Optimal Test Sequence Research Articles

ON THE USE OF INTELLIGENT AGENTS TO GUIDE TEST SEQUENCE SELECTION AND OPTIMIZATION

Many of the automated testing tools concentrate on the automatic generation of test cases but do not worry about their optimization. In our paper, we analyzed the system model, which is represented as a state diagram and selected a very limited set of test sequences to be executed from the extreme large number (usually infinitely many) of potential ones. This paper demonstrates a way to generate optimal test sequences that are guaranteed to take the least possible time to execute and also satisfies both state and branch coverage criteria using Intelligent Agents. In the proposed approach, the Intelligent Search Agent (ISA) takes the decision of optimized test sequences by searching through the SUT, which is represented as a graph in which each node is associated with a heuristic value and each edge is associated with an edge weight. The Intelligent Agent finds the best sequence by following the nodes that satisfy the fitness criteria and generates the optimized test sequences for the SUT. Finally we compared our approach with existing Ant Colony Optimization (ACO)-based test sequence optimization approach and proved that our approach produces better results.

Hierarchical Test Sequencing for Complex Systems

Testing complex systems, such as the ASML TWINSCAN lithographic machine, is expensive and time consuming. In a previous work, a test sequencing method to calculate time-optimal test sequences has been developed. Because complex systems are composed of several subsystems, which are again composed of several modules, there exists a need to hierarchically model test sequencing problems. Such a hierarchical test sequencing problem consists of a high-level model that describes a test sequencing problem at the system level, and one or more low-level models that describe the test sequencing problems at the subsystem or module level. The tests at the system level correspond to the solutions of low-level problems. This paper describes a hierarchical test sequencing model and proposes two algorithms to compute an optimal test sequence. The benefits of hierarchically modeling a problem are less computational effort and less modeling effort, because not all relations are needed. This is illustrated by a small example. The industrial relevance of this method is illustrated on a case study related to a manufacturing testing phase of a lithographic machine.

Secondary hypoadrenalism

Secondary adrenal insufficiency (SAI) is a clinical disorder that results from hypothalamic or hypophyseal damage or from prolonged administration of supraphysiological doses of glucocorticoids. Since glucocorticoids are widely used for a variety of diseases, the prevalence of SAI is by far exceeding that of primary adrenal insufficiency. Although the presentation of adrenal insufficiency may be insidious and difficult to recognize, an appropriate adrenocortical hormone replacement could lead to a normal quality of life and longevity can be achieved. The spectrum of adrenal insufficiency ranges from overt adrenal crises to subtle dysfunctions in asymptomatic patients who may be at risk of developing acute adrenal insufficiency since their hypothalamic-pituitary-adrenal (HPA) axis cannot appropriately react to stress. Thus, identification of patients with subtle abnormalities of the HPA is mandatory for avoiding this life-threatening event in stressful conditions. The optimal tests and the optimal testing sequence for adrenal insufficiency are still matter of debate. Insulin tolerance test (ITT) could be the gold standard, as it tests the whole HPA axis, but there are some patients who pass the ITT failing the ACTH test. Various alternatives to the ITT, including the standard cosyntropin stimulation test (SST) and low-dose SST, have been proposed since the adrenal gland in SAI loses the capacity for a prompt response to ACTH stimulation. The standard ACTH dose, but not the 1 microg dose, increases adrenal blood flow and this may contribute to produce an early cortisol response of greater magnitude. Moreover, the loss of the early cortisol response to ACTH stimulation could be a specific property of adrenal insufficiency, thus being a sensitive and early marker of failing adrenal function. While the results of the SSTs are often positive in patients with long-standing and severe disease, in patients with mild or recent-onset SAI these tests, using either 250 microg or 1 microg ACTH, tend to give normal results; thus, a negative cosyntropin test result does not rule out the possibility of SAI. Further studies with a systematic comparison of the different tests in large series of patients submitted to a prolonged follow-up are needed to solve the controversy of the optimal diagnostic strategy of SAI.

IntelligenTester –Test Sequence Optimization Framework using Multi-Agents

Our paper focuses on the generation of optimal test sequences and test cases using Intelligent Agents for highly reliable systems. Test sequences support test case generation for these types of systems. Our system is modeled through UML state charts. Conventional test generation techniques do not worry about optimization and dynamic nature of such systems. In the case of highly reliable Software Testing, we can implement agents with sophisticated intellectual capabilities such as the ability to reason, learn, or plan. In our proposed approach, we developed agents namely Intelligent Search Agent (ISA) for optimal test sequence generation and Intelligent Test Case Optimization Agent (ITOA) based on HGA for optimal test case generation. Finally, we compared our results against existing algorithms. We registered our tool “IntelligenTester” under Java Research License (JRL) under the URL name https://intelligentester.dev.java.net.

A 2-OPT procedure to reduce total inspection time in a serial inspection process

In this paper, a 2-OPT based procedure is proposed to solve the test-sequencing problem in a serial inspection process. Applications of these methods are also extended to quiz problems with precedence constraints. Test problems are run on both the heuristic and the branch and bound methods and the results are reported. An optimal test sequence is found for a real world application, a radio inspection process, using data obtained from a high volume electronics manufacturer.

2.2.1 Test time reduction by optimal test sequencing1

AbstractTesting complex manufacturing systems, like ASML lithographic machines (ASML 2005), can take up to 45% of the total development time of a system. This test time can be reduced by choosing wisely which test cases must be performed in which sequence, without making investments in test cases or the system. With the test sequencing method, developed by (Boumen 2005, 2006), it is possible to make these decisions such that a time, cost and/or quality optimal test sequence can be constructed. This paper shows with two case studies that test time can be reduced up to 20% without loss of quality with this method. The first case study is related to the test phase during the manufacturing of a lithographic machine. The second case study is related to the reliability testing of a first of a kind lithographic machine.

Use of DST for Effective Dynamic Appraisal: Case Studies

This article, written by Technology Editor Dennis-Denney, contains highlights of paper SPE 97113, "Use of DST for Effective Dynamic Appraisal: Case Studies From Deep Offshore West Africa and Associated Methodology," by J.L.B. de la Combe, SPE, O. Akinwunmi, SPE, C. Dumay, and M. Tachon, Total S.A., prepared for the 2005 SPE Annual Technical Conference and Exhibition, Dallas, 9–12 October. In the west Africa deep offshore region, most turbiditic-series reservoirs are structural traps with a stratigraphic component and severe faulting. Evaluation of connectivity and characterization of the reservoir heterogeneities before development decisions are the main challenges. Two extended drillstem tests (DSTs) acquired at a relatively early stage of the appraisal had a significant effect on the development projects. Case Study 1 Well A was the third appraisal well of a Nigerian deepwater field. The well was the first in the southern fault block. Hydrocarbon presence had been proved in the central and northern compartments, but the southern compartment was separated from the central compartment by an east/west fault having significant throw. Formation-testing-log (FTL) measurements confirmed the presence of oil in the reservoir sands. Preliminary pressure/volume/temperature (PVT) analyses carried out on the FTL samples indicated a fluid very close to saturation pressure, while permeability estimates from FTL mobility and magnetic-resonance (MR) -log data indicated permeability ranging from 1 to 3 darcies. Therefore, it was decided to run a DST on the reservoir interval with perforations across the entire sand portion of the reservoir. Test Design. Well-test-design software was used to define an optimal test sequence. The major problem encountered in these deep offshore tests was programming a buildup test longer than 30 hours. Both gauge resolution and tidal effect strongly influence the late-time derivative, and even after deconvolution of tidal effect, it may not be possible to obtain a denoised signal because of high permeability of the unconsolidated sands in turbiditic channels. The other constraint was that bubblepoint pressure was very close to initial pressure. Thus, to avoid liberating gas in the reservoir, high flow rates could not be achieved. The design required two buildup tests to account for transient depletion between the two buildup tests. Different models do not generate the same transient depletion: a channel model generates more transient depletion than a single-fault model. Therefore, the well-test analyst can diagnose events that are beyond the buildup derivative. The cumulative oil produced during the drawdown between the two buildup tests was computed to generate a 50-kPa depletion for a connected reservoir with 8.7×106 m3 of stock-tank oil originally in place (STOOIP). A main objective was to characterize the seismic attenuation on the east side of the well. Data Overview. Because of problems during cleanup and a high skin value during the first buildup, BU1, another flow period and a second buildup, BU2, were performed. During the second flow period, with a large pressure drawdown, the derivative signature was perturbed by tidal effects after 10 hours' shut-in. The tidal effect was removed, and the buildup derivatives of BU2 and the final buildup, BU3, were compared after tide deconvolution. They were practically superposed. Therefore, BU2 and BU3 are selected for analysis because of their greater durations.

Advances in diagnostic testing

Within the past decade surrogate markers have become important and reliable tools for the early diagnosis of invasive aspergillosis. Surrogate markers include the antigens galactomannan and (1 --> 3)-beta-D-glucan for which commercial assays are available, as well as fungal DNA for which experimental PCR assays have been developed. Although many clinical validation studies have been performed, the kinetics of these markers are still largely unknown. Recent studies have addressed several issues related to variables that interact with the performance of the assays, including exposure to mould-active antifungal agents and the interpretive cut-off levels. Insights gained as a result of these studies will help us to further optimize management strategies and to determine the optimal test sequence.

Risk-sensitive decision-theoretic diagnosis

We consider the problem of determining the optimal sequence of tests for the discovery of a faulty component, where there is a random cost associated with testing a component. Our work is motivated by applications in telecommunications networks, e.g., location and isolation of faults (or intruders) in IP networks. A novel feature in our approach is that a risk-sensitive performance criterion is used in order to rank different competing schedules. Risk-sensitivity is incorporated through the use of an exponential utility function, and hence optimal schedules attain a trade-off between minimal expected costs and, e.g., a low variance about the achievable expected costs. We characterize optimal schedules both when the testing sequence is not subject to precedence constraints, and when it is subject to such constraints, given by an arbitrary partial order. For the case with precedence constraints, we show that our models can be analyzed via modular decompositions, as studied by Monma and Sidney (1987).

Sequential testing algorithms for multiple fault diagnosis

We consider the problem of constructing optimal and near-optimal test sequences for multiple fault diagnosis. The computational complexity of solving the optimal multiple-fault isolation problem is super exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and AND/OR graph search and by exploiting the single fault testing strategies of Pattipati et al. (1990), we present several test sequencing algorithms for the multiple fault isolation problem. These algorithms provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a diagnostic directed graph, instead of a traditional diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. The algorithms developed herein have been successfully applied to several real-world systems.

An extended-UIO-based method for protocol conformance testing

Verification of protocols is performed through conformance testing. The aim of this paper is to introduce the conformance test generation approach for protocols described by means of Finite State Machines. A functional fault model is adopted and the state discrimination is performed by applying an extended version of Unique Input Output Sequences (UIO), which, different from classical UIO, can always be found in any state. Both algorithms for efficient extended UIO sequence identification and for optimal test sequence generation are presented, together with the experimental results on different protocol descriptions.

Optimizing Diagnostic Test Sequences: The Probability Modifying Plot

The problem of deciding the optimal sequence of diagnostic tests can be structured in decision trees, but unmanageable bushy decision trees result when the sequence of two or more tests is investigated. Most modelling techniques include tests on the basis of gain in certainty. The aim of this study was to explore a model for optimizing the sequence of diagnostic tests based on efficiency criteria. The probability modifying plot shows, when in a specific test sequence further testing is redundant and which costs are involved. In this way different sequences can be compared. The model is illustrated with data on urinary tract infection. The sequence of diagnostic tests was optimized on the basis of efficiency, which was either defined as the test sequence with the least number of tests or the least total cost for testing. Further research on the model is needed to handle current limitations.

Optimal and near-optimal test sequencing algorithms with realistic test models

In this paper, we first present the formulation and solution of the basic test sequencing problem. We then consider generalized test sequencing problems that incorporate various practical features such as precedence constraints and setup operations for tests, multi-outcome tests, modular diagnosis, and rectification. We develop various AO/sup */ and information heuristic-based algorithms to solve these practical test sequencing problems. We also discuss the issues involved in implementation of the test sequencing algorithms for solving large problems efficiently, and show that our preprocessing techniques result in considerable speed-ups.

Temperature‐based optimal test sequence for determining the equivalent circuit parameters of a three‐phase induction motor

Typical routine tests for an induction motor equivalent circuit such as a no‐load test, locked‐rotor test and resistance measurement are described in several testing standards along with specific procedures. However, these standards do not emphasize the sequence in which the tests should be carried out and the appropriate time duration of each test. In this paper, the importance of temperature rise during the test procedure is pointed out and an optimal test sequence for determining an induction motor equivalent circuit is proposed. A three‐phase 2 HP squirrel cage motor operating performance is determined by real load tests and computer simulation. Comparing the two results, it was found that the proposed temperature‐based test sequence gives more accuracy and consistent parameters, which would result in better prediction in motor performance simulation.

Cost-effectiveness of Noninvasive Diagnostic Aids in Suspected Pulmonary Embolism

Noninvasive instruments such as plasma D-dimer measurement (DD) and lower-limb compression ultrasonography (US) are being increasingly advocated to reduce the number of necessary angiograms in patients having suspected pulmonary embolism (PE) and a nondiagnostic lung scan. We therefore designed a decision analysis model (1) to evaluate the cost-effectiveness of combining these noninvasive diagnostic aids with lung scan and angiography in the diagnosis of PE and (2) to determine the optimal sequence and combination of tests taking into account the clinical probability of PE. We performed a cost-effectiveness analysis based on literature data, including data from a management study in our institution. Six diagnostic strategies were compared with the reference, ie, lung scan followed when nondiagnostic (low or intermediate probability) by angiography. In all strategies, PE was ruled out by a normal or near-normal scan, a negative DD (plasma level below 500 micrograms/L), or a negative angiogram. Pulmonary embolism was diagnosed and anticoagulant treatment was undertaken in the presence of a high-probability lung scan, deep vein thrombosis showed by US, or a positive angiogram. In case of a nondiagnostic scan (low or intermediate probability), patients could be either treated or not treated, or undergo other tests, according to the selected strategy. Under baseline conditions (prevalence of PE, 35%), strategies combining DD and US with lung scan, angiography being done only in case of an inconclusive noninvasive workup (DD level > 500 micrograms/L, normal US, and nondiagnostic lung scan), were most cost-effective. This approach yielded a 9% incremental cost reduction and a 37% to 47% decrease in the number of necessary angiograms compared with the reference strategy (scan +/- angiography). For patients with a low clinical probability of PE (< or = 20%), withholding treatment from those with a low-probability lung scan without performing an angiogram proved safe and highly cost-effective (30% cost reduction), provided US showed no deep vein thrombosis. The DD test and US are cost-effective in the diagnostic workup of PE, whether performed after or before lung scan, thus allowing centers devoid of lung scanning and/or angiography facilities to screen patients with suspected PE and avoid costly referrals. In patients with a low clinical probability, a low-probability lung scan, and a normal US, treatment may be withheld without resorting to angiography.

Testing linear operators—An average case study

Given a specification linear operatorS, we want to test an implementation linear operatorA and determine whether it conforms to the specification operator according to an error criterion. In an earlier paper [3], we studied a worst case error in which we test whether the error is no more than a given bound ε>0 for all elements in a given setF, i.e., sup fεf∥Sf—Af∥≤ε. In this work, we study the average error instead, i. e., ∫ F ∥Sf-Af∥2μ(df)ɛ≤2, where μ is a probability measure onF. We assume that an upper boundK on the norm of the difference ofS andA is given a priori. It turns out that any finite number of tests is in general inconclusive with the average error. Therefore, as in the worst case, we allow a relaxation parameter α>0 and test for weak conformance with an error bound (1+α)ε. Then a finite number of tests from an arbitrary orthogonal complete sequence is conclusive. Furthermore, the eigenvectors of the covariance operatorC μ of the probability measure μ provide an almost optimal test sequence. This implies that the test set isuniversal; it only depends on the set of valid inputsF and the measure μ, and is independent ofS, A, and the other parameters of the problem. However, the minimal number of tests does depend on all the parameters of the testing problem, i.e., ε, α,K, and the eigenvalues ofC μ. In contrast to the worst case setting, it also depends on the dimensiond of the range space ofS andA.

Using action-based hierarchies for real-time diagnosis

An intelligent agent diagnoses perceived problems so that it can respond to them appropriately. Basically, the agent performs a series of tests whose results discriminate among competing hypotheses. Given a specific diagnosis, the agent performs the associated action. Using the traditional information-theoretic heuristic to order diagnostic tests in a decision tree, the agent can maximize the information obtained from each successive test and thereby minimize the average time (number of tests) required to complete a diagnosis and perform the appropriate action. However, in real-time domains, even the optimal sequence of tests cannot always be performed in the time available. Nonetheless, the agent must respond. For agents operating in real-time domains, we propose an alternative action-based approach in which: (a) each node in the diagnosis tree is augmented to include an ordered set of actions, each of which has positive utility for all of its children in the tree; and (b) the tree is structured to maximize the expected utility of the action available at each node. Upon perceiving a problem, the agent works its way through the tree, performing tests that discriminate among successively smaller subsets of potential faults. When a deadline occurs, the agent performs the best available action associated with the most specific node it has reached so far. Although the action-based approach does not minimize the time required to complete a specific diagnosis, it provides positive utility responses, with step-wise improvements in expected utility, throughout the diagnosis process. We present theoretical and empirical results contrasting the advantages and disadvantages of the information-theoretic and action-based approaches.

Optimization of failure diagnosis procedure based on diagnosis error loss

AbstractBased on the results of its inspection items, the failure diagnosis system identifies the cause of system failure. The role of failure diagnosis is to identify the system state correctly. However, diagnosis errors may be caused by sensor failure or operator errors, which lead to serious damage or unnecessary protective actions. The effect of an error depends on the system condition. In the design of a failure diagnosis procedure, not only diagnosis error probabilities, but also the effect of diagnosis error on the system must be considered.This paper proposes the optimization of failure diagnosis procedures based on diagnosis error loss. The optimal procedure that minimizes the expected loss caused by inspection errors is developed for two cases: one where all results of inspection items are given simultaneously, and one where an inspection item is examined sequentially. In the former case the optimal failure diagnosis logic is obtained, while in the latter case the optimal test sequence is developed. Illustrative examples show the merits and details of the proposed method.

Neurex: a tutorial expert system for the diagnosis of neurogenic diseases of the lower limbs

Specialist tutors have to transfer two types of knowledge to doctors who are specialising in a particular clinic: public declarative knowledge, including facts, notions, principles in that particular field; and their own private procedural knowledge acquired in years of direct experience. Embodying this knowledge into an expert system means that this information can be shared more rapidly, and tutoring is easier. This paper presents a tutorial expert system for neurological clinics which can emulate the diagnostic process of an expert neurologist for neurogenic diseases of the lower limbs, assist users in planning the optimal sequence of NG and EMG tests, interpret the results of these tests, and help users to achieve the most suitable diagnosis.

Optimization of Failure Diagnosis Procedure Based on Diagnosis Error Loss.

Based on the results of its inspection items, the failure diagnosis system identifies the cause of system failure. The role of failure diagnosis is to identify the system state currectly. However, diagnosis errors may be caused by sensor failure or operator errors, which lead to serious damage or unnecessary protective actions. The effect of an error depends on the system condition. In the design of failure diagnosis procedure, not only diagnosis error probability, but also its effect on the system must be considered.This paper proposes the optimization of failure diagnosis procedures based on diagnosis error loss. The optimal procedure that minimizes the expected loss caused by inspection errors is developed for two cases: one where all results of inspection items are given simultaneously and one where an inspection item is examinied sequentially. In the former case the optimal failure diagnosis logic is obtained, while in the latter case the optimal test sequence is obtained. Illustrative examples show the merits and details of the proposed method.