Ramon A. Mata-Toledo

A factor analysis of software complexity measures

Abstract Factor analysis has been used to analyse software measures and is useful to identify the important factors that influence variability in measures. Some previous results indicate that many measures are actually measuring the same thing. This article reports on a series of experiments analyzing relationships among some of the commonly used software complexity measures. Identifying relationships is important in selecting the most significant measure(s) to collect. A set of PASCAL programs was analyzed for number of decisions, number of procedures, maximum level of nesting, number of I/O statements, the Halstead count, and number of lines of code. Factor analysis showed several interesting conclusions. First, the program should be normalized to avoid high correlation between program size and everything else. Second, dividing by lines of code appears to be the best normalization. Third, an inverse relationship exists between the normalized number of decisions and both the normalized unique operand counts and the number of decisions. Finally, small programs ( 100 lines).

Visualization of random sequences using the chaos game algorithm

Abstract A graphical technique using iterated function systems is used to examine random number generators by visually looking for patterns in the data generated. This simple graphical technique, which may be implemented and used on a PC, can complement more conventional statistically-oriented methods to find non-randomness within “pseudo-random” data sets.

Using program dependence graphs for information flow control

Abstract An algorithm that uses program dependence graphs for static program analysis to validate secure information flow is presented. The algorithm is able to deal with a wider class of information flow policies than the well-known lattice model of secure information flow. The lattice model requires that the information flow permitted by a flow policy be transitive and unidirectional; the algorithm presented here does not impose these restrictions on a flow policy.

A temporal relational calculus

This paper describes a generalization of the relational database model using first order predicate calculus with temporal operators. The generalization is intended to be a model for an intelligent database—one which employs reasoning in retrieving its data—and to suggest a query language for the system. An incremental approach to intelligent databases is employed, wherein a standard database model is augmented with temporal attributes and then with deductive capabilities. This paper builds on the work of Navathe on temporal databases and on Allens algebra of temporal relations. The goal is a logical reconstruction of the model which results when the two approaches are combined.

Computer storage technology

The hardware components, both internal and external, of a computer used to read (retrieve) or write…

Software engineering tools

Automated or semiautomated methods for developing computer code. Software tools and environments aut…

Database management system

A software system for managing and controlling access to a database. In a database management syste…

Open-source software

Computer software that is licensed by the copyright holder, granting the rights to examine, change,…

Natural language processing

The term natural language processing (NLP) can be subdivided into two terms: natural language, and t…

Green cloud architecture

Recently, cloud computing has become very popular and has emerged as a widely accepted computing and…