205046786
A formal program complexity model and its application
Abstract This article takes an axiomatic approach to defining program complexity using complexity rankings and measures. A complexity ranking is an abstract, qualitative comparison between programs that is approximated by a complexity measure on each program. A set of axioms are stated and a classification scheme is presented with properties of each class. This is extended a series of properties developed by Weyuker. The formal model has many applications, including evaluating and classifying existing complexity measures and serving as criteria for complexity measure selection.
8007887
An application of decision theory for the evaluation of software prototypes
Abstract There is a need to quantify management decision making in software development. To this end, this article presents an application of concepts from economic decision theory to an aspect of this problem currently under study by many in the software engineering community—how to prototype a design and evaluate the effectiveness of this prototype. The role of prototyping as an experimental tool is analyzed and techniques for defining what to prototype and when it is cost effective are introduced. We demonstrate some of these decision theory techniques to define a model that management can use to select solutions from a set of alternative designs.
33942395
Measuring and Modeling Usage and Reliability for Statistical Web Testing
Statistical testing and reliability analysis can be used effectively to assure quality for Web applications. To support this strategy, we extract Web usage and failure information from existing Web logs. The usage information is used to build models for statistical Web testing. The related failure information is used to measure the reliability of Web applications and the potential effectiveness of statistical Web testing. We applied this approach to analyze some actual Web logs. The results demonstrated the viability and effectiveness of our approach.
16987100
Measuring Prime Program Complexity
Abstract This paper uses the prime program decomposition of a program as the basis for a measure that closely correlates with our intuitive notion of program complexity. This measure is based upon the information theory ideas of randomness and entropy such that results about structured programming, data abstractions, and other programming paradigms can be stated in quantitative terms, and empirical means can be used to validate the assumptions used to develop the model. As a graph-based model, it can be applied to several graphical examples as extensions not otherwise available to source-code based models. This paper introduces the measure, derives several properties for it, and gives some simple examples to demonstrate that the measure is a plausible approximation of our notions concerning structured programming.
37559798
Measurement and continuous improvement of software reliability throughout software life-cycle
Abstract Software reliability is one of the most important aspects of software quality. However, most of the existing techniques focus on the system testing and other late stages of development life-cycle. Therefore, they are not effective for early problem identification and reliability improvement. This paper describes our recent work in establishing predictive linkage between software reliability and other entities that we can measure and control early in the development cycle, and using such predictive relations to drive continuous reliability improvement.
10468208
Measurement and defect modeling for a legacy software system
This paper analyzes the quality of a large-scale legacy software system using selected metrics. Quality measurements include defect information collected during product development and in-field operation. Other software metrics include measurements on various product and process attributes, including design, size, change, and complexity. Preliminary analyses revealed the high degree of skew in our data and a weak correlation between defects and software metrics. Tree-based models were then used to uncover relationships between defects and software metrics, and to identify high-defect modules together with their associated measurement characteristics. As results presented in tree forms are natural to the decision process and are easy to understand, tree-based modeling is shown to be suitable for change solicitation and useful in guiding remedial actions for quality improvement.
15872261
Identifying Direct Causal Effects in Linear Models
This paper deals with the problem of identifying direct causal effects in recursive linear structural equation models. Using techniques developed for graphical causal models, we show that a model can be decomposed into a set of submodels such that the identification problem can be solved independently in each submodel. We provide a new identification method that identifies causal effects by solving a set of algebraic equations.
393156
A general identification condition for causal effects
This paper concerns the assessment of the effects of actions or policy interventions from a combination of: (i) nonexperimental data, and (ii) substantive assumptions. The assumptions are encoded in the form of a directed acyclic graph, also called "causal graph", in which some variables are presumed to be unobserved. The paper establishes a necessary and sufficient criterion for the identifiability of the causal effects of a singleton variable on all other variables in the model, and a powerful sufficient criterion for the effects of a singleton variable on any set of variables.
12486810
A new class of biorthogonal wavelet systems for image transform coding
We construct general biorthogonal Coifman wavelet systems, a new class of compactly supported biorthogonal wavelet systems with vanishing moments equally distributed for a scaling function and wavelet pair. A time-domain design method is employed and closed-form expressions for the impulse responses and the frequency responses of the corresponding dual filters are derived. The resulting filter coefficients are all dyadic fractions, which is an attractive feature in the realization of multiplication-free discrete wavelet transform. Even-ordered systems in this family are symmetric, which correspond to linear-phase dual filters. In particular, three filterbanks (FBs) in this family are systematically verified to have competitive compression potential to the 9-7 tap biorthogonal wavelet FB by Cohen et al., which is currently the most widely used one in the field of wavelet transform coding. In addition, the proposed FB's have much smaller computational complexity in terms of floating-point operations required in transformation, and therefore indicate a better tradeoff between compression performance and computational complexity.
10434536
Identifying Linear Causal Effects
This paper concerns the assessment of linear cause-effect relationships from a combination of observational data and qualitative causal structures. The paper shows how techniques developed for identifying causal effects in causal Bayesian networks can be used to identify linear causal effects, and thus provides a new approach for assessing linear causal effects in structural equation models. Using this approach the paper develops a systematic procedure for recognizing identifiable direct causal effects.
4621823
On the Testable Implications of Causal Models with Hidden Variables
The validity of a causal model can be tested only if the model imposes constraints on the probability distribution that governs the generated data. In the presence of unmeasured variables, causal models may impose two types of constraints: conditional independencies, as read through the d-separation criterion, and functional constraints, for which no general criterion is available. This paper offers a systematic way of identifying functional constraints and, thus, facilitates the task of testing causal models as well as inferring such models from data.