Efficient Testing Strategy Research Articles

Adaptive and Random Partition Software Testing

Random testing (RT) and subdomain testing are two major software testing strategies. Their simplicity makes them likely the most efficient testing strategies with respect to the time required for test case selection. However, the disadvantage of RT is its defect detection effectiveness. Adaptive testing (AT) is a feedback-based software testing strategy that has been shown to be more effective than RT and partition testing (PT). However, a major concern in the application of AT is its complexity and computational cost for test case selection. In this paper, we propose a hybrid approach that uses AT and random partition testing (RPT) in an alternating manner. The motivation for this approach is that both strategies are employed such that the underlying computational complexity of AT is reduced by introducing RPT into the testing process without affecting the defect detection effectiveness. A case study with seven real-life subject programs is presented. The experimental results demonstrate that this novel strategy considerably reduces the computational overhead of the original AT strategy but still outperforms the pure RT strategy and PT strategy in terms of the number of test cases used to detect and remove a given number of defects. In addition, a sensitivity analysis is conducted to validate the robustness of our strategy.

Automatic Generation of Data Flow Test Paths using a Genetic Algorithm

testing a program involves generating all paths through the program, and finding a set of program inputs that will execute every path. Since it is impossible to cover all paths in a program, path testing can be relaxed by selecting a subset of all executable paths that fulfill a certain path selection criterion and finding test data to cover it. The automatic generation of such test paths leads to more test coverage paths thus resulting in efficient and effective testing strategy. This paper presents a structural-oriented technique that uses a genetic algorithm (GA) for automatic generation of a set of test paths that cover the all-uses criterion. In the case of programs that have loops, the proposed technique generates paths according to the ZOT-subset criterion, which requires paths that traverse loops zero, one and two times. The proposed GA uses a binary vector as a chromosome to represent the edges in the DD-graph of the program under test. The set of paths generated by the proposed GA can be passed to a test data generation tool to find program inputs that will execute them. Experiments have been carried out to evaluate the effectiveness of the proposed GA compared to the random test path generation technique.

Neoadjuvant chemotherapy for breast cancer: a role for short-term fasting?

443 ISSN 1758-1923 10.2217/BMT.13.49 © 2013 Future Medicine Ltd Breast Cancer Manage. (2013) 2(6), 443–446 Breast cancer is the second leading cause of cancer death in women in the USA. An estimated 232,340 women will be diagnosed with breast cancer in 2013, with approximately 90% of women with breast cancer presenting with loco-regional disease [1]. Traditionally, most women undergo a definitive surgical procedure that allows for accurate staging followed by treatment plans consisting of systemic chemotherapy and radiation commensurate with staging and guideline recommendations. Systemic chemotherapy is critical to eradicate occult micrometastatic disease after surgery. Adjuvant chemotherapy regimens have gone through rigorous head-tohead comparison in the past three decades, with anthracycline–taxane combinations regarded as the most active chemotherapy regimens for HER2-negative breast cancer [2]. Neoadjuvant chemotherapy has been established as a reasonable alternative for adjuvant chemotherapy, since multiple large randomized clinical trials have demonstrated that neoadjuvant chemotherapy provides identical disease-free (DFS) and overall survival (OS) benefits as adjuvant chemotherapy administered with the same regimens [3,4]. Neoadjuvant chemotherapy has also been shown to increase the breast conservation rate and decrease the rate of complete axillary lymph node dissection. Often, neoadjuvant chemotherapy represents the only reasonable option for women who present with more locally advanced disease and desire breast conservation. More importantly, response to neoadjuvant chemotherapy portends a good prognosis. Women with breast cancer that achieves a pathological complete remission (pCR) are expected to have excellent DFS and OS [5]. Irrespective of the different definitions of pCR in various clinical trials, the absence of invasive disease in both the breast and lymph nodes provides the best overall outcome. Evaluation of tumor responses to neoadjuvant regimens in patients who have not previously been exposed to any other systemic therapies could offer an efficient testing strategy to different regimens or interventions. Unfortunately, up to 75% of women do not achieve pCR when they are treated with anthracycline–taxane-based neoadjuvant chemotherapy [5]. Among those with four to nine positive axillary lymph nodes

The mode of action (MOA) approach reveals interactive effects of environmental pharmaceuticals on Mytilus galloprovincialis

Aquatic organisms are unintentionally exposed to a large number of pharmaceutical residues in their natural habitats. Ecotoxicological studies have agreed that these compounds are not harmful to aquatic organisms, as their environmental concentrations are typically too low. However, recent reports have shown biological effects at such low concentrations when biological endpoints related to the therapeutic effects are assessed. Therefore, conservation of molecular targets is now addressed as a key aspect for the development of more efficient test strategies for pharmaceutical environmental risk assessment, providing the rationale for the mode of action (MOA) approach. In the present study the MOA approach was used to investigate the interactive effects of fluoxetine (FX) and propranolol (PROP) on the Mediterranean mussels (Mytilus galloprovincialis). Indeed, organisms in the environment are exposed to pharmaceutical mixtures throughout their lifetime, and particular combinations may be of concern. The antidepressant FX increases serotonin (5-HT) levels in the synaptic cleft by inhibiting 5-HT reuptake. PROP, a prototypical β-adrenoceptor antagonist, also blocks 5-HT1 receptors, which are negatively coupled to cAMP-mediated signaling. Cell signaling alterations potentially triggered by 5-HT1 receptor occupation were therefore assessed after a 7-day mussel exposure to FX or PROP, alone or in combination, each at 0.3ng/L concentration. FX decreased cAMP levels and PKA activities in digestive gland and mantle/gonads, in agreement with an increased occupation of 5-HT1 receptors. PROP caused a decrease in cAMP levels and PKA activities in digestive gland and an increase in cAMP levels in mantle/gonads, consistent with a differential expression of adrenergic and 5-HT receptors in the two tissues. Co-exposure to FX and PROP provides significant indications for antagonistic effects of the pharmaceuticals, consistent with a direct (PROP) and indirect (FX) action on the same molecular target. Interestingly, FX induced over-expression of a 5-HT1 gene product, and PROP counteracted such increase when the mixture was administered, while having per se no effect. Finally, mRNA expression of the ABCB gene encoding the MXR-related transporter P-glycoprotein was reduced by both pharmaceuticals in the digestive gland, while decreased by FX, increased by PROP, and not affected by the mixture in mantle/gonads. Since transcription of this gene product is under cAMP/PKA modulation, the impairment of regulatory pathways triggered by low concentrations of pharmaceuticals have the potential to affect the ability of animals to elaborate strategies of defense or adaptation toward further stress factors. In this specific case, the pharmaceutical mixture limits the detrimental effects of the single compounds.

Sequential Testing of Chemicals When Costs Matter: A Value of Information Approach

ABSTRACT This article provides a set of general conditions to identify efficient sequential testing strategies when test information is uncertain. We first survey the Bayesian Value-of-Information (VOI) approach to test selection. Second, we extend the approach to study sequential testing systems as applied in toxicology, but also relevant in other domains. We show how the order of tests in the sequence and the stopping rule depend on prior beliefs, the diagnostic performance of tests, and testing costs. We illustrate our findings with an example from short-term genotoxicity testing and discuss implications for developing optimized sequential testing strategies for risk management of chemicals.

Thick composite design for hydrogen vessels: A contribution to composite design method

Hydrogen stock vessels add new product specifications because of higher pressure use. Today static application leads up to 700 bars. But pressure devices must resist, because of certification, at 3 times pressure (2100 bars). Composite vessels give material–structure potential solutions. But designers face limits of knowledge due to actual good practices of thick composite structures use. This paper presents levels of knowledge enrichment for designers (multi-scale experiments and models), analysis of process influence on models improvement, and a discussion for an efficient testing strategy (meaning virtual testing in order to reduce the number of tests and their costs).

Strategies for testing products in software product lines

The software product line engineering strategy enables the achievement of significant improvements in quality through reuse of carefully crafted software assets across multiple products. However, high levels of quality in the software product line assets, which are used to create products, must be accompanied by effective and efficient test strategies for the products in the software product line. The goal of this study is to understand which strategies for testing products in software product lines have been reported in the literature, enabling discussions on the significant issues, and also pointing out further research directions. A systematic literature review was carried out that identified two hundred seventy-three papers, published from the years 1998 and early in 2012. From such a set of papers, a systematic selection resulted in forty-one relevant papers. The analysis of the reported strategies comprised two important aspects: the selection of products for testing, and the actual test of products. The findings showed a range of strategies, dealing with both aspects, but few empirical evaluations of their effectiveness have been performed, which limits the inferences that can be drawn.

PLS-Optimal: A Stepwise D-Optimal Design Based on Latent Variables

Several applications, such as risk assessment within REACH or drug discovery, require reliable methods for the design of experiments and efficient testing strategies. Keeping the number of experiments as low as possible is important from both a financial and an ethical point of view, as exhaustive testing of compounds requires significant financial resources and animal lives. With a large initial set of compounds, experimental design techniques can be used to select a representative subset for testing. Once measured, these compounds can be used to develop quantitative structure-activity relationship models to predict properties of the remaining compounds. This reduces the required resources and time. D-Optimal design is frequently used to select an optimal set of compounds by analyzing data variance. We developed a new sequential approach to apply a D-Optimal design to latent variables derived from a partial least squares (PLS) model instead of principal components. The stepwise procedure selects a new set of molecules to be measured after each previous measurement cycle. We show that application of the D-Optimal selection generates models with a significantly improved performance on four different data sets with end points relevant for REACH. Compared to those derived from principal components, PLS models derived from the selection on latent variables had a lower root-mean-square error and a higher Q2 and R2. This improvement is statistically significant, especially for the small number of compounds selected.

Genomics, personalized medicine and cancer practice

► Early successes of targeted drugs and companion predictive tests support the idea that personalized medicine may improve drug development and patient outcomes ► The evaluation and adoption of personalized medicine approaches in clinical practice will depend on our commitment to the development of clinical and technology platforms, standard procedures, educational tools for care providers and patients and our willingness to share data and best practices. ► These activities will lead to efficient and effective testing and treatment strategies to improve the outcomes for cancer patients.

Implicit functional testing of switched current filter based on fault signatures

This article aims at defining an efficient test strategy for switched-current (SI) circuit testing. By checking the constructed signatures (impulse response samples) against the derived tolerance ranges, we can infer the correctness of the device under test without explicitly measuring the original performance parameters. We also describe a technique of mapping the tolerance ranges in the performance space to its associated tolerance ranges in the signature space (We call such a procedure implicit functional testing). Taking into account the specificity of SI circuit, catastrophic and parametric fault model for testing are constructed. A fifth order Butterworth low-pass filter and a sixth order Elliptic band-pass filter have been used as test benches to assess the effectiveness of the proposed technique. Test results demonstrate that high fault coverage can be achieved with low cost test equipments.

Optimizing in vivo Assessment of Nano/bio Interactions to Guide Safer Material Design

ABSTRACTThe rapid rate of discovery and development in the nanotechnology field will undoubtedly increase both human and environmental exposures to engineered nanomaterials. Whether these exposures pose a significant risk remains uncertain. Despite recent collective progress there remain gaps in our understanding of the nanomaterials physiochemical properties that drive or dictate biological responses. The development and implementation of rapid relevant and efficient testing strategies to assess these emerging materials prior to large-scale exposures could help advance this exciting field. I present a powerful approach that utilizes a dynamic in vivo zebrafish embryonic assay to rapidly define the biological responses to nanomaterial exposures. Early developmental life stages are often uniquely sensitive to environmental insults, due in part to the enormous changes in cellular differentiation, proliferation and migration required to form the required cell types, tissues and organs. Molecular signaling underlies all of these processes. Most toxic responses result from disruption of proper molecular signaling, thus, early developmental life stages are perhaps the ideal life stage to determine if nanomaterials perturb normal biological pathways. Through automation and rapid throughput approaches, a systematic and iterative strategy has been deployed to help elucidate the nanomaterials properties that drive biological responses.

Pilot study of high‐sensitivity troponin T testing to facilitate safe early disposition decisions in patients presenting to the emergency department with chest pain

Many patients present to emergency departments with chest pain, but little is known about this population and the safest, most efficient testing strategies. We assessed clinical risk stratification of all patients with chest pain and, on a subset, utility of high-sensitivity troponin at 4 and 6 h after pain onset in aiding disposition decisions. Patients with intermediate or high-risk chest pain presenting within 6 h of onset were eligible for detailed study of troponin testing and outcome. Confusion, inability to speak English or need for urgent angiography was exclusion. Troponin levels were performed on arrival and at 4, 6 and 10-24 h from chest pain onset. Follow up of 30 days assessed compliance with, and results of, further investigation. Chest pain accounted for 627 presentations over 112 days. Of 282 intermediate or high-risk presentations 144 (51%) presented more than 6 h after onset. The detailed study enrolled 52 patients with a troponin rise observed in 26%. In no cases did troponin increase between 6 and 10 h and, in five cases, fell. Follow up was achieved in 96%. Eight high-risk patients (40%) and four intermediate risk patients (13%) had positive stress tests. For discharged patients with outpatient investigations booked in emergency department 92% attended, while those with letters recommending investigations did not obtain testing. These preliminary data suggest that high-sensitivity troponin 6 h after chest pain onset may be diagnostically useful. Marked differences in outpatient testing attendance suggest bookings should be made before discharge.

Combined QF‐PCR and MLPA molecular analysis of miscarriage products: an efficient and robust alternative to karyotype analysis

To replace G-banded chromosome analysis for miscarriage products with a combined molecular approach: QF-PCR and MLPA, to increase efficiency, reduce costs, and improve the diagnostic success rate for these samples. A review of 10 years of karyotype results for miscarriages products indicated that 2.7% of nonmosaic chromosome imbalance would not be detected by the molecular approach. The molecular approach was validated on 117 samples in parallel with karyotype analysis; no discrepancies were detected. The molecular approach was implemented in September 2007, and in the first 18 months 500 samples were processed. In 500 samples, 117 samples (23%) were abnormal. Of these abnormalities, 64% were trisomies, 12% triploid, 11% monosomy X and 13% other abnormalities. When compared to karyotype analysis, the success rate was higher (95% cf 70%) and the reporting time was lower (88% within 28 days cf 79%). In addition, efficiency was higher as labour-intensive cell culture and karyotyping were replaced by batch testing and automated analysis. This molecular approach is less labour-intensive, allows a higher sample throughput and has a higher success rate than karyotype analysis; it is therefore an efficient and cost-effective diagnostic testing strategy for miscarriage products.

In vivo biodistribution and toxicity depends on nanomaterial composition, size, surface functionalisation and route of exposure

Anticipated growth of the nanotechnology industry has motivated the development of rapid, relevant and efficient testing strategies to evaluate the biological activity and toxic potential of the growing number of novel nanoparticles. Since nanoparticles may interact with biological systems in unforeseen ways, it is important that evaluation of nanomaterial–biological interactions cover a broad range of cell types, tissues, organs and systems. Here, we use the embryonic zebrafish as a dynamic whole animal (in vivo) assay to investigate the importance of chemical composition, size, surface functionalisation and route of exposure on nanomaterial–biological interactions and delineate nanomaterials that are biologically active from those that are not. Information gained using model systems, such as the embryonic zebrafish, can be used to direct the rational development of safer, less hazardous nanoparticles. Our results demonstrate the utility of this model as an effective and accurate tool to assess the biological activity and toxic potential of nanomaterials in a short period of time with minimal cost.

Assuring the quality of LIN ECUs

High quality and reliability are essential preconditions for the successful application of bus systems to modern automobiles. Due to the significant increase in the number of LIN (Local Interconnect Network) components used in automotive developments, efficient test strategies for this cost-efficient bus system are gaining in importance. Vector Informatik describes the current possibilities for testing LIN nodes according to the latest LIN conformance test specification. For Master nodes a new and efficient black box test strategy is presented based on the well-known development and simulation tool CANoe.LIN.

Towards more efficient testing strategies—Analyzing the efficiency of toxicity data requirements in relation to the criteria for classification and labelling

This contribution is based on the assumption that the aim of toxicity testing as required by chemicals legislation is to identify as many chemicals of concern to human health and the environment as possible, given a limited amount of resources allocated to testing. Based on this assumption we propose a method for the optimization of test systems for industrial chemicals, based on the calculation of efficiency ratios for tests and test systems. The efficiency ratio of a toxicity test depends on the monetary cost of performing the test and the probability that the test will identify a chemical of concern, as estimated by the rules for classification and warning labelling. Efficiency ratios are estimated based on the results of basic standardized toxicity testing for acute toxicity, subacute toxicity, irritation and sensitization of 1409 industrial chemicals notified in the European Union between 1994 and 2004. This careful evaluation of the regulatory consequences of testing indicated that many of these substances are classified based on short-term testing of acute toxicity, irritation and sensitization and that most of the substances classified due to a 28-day study were also classified based on short-term testing. These results indicate that, within the classification and labelling system, it is currently more efficient to perform short-term testing of a larger number of substances rather than to perform subacute toxicity studies on substances already tested for acute toxicity.

Deletions or duplications in KCNQ2 can cause benign familial neonatal seizures

Background:Benign familial neonatal seizures are most often caused by mutations in the voltage-gated potassium channel subunit gene KCNQ2. More than 60 mutations have been described in BFNS families, approximately half...

Investigation into the Use of Hybrid Solutions for ΣΔ A/D Converter Testing

?? ADCs are now extensively used in electronic system applications requiring high resolution analogue to digital interfaces. Many of these applications require low cost solutions that imply the need for efficient production test strategies for verifying performance specifications. Industrial state-of-the-art is based on DSP testing to extract dynamic performance such as THD and SNR from an FFT on a sampled bit-stream from the decimator output. This method is computationally expensive and as resolution increases, the total number of samples required also increases thus pushing total test time beyond acceptable limits. This paper proposes an alternative hybrid solution based on an initial low-cost wafer level screening test followed by a DSP based technique on marginal devices based on alternative DSP transforms. The screening test is applied to the high-frequency bit-stream output of the ?? modulator and has potential for on-chip implementation. Relatively simple algorithms and cross-correlation techniques are used that can associate specific changes in the bit-stream pattern to key failure modes affecting dynamic performance parameters. A simplified supplementary DSP test for marginal devices is proposed that is less computationally intensive than FFT analysis.

LEAD: A Methodology for Learning Efficient Approaches to Medical Diagnosis

Determining the most efficient use of diagnostic tests is one of the complex issues facing medical practitioners. With the soaring cost of healthcare, particularly in the US, there is a critical need for cutting costs of diagnostic tests, while achieving a higher level of diagnostic accuracy. This paper develops a learning based methodology that, based on patient information, recommends test(s) that optimize a suitable measure of diagnostic performance. A comprehensive performance measure is developed that accounts for the costs of testing, morbidity, and mortality associated with the tests, and time taken to reach diagnosis. The performance measure also accounts for the diagnostic ability of the tests. The methodology combines tools from the fields of data mining (rough set theory, in particular), utility theory, Markov decision processes (MDP), and reinforcement learning (RL). The rough set theory is used in extracting diagnostic information in the form of rules from the medical databases. Utility theory is used in bringing various nonhomogenous performance measures into one cost based measure. An MDP model together with an RL algorithm facilitates obtaining efficient testing strategies. The methodology is implemented on a sample problem of diagnosing solitary pulmonary nodule (SPN). The results obtained are compared with those from four alternative testing strategies. Our methodology holds significant promise to improve the process of medical diagnosis.

A Testing Framework for Identifying Susceptibility Genes in the Presence of Epistasis

An efficient testing strategy called the "focused interaction testing framework" (FITF) was developed to identify susceptibility genes involved in epistatic interactions for case-control studies of candidate genes. In the FITF approach, likelihood-ratio tests are performed in stages that increase in the order of interaction considered. Joint tests of main effects and interactions are performed conditional on significant lower-order effects. A reduction in the number of tests performed is achieved by prescreening gene combinations with a goodness-of-fit chi2 statistic that depends on association among candidate genes in the pooled case-control group. Multiple testing is accounted for by controlling false-discovery rates. Simulation analysis demonstrated that the FITF approach is more powerful than marginal tests of candidate genes. FITF also outperformed multifactor dimensionality reduction when interactions involved additive, dominant, or recessive genes. In an application to asthma case-control data from the Children's Health Study, FITF identified a significant multilocus effect between the nicotinamide adenine dinucleotide (phosphate) reduced:quinone oxidoreductase gene (NQO1), myeloperoxidase gene (MPO), and catalase gene (CAT) (unadjusted P = .00026), three genes that are involved in the oxidative stress pathway. In an independent data set consisting primarily of African American and Asian American children, these three genes also showed a significant association with asthma status (P = .0008).