scholarly journals Concurrency testing using symbolic path finder

2018 ◽  
Vol 7 (2.6) ◽  
pp. 275
Author(s):  
Bidush Kumar Sahoo ◽  
Mitrabinda Ray
Keyword(s):  
Symbolic Execution ◽  
Concurrent Programs ◽  
Test Case ◽  
Test Cases ◽  
Concurrent Program ◽  
Activity Complex ◽  
Race Condition ◽  
Concurrent Testing ◽  
Concurrency Testing ◽  
The Given

Concurrent programs have specific features such as italic communication, synchronization and nondeterministic behavior that make the testing activity complex. The objective is to find various types of concurrent defects. In this paper, we have used a model checking tool called Symbolic Path Finder (SPF) which is the upgradation of Java Path Finder (JPF) for concurrent testing. SPF is used for generating the test cases to check concurrent defects such as deadlock, race condition etc. SPF generates symbolic execution tree of the given code which is used as an input for test case generation. The execution is done for finding the test cases in concurrent program where number of threads is operating together with the concurrent defects. The test cases show the type of concurrent defects in the respective line number of the source code.  

scholarly journals Test case generation for object-oriented imperative languages in CLP

2010 ◽  
Vol 10 (4-6) ◽  
pp. 659-674 ◽  
Author(s):  
MIGUEL GÓMEZ-ZAMALLOA ◽  
ELVIRA ALBERT ◽  
GERMÁN PUEBLA
Keyword(s):  
Symbolic Execution ◽  
Object Oriented ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Software Development Process ◽  
Java Programs ◽  
Promising Application ◽  
Account Due ◽  
Imperative Language

AbstractTesting is a vital part of the software development process. Test Case Generation (TCG) is the process of automatically generating a collection of test-cases which are applied to a system under test. White-box TCG is usually performed by means of symbolic execution, i.e., instead of executing the program on normal values (e.g., numbers), the program is executed on symbolic values representing arbitrary values. When dealing with an object-oriented (OO) imperative language, symbolic execution becomes challenging as, among other things, it must be able to backtrack, complex heap-allocated data structures should be created during the TCG process and features like inheritance, virtual invocations and exceptions have to be taken into account. Due to its inherent symbolic execution mechanism, we pursue in this paper that Constraint Logic Programming (CLP) has a promising application field in tcg. We will support our claim by developing a fully CLP-based framework to TCG of an OO imperative language, and by assessing it on a corresponding implementation on a set of challenging Java programs.

scholarly journals Diversifying Focused Testing for Unit Testing

2021 ◽  
Vol 30 (4) ◽  
pp. 1-24
Author(s):  
Héctor D. Menéndez ◽  
Gunel Jahangirova ◽  
Federica Sarro ◽  
Paolo Tonella ◽  
David Clark
Keyword(s):  
Search Algorithm ◽  
Symbolic Execution ◽  
Specific Area ◽  
Test Suite ◽  
Constraint Solving ◽  
Test Case ◽  
Unit Testing ◽  
Bug Detection ◽  
Mutation Score ◽  
The Given

Software changes constantly, because developers add new features or modifications. This directly affects the effectiveness of the test suite associated with that software, especially when these new modifications are in a specific area that no test case covers. This article tackles the problem of generating a high-quality test suite to cover repeatedly a given point in a program, with the ultimate goal of exposing faults possibly affecting the given program point. Both search-based software testing and constraint solving offer ready, but low-quality, solutions to this: Ideally, a maximally diverse covering test set is required, whereas search and constraint solving tend to generate test sets with biased distributions. Our approach, Diversified Focused Testing (DFT), uses a search strategy inspired by GödelTest. We artificially inject parameters into the code branching conditions and use a bi-objective search algorithm to find diverse inputs by perturbing the injected parameters, while keeping the path conditions still satisfiable. Our results demonstrate that our technique, DFT, is able to cover a desired point in the code at least 90% of the time. Moreover, adding diversity improves the bug detection and the mutation killing abilities of the test suites. We show that DFT achieves better results than focused testing, symbolic execution, and random testing by achieving from 3% to 70% improvement in mutation score and up to 100% improvement in fault detection across 105 software subjects.

MODEL-BASED TESTING OF CONCURRENT PROGRAMS WITH PREDICATE SEQUENCING CONSTRAINTS

2006 ◽  
Vol 16 (05) ◽  
pp. 727-746 ◽  
Author(s):  
PENG WU ◽  
HUIMIN LIN
Keyword(s):  
Dynamic Test ◽  
Concurrent Programs ◽  
Test Cases ◽  
Data Dependency ◽  
Data Dependencies ◽  
Concurrent Program ◽  
Program Testing ◽  
Model Based Testing ◽  
Symbolic Test

A predicate sequencing constraint logic (PSCL) is proposed to represent test purpose for concurrent program testing. The logic is capable of expressing not only sequencing relationships among input and output events, but also data dependencies between event parameters. A PSCL-based symbolic test generation method is developed to automatically derive symbolic test cases that incorporate given data dependency constraints as verdict conditions. The method works in a syntactic way without referring to concrete program states and the derived test cases allow dynamic test data selection according to the response from the software under test. The advantage of the approach is demonstrated with a case study.

scholarly journals Test Case Prioritization & Selection for an Object Oriented Software using Genetic Algorithm.

2020 ◽  
Vol 9 (4) ◽  
pp. 349-354
Keyword(s):  
Genetic Algorithm ◽  
Object Oriented ◽  
Test Case ◽  
Test Cases ◽  
Test Case Prioritization ◽  
Test Case Selection ◽  
Case Selection ◽  
Selection For ◽  
The Given

In this paper our aim is to propose a Test Case Selection and Prioritization technique for OOP for ordering the test cases as per in accordance with their priority for finding the faults in the OOS. We have used the heuristic Genetic Algorithm, in order to generating the order of these prioritized test cases for a given OOS. The motive is to put a test case first into the ordered sequence that may have the highest prospective of finding an error in the given OOS & then soon..

scholarly journals Resource and dependency based test case generation for RESTful Web services

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Man Zhang ◽  
Bogdan Marculescu ◽  
Andrea Arcuri
Keyword(s):  
Web Services ◽  
Domain Knowledge ◽  
Automated System ◽  
Test Case ◽  
Test Cases ◽  
Evolutionary Search ◽  
Sampling Strategies ◽  
Mutation Operators ◽  
On Line ◽  
Restful Web Services

AbstractNowadays, RESTful web services are widely used for building enterprise applications. REST is not a protocol, but rather it defines a set of guidelines on how to design APIs to access and manipulate resources using HTTP over a network. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services, by exploiting domain knowledge on the handling of HTTP resources. The proposed techniques use domain knowledge specific to RESTful web services and a set of effective templates to structure test actions (i.e., ordered sequences of HTTP calls) within an individual in the evolutionary search. The action templates are developed based on the semantics of HTTP methods and are used to manipulate the web services’ resources. In addition, we propose five novel sampling strategies with four sampling methods (i.e., resource-based sampling) for the test cases that can use one or more of these templates. The strategies are further supported with a set of new, specialized mutation operators (i.e., resource-based mutation) in the evolutionary search that take into account the use of these resources in the generated test cases. Moreover, we propose a novel dependency handling to detect possible dependencies among the resources in the tested applications. The resource-based sampling and mutations are then enhanced by exploiting the information of these detected dependencies. To evaluate our approach, we implemented it as an extension to the EvoMaster tool, and conducted an empirical study with two selected baselines on 7 open-source and 12 synthetic RESTful web services. Results show that our novel resource-based approach with dependency handling obtains a significant improvement in performance over the baselines, e.g., up to + 130.7% relative improvement (growing from + 27.9% to + 64.3%) on line coverage.

scholarly journals From Stress to Shape: Equilibrium of Cloister and Cross Vaults

2021 ◽  
Vol 11 (9) ◽  
pp. 3846
Author(s):  
Andrea Montanino ◽  
Carlo Olivieri ◽  
Giulio Zuccaro ◽  
Maurizio Angelillo
Keyword(s):  
Error Function ◽  
Membrane Surface ◽  
Equilibrium Analysis ◽  
Test Cases ◽  
Order Partial Differential Equation ◽  
Negative Semidefinite ◽  
Historical Heritage ◽  
Masonry Vaults ◽  
Membrane Shape ◽  
The Given

The assessment of the equilibrium and the safety of masonry vaults is of high relevance for the conservation and restoration of historical heritage. In the literature many approaches have been proposed for this tasks, starting from the 17th century. In this work we focus on the Membrane Equilibrium Analysis, developed under the Heyman’s theory of Limit Analysis. Within this theory, the equilibrium of a vault is assessed if it is possible to find at least one membrane surface, between the volume of the vaults, being in equilibrium under the given loads through a purely compressive stress field. The equilibrium of membranes is described by a second order partial differential equation, which is definitely elliptic only when a negative semidefinite stress is assigned, and the shape is the unknown of the problem. The proposed algorithm aims at finding membrane shapes, entirely comprised between the geometry of the vault, in equilibrium with admissible stress fields, through the minimization of an error function with respect to shape parameters of the stress potential, and then, with respect to the boundary values of the membrane shape. The application to two test cases shows the viability of this tool for the assessment of the equilibrium of existing masonry vaults.

scholarly journals Performance of Enhanced Multiple-Searching Genetic Algorithm for Test Case Generation in Software Testing

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1779
Author(s):  
Wanida Khamprapai ◽  
Cheng-Fa Tsai ◽  
Paohsi Wang ◽  
Chi-En Tsai
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Random Search ◽  
Automatic Generation ◽  
Superior Performance ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Network Systems ◽  
Routing Problem

Test case generation is an important process in software testing. However, manual generation of test cases is a time-consuming process. Automation can considerably reduce the time required to create adequate test cases for software testing. Genetic algorithms (GAs) are considered to be effective in this regard. The multiple-searching genetic algorithm (MSGA) uses a modified version of the GA to solve the multicast routing problem in network systems. MSGA can be improved to make it suitable for generating test cases. In this paper, a new algorithm called the enhanced multiple-searching genetic algorithm (EMSGA), which involves a few additional processes for selecting the best chromosomes in the GA process, is proposed. The performance of EMSGA was evaluated through comparison with seven different search-based techniques, including random search. All algorithms were implemented in EvoSuite, which is a tool for automatic generation of test cases. The experimental results showed that EMSGA increased the efficiency of testing when compared with conventional algorithms and could detect more faults. Because of its superior performance compared with that of existing algorithms, EMSGA can enable seamless automation of software testing, thereby facilitating the development of different software packages.

scholarly journals Automated Search-Based Robustness Testing for Autonomous Vehicle Software

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Kevin M. Betts ◽  
Mikel D. Petty
Keyword(s):  
Monte Carlo ◽  
Performance Metrics ◽  
Initial Conditions ◽  
Autonomous Vehicle ◽  
Vehicle Control ◽  
Test Case ◽  
Test Cases ◽  
Control Software ◽  
Robustness Testing ◽  
Testing Techniques

Autonomous systems must successfully operate in complex time-varying spatial environments even when dealing with system faults that may occur during a mission. Consequently, evaluating the robustness, or ability to operate correctly under unexpected conditions, of autonomous vehicle control software is an increasingly important issue in software testing. New methods to automatically generate test cases for robustness testing of autonomous vehicle control software in closed-loop simulation are needed. Search-based testing techniques were used to automatically generate test cases, consisting of initial conditions and fault sequences, intended to challenge the control software more than test cases generated using current methods. Two different search-based testing methods, genetic algorithms and surrogate-based optimization, were used to generate test cases for a simulated unmanned aerial vehicle attempting to fly through an entryway. The effectiveness of the search-based methods in generating challenging test cases was compared to both a truth reference (full combinatorial testing) and the method most commonly used today (Monte Carlo testing). The search-based testing techniques demonstrated better performance than Monte Carlo testing for both of the test case generation performance metrics: (1) finding the single most challenging test case and (2) finding the set of fifty test cases with the highest mean degree of challenge.

scholarly journals PRIORITIZATION OF COMBINATORIAL TEST CASES BY INCREMENTAL INTERACTION COVERAGE

2013 ◽  
Vol 23 (10) ◽  
pp. 1427-1457 ◽  
Author(s):  
RUBING HUANG ◽  
XIAODONG XIE ◽  
DAVE TOWEY ◽  
TSONG YUEH CHEN ◽  
YANSHENG LU ◽  
...  
Keyword(s):  
Test Case ◽  
Test Cases ◽  
New Strategy ◽  
Testing Cost ◽  
Test Prioritization ◽  
Interaction Testing ◽  
Parameter Interactions ◽  
Combinatorial Interaction Testing ◽  
Alternative Assumption ◽  
Better Than

Combinatorial interaction testing is a well-recognized testing method, and has been widely applied in practice, often with the assumption that all test cases in a combinatorial test suite have the same fault detection capability. However, when testing resources are limited, an alternative assumption may be that some test cases are more likely to reveal failure, thus making the order of executing the test cases critical. To improve testing cost-effectiveness, prioritization of combinatorial test cases is employed. The most popular approach is based on interaction coverage, which prioritizes combinatorial test cases by repeatedly choosing an unexecuted test case that covers the largest number of uncovered parameter value combinations of a given strength (level of interaction among parameters). However, this approach suffers from some drawbacks. Based on previous observations that the majority of faults in practical systems can usually be triggered with parameter interactions of small strengths, we propose a new strategy of prioritizing combinatorial test cases by incrementally adjusting the strength values. Experimental results show that our method performs better than the random prioritization technique and the technique of prioritizing combinatorial test suites according to test case generation order, and has better performance than the interaction-coverage-based test prioritization technique in most cases.

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