35812086
Effect of Test Set Minimization on Fault Detection Effectiveness
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.
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.
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.
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.
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.
6423442
Rule-based anomaly pattern detection for detecting disease outbreaks
This paper presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly detection are unsatisfactory for this problem because they identify individual data points that are rare due to particular combinations of features. When applied to our scenario, these traditional algorithms discover isolated outliers of particularly strange events, such as someone accidentally shooting their ear, that are not indicative of a new outbreak. Instead, we would like to detect anomalous patterns. These patterns are groups with specific characteristics whose recent pattern of illness is anomalous relative to historical patterns. We propose using a rule-based anomaly detection algorithm that characterizes each anomalous pattern with a rule. The significance of each rule is carefully evaluated using Fisher's Exact Test and a randomization test. Our algorithm is compared against a standard detection algorithm by measuring the number of false positives and the timeliness of detection. Simulated data, produced by a simulator that creates the effects of an epidemic on a city, is used for evaluation. The results indicate that our algorithm has significantly better detection times for common significance thresholds while having a slightly higher false positive rate.
40827612
Conditional entropy coding of VQ indexes for image compression
Vector quantization (VQ) is a source coding methodology with provable rate-distortion optimality. However, despite more than two decades of intensive research, VQ theoretical promise is yet to be fully realized in image compression practice. Restricted by high VQ complexity in dimensions and due to high-order sample correlations in images, block sizes of practical VQ image coders are hardly large enough to achieve the rate-distortion optimality. Among the large number of VQ variants in the literature, a technique called address VQ (A-VQ) by Nasrabadi and Feng (1990) achieved the best rate-distortion performance so far to the best of our knowledge. The essence of A-VQ is to effectively increase VQ dimensions by a lossless coding of a group of 16-dimensional VQ codewords that are spatially adjacent. From a different perspective, we can consider a signal source that is coded by memoryless basic VQ to be just another signal source whose samples are the indices of the memoryless VQ codewords, and then induce the problem of lossless compression of the VQ-coded source. If the memoryless VQ is not rate-distortion optimal (often the case in practice), then there must exist hidden structures between the samples of VQ-coded source (VQ codewords). Therefore, an alternative way of approaching the rate-distortion optimality is to model and utilize these inter-codewords structures or correlations by context modeling and conditional entropy coding of VQ indexes.
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.
8187290
Model-driven SoC design via executable UML to SystemC
We present a system level description mechanism based on UML-notations from which one can automatically extract SystemC code. Our modelling framework is based on a restricted set of UML diagram types and some standard extensions influenced by the communication infrastructure of SystemC. The system specifications are developed using the UML-compatible tool, Rhapsody (2004). We then translate the internal representation of the design generated by Rhapsody into SystemC code. The extensions we have implemented using the stereotype feature of the Rhapsody tool pull up the communication infrastructure and timing features of SystemC to the UML-level. Consequently, we can describe executable platforms at the UML-level as well as translate UML-based application descriptions to SystemC level.
1021507
Augmented vessels for quantitative analysis of vascular abnormalities and endovascular treatment planning
Endovascular treatment plays an important role in the minimally invasive treatment of patients with vascular diseases, a major cause of morbidity and mortality worldwide. Given a segmentation of an angiography, quantitative analysis of abnormal structures can aid radiologists in choosing appropriate treatments and apparatuses. However, effective quantitation is only attainable if the abnormalities are identified from the vasculature. To achieve this, a novel method is developed, which works on the simpler shape of normal vessels to identify different vascular abnormalities (viz. stenotic atherosclerotic plaque, and saccular and fusiform aneurysmal lumens) in an indirect fashion, instead of directly manipulating the complex-shaped abnormalities. The proposed method has been tested on three synthetic and 17 clinical data sets. Comparisons with two related works are also conducted. Experimental results show that our method can produce satisfactory identification of the abnormalities and approximations of the ideal post-treatment vessel lumens. In addition, it can help increase the repeatability of the measurement of clinical parameters significantly