scholarly journals First international competition on software testing

2021 ◽  
Author(s):  
Dirk Beyer
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Comparative Evaluation ◽  
State Of The Art ◽  
International Competition ◽  
Software Test ◽  
Test Specifications ◽  
Research Areas ◽  
Function Call ◽  
Generation Test

AbstractTool competitions are a special form of comparative evaluation, where each tool has a team of developers or supporters associated that makes sure the tool is properly configured to show its best possible performance. In several research areas, tool competitions have been a driving force for the development of mature tools that represent the state of the art in their field. This paper describes and reports the results of the 1$$^{\text {st}}$$ st International Competition on Software Testing (Test-Comp 2019), a comparative evaluation of automatic tools for software test generation. Test-Comp 2019 was presented as part of TOOLympics 2019, a satellite event of the conference TACAS. Nine test generators were evaluated on 2 356 test-generation tasks. There were two test specifications, one for generating a test that covers a particular function call and one for generating a test suite that tries to cover the branches of the program.

scholarly journals Status Report on Software Testing: Test-Comp 2021

2021 ◽  
pp. 341-357 ◽  
Author(s):  
Dirk Beyer
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Software Test ◽  
Status Report ◽  
Generation Task ◽  
C Programs ◽  
Branch Coverage ◽  
Current State ◽  
Strong Focus ◽  
Automatic Software

AbstractThis report describes Test-Comp 2021, the 3rd edition of the Competition on Software Testing. The competition is a series of annual comparative evaluations of fully automatic software test generators for C programs. The competition has a strong focus on reproducibility of its results and its main goal is to provide an overview of the current state of the art in the area of automatic test-generation. The competition was based on 3 173 test-generation tasks for C programs. Each test-generation task consisted of a program and a test specification (error coverage, branch coverage). Test-Comp 2021 had 11 participating test generators from 6 countries.

scholarly journals Software Testing or The Bugs’ Nightmare

2021 ◽  
pp. 1-21
Author(s):  
Hector David Menendez
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
State Of The Art ◽  
Symbolic Execution ◽  
Significant Progress ◽  
Automatic Test Generation ◽  
Significant Development ◽  
Testing Strategies ◽  
Future Challenges ◽  
Single Part

Software development is not error-free. For decades, bugs –including physical ones– have become a significant development problem requiring major maintenance efforts. Even in some cases, solving bugs led to increment them. One of the main reasons for bug’s prominence is their ability to hide. Finding them is difficult and costly in terms of time and resources. However, software testing made significant progress identifying them by using different strategies that combine knowledge from every single part of the program. This paper humbly reviews some different approaches from software testing that discover bugs automatically and presents some different state-of-the-art methods and tools currently used in this area. It covers three testing strategies: search-based methods, symbolic execution, and fuzzers. It also provides some income about the application of diversity in these areas, and common and future challenges on automatic test generation that still need to be addressed.

Research Notes: Binary Test-Suites Using Covering Arrays

2018 ◽  
Vol 28 (09) ◽  
pp. 1321-1337 ◽  
Author(s):  
Jose Torres-Jimenez ◽  
Himer Avila-George ◽  
Ezra Federico Parra-González
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Software Systems ◽  
Combinatorial Testing ◽  
Covering Array ◽  
Covering Arrays ◽  
Almost All ◽  
Generation Problem ◽  
Test Suites

Software testing is an essential activity to ensure the quality of software systems. Combinatorial testing is a method that facilitates the software testing process; it is based on an empirical evidence where almost all faults in a software component are due to the interaction of very few parameters. The test generation problem for combinatorial testing can be represented as the construction of a matrix that has certain properties; typically this matrix is a covering array. Covering arrays have a small number of tests, in comparison with an exhaustive approach, and provide a level of interaction coverage among the parameters involved. This paper presents a repository that contains binary covering arrays involving many levels of interaction. Also, it discusses the importance of covering array repositories in the construction of better covering arrays. In most of the cases, the size of the covering arrays included in the repository reported here are the best upper bounds known, moreover, the files containing the matrices of these covering arrays are available to be downloaded. The final purpose of our Binary Covering Arrays Repository (BCAR) is to provide software testing practitioners the best-known binary test-suites.

scholarly journals DiagnosisQA: A semi-automated pipeline for developing clinician validated diagnosis specific QA datasets.

2021 ◽  
Author(s):  
Shreya Mishra ◽  
Raghav Awasthi ◽  
Frank Papay ◽  
Kamal Maheshawari ◽  
Jacek B Cywinski ◽  
...  
Keyword(s):  
Question Answering ◽  
State Of The Art ◽  
Healthcare Providers ◽  
Unstructured Data ◽  
Significant Progress ◽  
Improve Performance ◽  
Healthcare Data ◽  
Research Areas ◽  
Benchmark Datasets ◽  
Automated Pipeline

Question answering (QA) is one of the oldest research areas of AI and Compu- national Linguistics. QA has seen significant progress with the development of state-of-the-art models and benchmark datasets over the last few years. However, pre-trained QA models perform poorly for clinical QA tasks, presumably due to the complexity of electronic healthcare data. With the digitization of healthcare data and the increasing volume of unstructured data, it is extremely important for healthcare providers to have a mechanism to query the data to find appropriate answers. Since diagnosis is central to any decision-making for the clinicians and patients, we have created a pipeline to develop diagnosis-specific QA datasets and curated a QA database for the Cerebrovascular Accident (CVA). CVA, also commonly known as Stroke, is an important and commonly occurring diagnosis amongst critically ill patients. Our method when compared to clinician validation achieved an accuracy of 0.90(with 90% CI [0.82,0.99]). Using our method, we hope to overcome the key challenges of building and validating a highly accurate QA dataset in a semiautomated manner which can help improve performance of QA models.

Concolic Test Generation and the Cloud

2015 ◽  
pp. 302-322
Author(s):  
Nikolai Kosmatov
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Symbolic Execution ◽  
Major Obstacle ◽  
Testing Methods ◽  
C Programs ◽  
Security Issues ◽  
Efficient Alternative ◽  
Cloud Environments ◽  
Testing Techniques

Software testing in the cloud can reduce the need for hardware and software resources and offer a flexible and efficient alternative to the traditional software testing process. A major obstacle to the wider use of testing in the cloud is related to security issues. This chapter focuses on test generation techniques that combine concrete and symbolic execution of the program under test. Their deployment in the cloud leads to complex technical and security issues that do not occur for other testing methods. This chapter describes recent online deployment of such a technique implemented by the PathCrawler test generation tool for C programs, where the author faced, studied, and solved many of these issues. Mixed concrete/symbolic testing techniques not only constitute a challenging target for deployment in the cloud, but they also provide a promising way to improve the reliability of cloud environments. The author argues that these techniques can be efficiently used to help to create trustworthy cloud environments.

A Scientometric Analysis of Studies in Turkey

2019 ◽  
Vol 8 (1) ◽  
pp. 28-41
Author(s):  
Ecem Tezel ◽  
Heyecan Giritli
Keyword(s):  
Construction Projects ◽  
State Of The Art ◽  
Developed Countries ◽  
Information Modeling ◽  
Scientometric Analysis ◽  
Facilities Management ◽  
Research Gaps ◽  
Research Areas ◽  
Building Information ◽  
Bibliometric Review

Recently, architecture engineering and construction (AEC) industry benefits from building information modeling (BIM) as a technology-based development, to enhance collaboration and increase the efficiency of construction projects. After implementing BIM in design and construction phases, developed countries now head towards utilization of BIM in facilities management (FM) processes. As ranking among the leading AEC industries, Turkey not only follows latest developments but also promises valuable potentials for both theoretical and practical improvement of BIM. Based on the studies published in BIM field, this study applies bibliometric review approach to analyze the state-of-the-art situation of the field in Turkey, and determine potential research areas, especially in BIM and FM intersection. Following the systematic literature search that aims to introduce current efforts of Turkish researchers in BIM field, the qualitative analysis categorizes these efforts according to life cycle phases of a construction project and provides a vision on existing knowledge as well as research gaps. Findings of this study point out the important contributions of Turkey to BIM field especially in design and/or construction phases. A prominent conclusion of this study also signals a need for more FM oriented approach in BIM researches.

scholarly journals A visual SLAM method based on point-line fusion in weak-matching scene

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142090419 ◽  
Author(s):  
Baofu Fang ◽  
Zhiqiang Zhan
Keyword(s):  
State Of The Art ◽  
Localization Accuracy ◽  
Line Segments ◽  
Research Areas ◽  
Current State ◽  
Localization And Mapping ◽  
Reprojection Error ◽  
Feature Based ◽  
Point Line ◽  
Point Feature

Visual simultaneous localization and mapping (SLAM) is well-known to be one of the research areas in robotics. There are many challenges in traditional point feature-based approaches, such as insufficient point features, motion jitter, and low localization accuracy in low-texture scenes, which reduce the performance of the algorithms. In this article, we propose an RGB-D SLAM system to handle these situations, which is named Point-Line Fusion (PLF)-SLAM. We utilize both points and line segments throughout the process of our work. Specifically, we present a new line segment extraction method to solve the overlap or branch problem of the line segments, and then a more rigorous screening mechanism is proposed in the line matching section. Instead of minimizing the reprojection error of points, we introduce the reprojection error based on points and lines to get a more accurate tracking pose. In addition, we come up with a solution to handle the jitter frame, which greatly improves tracking success rate and availability of the system. We thoroughly evaluate our system on the Technische Universität München (TUM) RGB-D benchmark and compare it with ORB-SLAM2, presumably the current state-of-the-art solution. The experiments show that our system has better accuracy and robustness compared to the ORB-SLAM2.

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