Program Input Parameters Research Articles

Test data generation using genetic programming

Typically, search-based test data generation methods search on a population of program input values. Program input values can be regarded as solutions to underlying path constraints over program input parameters. One way to discover these path constraints is to use the symbolic execution method. Search-based methods attempt to find input values which are solutions to these path constraints, without knowing the actual constraints. In this paper, we show that we can search for the underlying path constraints using search-based methods, without resorting to symbolic execution. Trying to discover the exact or a good enough approximation of the underlying constraints may lead to a more targeted search, compared to directly searching for program input values. Besides, the construction of approximate constraints by searching may help to avoid some problems of symbolic execution. The proposed method uses genetic programming for learning constraints on program input parameters. To evaluate the performance of the proposed approach, a series of experiments have been conducted on a number of different benchmark programs. For 91.8% of benchmark programs, the proposed method achieved the best efficiency among the competitive algorithms. The results show that, if constraint solving can be provided for some or all parameter types of the methods of programs under test, our approach can improve the efficiency and effectiveness of search-based test data generation.

POPdemog: visualizing population demographic history from simulation scripts.

We present POPdemog, an R package which converts coalescent simulation program input parameters into a visual representation of the demographic model. This package is useful for preparing figures, for checking that demographic simulation parameters have been correctly specified, and for understanding demographic models that other researchers have used to simulate genetic data. The POPdemog package supports the ms, msa, msHot, MaCS, msprime, scrm and Cosi2 programs, and includes options for customizing the output figures. The POPdemog package and its tutorial can be freely downloaded from https://github.com/YingZhou001/POPdemog. Supplementary data are available at Bioinformatics online.

Enhancing adaptive random testing for programs with high dimensional input domains or failure-unrelated parameters

Adaptive random testing (ART), an enhancement of random testing (RT), aims to both randomly select and evenly spread test cases. Recently, it has been observed that the effectiveness of some ART algorithms may deteriorate as the number of program input parameters (dimensionality) increases. In this article, we analyse various problems of one ART algorithm, namely fixed-sized-candidate-set ART (FSCS-ART), in the high dimensional input domain setting, and study how FSCS-ART can be further enhanced to address these problems. We propose to add a filtering process of inputs into FSCS-ART to achieve a more even-spread of test cases and better failure detection effectiveness in high dimensional space. Our study shows that this solution, termed as FSCS-ART-FE, can improve FSCS-ART not only in the case of high dimensional space, but also in the case of having failure-unrelated parameters. Both cases are common in real life programs. Therefore, we recommend using FSCS-ART-FE instead of FSCS-ART whenever possible. Other ART algorithms may face similar problems as FSCS-ART; hence our study also brings insight into the improvement of other ART algorithms in high dimensional space.

Predicting locality phases for dynamic memory optimization

Dynamic data, cache, and memory adaptation can significantly improve program performance when they are applied on long continuous phases of execution that have dynamic but predictable locality. To support phase-based adaptation, this paper defines the concept of locality phases and describes a four-component analysis technique. Locality-based phase detection uses locality analysis and signal processing techniques to identify phases from the data access trace of a program; frequency-based phase marking inserts code markers that mark phases in all executions of the program; phase hierarchy construction identifies the structure of multiple phases; and phase-sequence prediction predicts the phase sequence from program input parameters. The paper shows the accuracy and the granularity of phase and phase-sequence prediction as well as its uses in dynamic data packing, memory remapping, and cache resizing.

Parameter-space screening: a powerful tool for high-throughput crystal structure determination

The determination of protein structures on a genomic scale requires both computing capacity and efficiency increases at many stages along the complex process. By combining bioinformatics workflow-management techniques, cluster-based computing and popular crystallographic structure-determination software packages, an efficient and powerful new tool for structural biology/genomics has been developed. Using the workflow manager and a simple web interface, the researcher can, in a few easy steps, set up hundreds of structure-determination jobs, each using a slightly different set of program input parameters, thus efficiently screening parameter space for the optimal input-parameter combination, i.e. a set of parameters that leads to a successful structure determination. Upon completion, results from the programs are harvested, analyzed, sorted based on success and presented to the user via the web interface. This approach has been applied with success in more than 30 cases. Examples of successful structure determinations based on single-wavelength scattering (SAS) are described and include cases where the 'rational' crystallographer-based selection of input parameters values had failed.

A review of TSW: the Windows version of the TRAMO–SEATS program

TRAMO (Time Series Regression with ARIMA Noise, Missing Observations and Outliers) and SEATS (Signal Extraction in ARIMA Time Series) are two closely coupled programs. The latest versions, which reside within the TSW (TRAMO-SEATS for Windows) program, have become virtually fused. The TSW program, of which there is both a single-user version and a networked version, is freely available from the web site of the Bank of Spain at http://www.bde.es/servicio/software/tswe.htm. It is accompanied by a reference manual, which is illustrated with numerous screen shots and currently has 37 pages. The manual contains instructions for installation and use of the program, along with a glossary and index of the program's input parameters. The TSW program has been implemented by Gianluca Caporello working under the supervision of Augustin Maravall. The original inspiration for the SEATS program was the work of Burman (1980), who built a program for the seasonal adjustment of economic time series while working for the Bank of England. The previous versions of the TRAMO and SEATS programs, which appeared in 1996, were the joint work of Victor Gomez and Augustin Maravall. It is fortuitous that TSW has reached its present state of maturity at the same time as the Windows version of the rival STAMP program of Koopman et al. (2000) has been released. Although the two programs share the same objectives, they are underpinned by different philosophies, and they obtain their results in quite different ways. We shall highlight some of these differences in the course of this review.

A computer method for inventory production/disposal decisions when reorder-occurrence is uncertain

A computer method is presented to determine the lowest discounted expected cost production/disposal inventory policy for items with uncertain reorder-occurrence. After explaining the method, several examples are described for slow-moving items with relatively high setup costs. The required program input parameters are presented and discussed so that others may easily determine parameter settings appropriate for their situation. Printed output for the examples is provided so that the program can be validated.

Computer modeling of human crash kinematics

The idea of designing a computer program for the simulation of the gross motion of human crash victims has received much attention during the past decade. The existence of reliable programs would drastically reduce the need for extensive full‐scale crash testing in order to determine the effects of vehicle design perturbations on human trauma. A variety of reasons exist which so far have precluded the use of crash victim simulation programs in lieu of full‐scale tests. There currently exist no crash victim simulation programs which can accurately reproduce an experimental test without considerable “tuning.” The choice of program input parameters and internal physical models is very much a matter of physical intuition. Once reasonable correlation of computer results with full‐scale test results is attained, the model is assumed to be validated. However, there is an increasing body of evidence which suggests that full‐scale tests utilizing anthropomorphic dummies lack sufficient repeatability so that the use of a single test to validate a computer model is questionable at best. A survey of the current state of crash victim simulation is presented, with emphasis on areas in which improvements are needed.

An accurate calculation of uniform microstrip transmission lines

An analytical program for calculating the field distribution about a microstrip transmission line bounded by a shielding wall is used to calculate the impedance, velocity, and attenuation parameters. The program input parameters are the dimensions of the strip and shielding wall and the relative dielectric constant of the substrate material. The field distribution about the strip is integrated to find the charge density on the strip and walls with and without the dielectric substrate. From these two calculations, the relative velocity and impedance can be calculated.

An Accurate Calculation of Uniform Microstrip Transmission Lines

An analytical program for calculating the field distribution about a microstrip transmission line bounded by a shielding wall is used to calculate the impedance, velocity, and attenuation parameters. The program input parameters are the dimensions of the strip and shielding wall and the relative dielectric constant of the substrate material. The field distribution about the strip is integrated to find the charge density on the strip and walls with and without the dielectric substrate. From these two calculations, the relative velocity and impedance can be calculated.

An Accurate Calculation of Uniform Microstrip Transmission Lines

An analytical program for calculating the field distribution about a microstrip transmission line bounded by a shielding wall is used to calculate the impedance, velocity, and attenuation parameters. The program input parameters are the dimensions of the strip and shielding wall and the relative dielectric constant of the substrate material. The field distribution about the strip is integrated to find the charge density on the strip and walls with and without the dielectric substrate. From these two calculations, the relative velocity and impedance can be calculated.