design, but the clocking semantics has not been properly dealt with. In this paper, we will present our experience of using UML to design a clocked system. In particular, UML is used to model the digital down converter, an essential component of software radios. Our tool chain automatically generates the simulation as well as synthesizes the final implementation.