AUTOMATED GENERATION OF TEST TRAJECTORIES FOR EMBEDDED FLIGHT CONTROL SYSTEMS

2002 ◽  
Vol 12 (02) ◽  
pp. 175-200 ◽  
Author(s):  
BOJAN CUKIC ◽  
BRIAN J. TAYLOR ◽  
HARSHINDER SINGH
Keyword(s):  
Linear Regression ◽  
Control Systems ◽  
Test Data ◽  
Flight Control ◽  
Performance Metrics ◽  
Large Set ◽  
Data Generation ◽  
Statistical Regression ◽  
Automated Generation ◽  
Independent Variables

Automated generation of test cases is a prerequisite for fast testing. Whereas the research in automated test data generation addressed the creation of individual test points, test trajectory generation has attracted limited attention. In simple terms, a test trajectory is defined as a series of data points, with each (possibly multidimensional) point relying upon the value(s) of previous point(s). Many embedded systems use data trajectories as inputs, including closed-loop process controllers, robotic manipulators, nuclear monitoring systems, and flight control systems. For these systems, testers can either handcraft test trajectories, use input trajectories from older versions of the system or, perhaps, collect test data in a high fidelity system simulator. While these are valid approaches, they are expensive and time-consuming, especially if the assessment goals require many tests. We developed a framework for expanding a small, conventionally developed set of test trajectories into a large set suitable, for example, for system safety assurance. Statistical regression is the core of this framework. The regression analysis builds a relationship between controllable independent variables and closely correlated dependent variables, which represent test trajectories. By perturbing the independent variables, new test trajectories are generated automatically. Our approach has been applied in the safety assessment of a fault tolerant flight control system. Linear regression, multiple linear regression, and autoregressive techniques are compared. The performance metrics include the speed of test generation and the percentage of "acceptable" trajectories, measured by the domain specific reasonableness checks.

scholarly journals Automated Test Data Generation Based on a Genetic Algorithm with Maximum Code Coverage and Population Diversity

2021 ◽  
Vol 11 (10) ◽  
pp. 4673
Author(s):  
Tatiana Avdeenko ◽  
Konstantin Serdyukov
Keyword(s):  
Test Data ◽  
Fitness Function ◽  
Population Diversity ◽  
Test Case ◽  
Test Cases ◽  
Data Generation ◽  
Intelligent Support ◽  
Automated Generation ◽  
Code Coverage ◽  
Automated Test Data Generation

In the present paper, we investigate an approach to intelligent support of the software white-box testing process based on an evolutionary paradigm. As a part of this approach, we solve the urgent problem of automated generation of the optimal set of test data that provides maximum statement coverage of the code when it is used in the testing process. We propose the formulation of a fitness function containing two terms, and, accordingly, two versions for implementing genetic algorithms (GA). The first term of the fitness function is responsible for the complexity of the code statements executed on the path generated by the current individual test case (current set of statements). The second term formulates the maximum possible difference between the current set of statements and the set of statements covered by the remaining test cases in the population. Using only the first term does not make it possible to obtain 100 percent statement coverage by generated test cases in one population, and therefore implies repeated launch of the GA with changed weights of the code statements which requires recompiling the code under the test. By using both terms of the proposed fitness function, we obtain maximum statement coverage and population diversity in one launch of the GA. Optimal relation between the two terms of fitness function was obtained for two very different programs under testing.

scholarly journals A Data-Driven Approach to Identify Flight Test Data Suitable to Design Angle of Attack Synthetic Sensor for Flight Control Systems

Aerospace ◽  
2020 ◽  
Vol 7 (5) ◽  
pp. 63 ◽  
Author(s):  
Angelo Lerro ◽  
Alberto Brandl ◽  
Manuela Battipede ◽  
Piero Gili
Keyword(s):  
Control Systems ◽  
Test Data ◽  
Flight Control ◽  
Flight Test ◽  
Data Driven ◽  
Training Set ◽  
Consequent Reduction ◽  
Data Driven Approach ◽  
Data Points ◽  
Data Pruning

Digital avionic solutions enable advanced flight control systems to be available also on smaller aircraft. One of the safety-critical segments is the air data system. Innovative architectures allow the use of synthetic sensors that can introduce significant technological and safety advances. The application to aerodynamic angles seems the most promising towards certified applications. In this area, the best procedures concerning the design of synthetic sensors are still an open question within the field. An example is given by the MIDAS project funded in the frame of Clean Sky 2. This paper proposes two data-driven methods that allow to improve performance over the entire flight envelope with particular attention to steady state flight conditions. The training set obtained is considerably undersized with consequent reduction of computational costs. These methods are validated with a real case and they will be used as part of the MIDAS life cycle. The first method, called Data-Driven Identification and Generation of Quasi-Steady States (DIGS), is based on the (i) identification of the lift curve of the aircraft; (ii) augmentation of the training set with artificial flight data points. DIGS’s main aim is to reduce the issue of unbalanced training set. The second method, called Similar Flight Test Data Pruning (SFDP), deals with data reduction based on the isolation of quasi-unique points. Results give an evidence of the validity of the methods for the MIDAS project that can be easily adopted for generic synthetic sensor design for flight control system applications.

scholarly journals Seeding Grammars in Grammatical Evolution to Improve Search-Based Software Testing

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Muhammad Sheraz Anjum ◽  
Conor Ryan
Keyword(s):  
Test Data ◽  
Original System ◽  
Optimization Techniques ◽  
Grammatical Evolution ◽  
Benchmark Problems ◽  
Large Set ◽  
Data Generation ◽  
Code Coverage ◽  
Order Of Magnitude ◽  
Generate Test Data

AbstractHeuristic-based optimization techniques have been increasingly used to automate different types of code coverage analysis. Several studies suggest that interdependencies (in the form of comparisons) may exist between the condition constructs, of variables and constant values, in the branching conditions of real-world programs, e.g. ($$i \le 100$$ i ≤ 100 ) or ($$i==j$$ i = = j ), etc. In this work, by interdependencies we refer to the situations where, to satisfy a branching condition, there must be a certain relationship between the values of some specific condition constructs (which may or may not be a part of the respective condition predicates). For example, the values of variables i and j must be equal to satisfy the condition of ($$i==j$$ i = = j ), and the value of variable k must be equal to 100 for the satisfaction of the condition of ($$k==100$$ k = = 100 ). To date, only the Ariadne, a Grammatical Evolution (GE)-based system, exploits these interdependencies between input variables (e.g. of the form ($$i \le j$$ i ≤ j ) or ($$i==j$$ i = = j ), etc.) to efficiently generate test data. Ariadne employs a simple attribute grammar to exploit these dependencies, which enables it to evolve complex test data, and has been compared favourably to other well-known techniques in the literature. However, Ariadne does not benefit from interdependencies involving constants, e.g. ($$i \le 100$$ i ≤ 100 ) or ($$j==500$$ j = = 500 ), etc., due to the difficulty in evolving precise values, and these are equally important constructs of condition predicates. Furthermore, constant creation in GE can be difficult, particularly with high precision. We propose to seed the grammar with constants extracted from the source code of the program under test to enhance and extend Ariadne’s capability to exploit richer types of dependencies (involving all combinations of both variables and constant values). We compared our results with the original system of Ariadne against a large set of benchmark problems which include 10 numeric programs in addition to the ones originally used for Ariadne. Our results demonstrate that the seeding strategy not only dramatically improves the generality of the system, as it improves the code coverage (effectiveness) by impressive margins, but it also reduces the search budgets (efficiency) often up to an order of magnitude. Moreover, we also performed a rigorous analysis to investigate the scalability of our improved Ariadne, showing that it stays highly scalable when compared to both the original system of Ariadne and GA-based test data generation approach.

scholarly journals Automatic Test Data Generation Using the Activity Diagram and Search-Based Technique

2020 ◽  
Vol 10 (10) ◽  
pp. 3397 ◽  
Author(s):  
Aman Jaffari ◽  
Cheol-Jung Yoo ◽  
Jihyun Lee
Keyword(s):  
Fault Detection ◽  
Test Data ◽  
Large Set ◽  
Generation Process ◽  
Test Data Generation ◽  
Test Automation ◽  
Data Generation ◽  
Activity Diagram ◽  
Coverage Criterion ◽  
Better Than

In software testing, generating test data is quite expensive and time-consuming. The manual generation of an appropriately large set of test data to satisfy a specified coverage criterion carries a high cost and requires significant human effort. Currently, test automation has come at the cost of low quality. In this paper, we are motivated to propose a model-based approach utilizing the activity diagram of the system under test as a test base, focusing on its data flow aspect. The technique is incorporated with a search-based optimization heuristic to fully automate the test data generation process and deliver test cases with more improved quality. Our experimental investigation used three open-source software systems to assess and compare the proposed technique with two alternative approaches. The experimental results indicate the improved fault-detection performance of the proposed technique, which was 11.1% better than DFAAD and 38.4% better than EvoSuite, although the techniques did not differ significantly in terms of statement and branch coverage. The proposed technique was able to detect more computation-related faults and tends to have better fault detection capability as the system complexity increases.

PENGARUH KARAKTERISTIK PEKERJAAN TERHADAP TURNOVER INTENTION PADA BEBERAPA RESTORAN MASAKAN ORIENTAL DI KOTA SURABAYA

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Tony Susilo Wibowo ◽  
I Made Bagus Dwiarta
Keyword(s):  
Linear Regression ◽  
Human Resources ◽  
Turnover Intention ◽  
Job Characteristics ◽  
Independent Variables ◽  
A Value ◽  
Industry Competition ◽  
Task Identity ◽  
Innovation Ability ◽  
Identity Task

 Culinary industry competition getting tougher to make some employers continue to innovate at a restaurant for some things like menu, places, atmosphere and service that became the mainstay of the restaurant. In so doing, it needs one innovation ability of human resources quality and competence in their field. Innovation will be a reminder for consumers who feel the restaurant services and in turn will increase the revenue thus achieved profit restaurant that is optimal.The selected researchers research object was 3rd Restaurant Oriental cuisine i.e. Kapin, X O Cuisine and Paradise Dynasty which respectively have 3 and 2 branches of the restaurant. This research uses the concept of job characteristics expressed by Hackman and Oldham (1976), which are further subdivided into 5 independent variables namely a diversity of tasks, task identity, task meaningful, autonomy and feedback as well as the dependent variable turnover intention, while the analysis on research using multiple linear regression with the respondent an amount of 120 people that consists of all the employees of the restaurant. Data processing results shows that the diversity of the variable assignments and most influential task ID with a value of beta X1  0,676 and the beta X 2 of 0,538 so that these two variables have a positive and significant impact on the turnover intention because the variable is greater than 0.05 alpha. While the 3 other variables i.e  tasks meaningful, autonomy and feedback does not affect significantly to turnover intention. Keywords: Job Characteristics, Turnover intention.  

ANALISIS VARIABEL YANG BERPENGARUH TERHADAP KINERJA PERUSAHAAN DI BURSA EFEK INDONESIA

2019 ◽  
Author(s):  
SUSENO - SUSENO
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Exchange ◽  
T Test ◽  
The Other ◽  
Financial Leverage ◽  
F Test ◽  
Research Results ◽  
Independent Variables ◽  
Influential Variable

ANALISIS VARIABEL YANG BERPENGARUH TERHADAP KINERJA PERUSAHAAN DI BURSA EFEK INDONESIAOleh : Suseno STIE SATRIA Purwokerto ABSTRACT The aims of the research are (1) to analyze influence of age, scale, financial leverage, and profitability to performance of firms at The Indonesian Stock Exchange. (2) to determine the most influential variable on the performance of the firms. Hypotheses proposed in this research were: (1) Age, Scales, Financial Leverage, Profitability influences the performance of firms, (2) Age influences the performance of firms, (3) Scales influences the performance of firms, (4) Financial Leverage influences the performance of firms, (5) Profitability influences the performance of firms. Instrument of analysis employed in the research was multiple linear regression with t test and F test.The results of analyses of t test showed that profitability did not influence the performance of the firms. It was indicated by the value of computed t which was smaller than the value of t table. Meanwhile, the t test of age, scale and financial leverage indicated that the value of computed t > t table. It means that these variables (scale and financial leverage) influenced the performance of the firms. The F test showed that the independent variables of age, scale, financial leverage and profitability as a whole significantly influenced the performance of the firms. It was indicated by the calculated F > the value of F table, the value the age computed t which was smaller than the value of -t table..Based on the research results that age and profitability do not influence the performance of the firms, it is suggested that investors should not pay any attention to those variables. On the other hand, they should pay attention to the variables of scale and financial leverage. It is recommended that for further research should include longer periode of the sample.

PENGARUH KUALITAS PELAYANAN DAN KEPERCAYAAN TERHADAP LOYALITAS NASABAH PT BANK MANDIRI,Tbk CABANG JAKARTA KELAPA GADING BARAT

2015 ◽  
Vol 3 (3) ◽  
Author(s):  
Imam Wibowo ◽  
Santi Putri Ananda
Keyword(s):  
Linear Regression ◽  
Service Quality ◽  
Multiple Linear Regression ◽  
Analysis Tool ◽  
Positive Contribution ◽  
Homogeneous Population ◽  
Independent Variables ◽  
Research Population ◽  
The Impact

Purpose-To study the impact of the service quality and trust on customers loyalty of PT.Bank Mandiri,Tbk; Kelapa Gading Barat Branch. To improve the customers loyalty there are several factors that can influence them, such as service quality and trust. Methodology/approach-The research population was all customers PT.Bank Mandiri,Tbk;Kelapa Gading Barat Branch.According to the homogeneous population and based on the Gay and Diehl Theory, the samples taken were 50 people. Variables in this investigations consisted of: a).Independent Variables (exogenous): Service Quality (X1) and Trust (X2). b).The dependent variable (endogenous) Customers Loyalty (Y). Analysis tool being used is multiple linear regression which previously conducted validity and realiability. Findings-The result of investigations that service quality and trust simultaneously have a very strong contribution of 75,5% to the customers loyalty, and partially showed that service quality has significant and positive contribution to the customers loyalty of 64,8%. Partially, the trust variable has significant and positive contribution which amounted to 55,9% to the customers loyalty.

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