{"title":"BEAPI: A tool for bounded exhaustive input generation from APIs","authors":"Mariano Politano , Valeria Bengolea , Facundo Molina , Nazareno Aguirre , Marcelo Frias , Pablo Ponzio","doi":"10.1016/j.scico.2024.103153","DOIUrl":null,"url":null,"abstract":"<div><p>Bounded exhaustive testing is a very effective technique for bug finding, which proposes to test a given program under all valid bounded inputs, for a bound provided by the developer. Existing bounded exhaustive testing techniques require the developer to provide a precise specification of the valid inputs. Such specifications are rarely present as part of the software under test, and writing them can be costly and challenging.</p><p>To address this situation we propose BEAPI, a tool that given a Java class under test, generates a bounded exhaustive set of objects of the class solely employing the methods of the class, without the need for a specification. BEAPI creates sequences of calls to methods from the class' public API, and executes them to generate inputs. BEAPI implements very effective pruning techniques that allow it to generate inputs efficiently.</p><p>We experimentally assessed BEAPI in several case studies from the literature, and showed that it performs comparably to the best existing specification-based bounded exhaustive generation tool (Korat), without requiring a specification of the valid inputs.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"238 ","pages":"Article 103153"},"PeriodicalIF":1.5000,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Computer Programming","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167642324000765","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Bounded exhaustive testing is a very effective technique for bug finding, which proposes to test a given program under all valid bounded inputs, for a bound provided by the developer. Existing bounded exhaustive testing techniques require the developer to provide a precise specification of the valid inputs. Such specifications are rarely present as part of the software under test, and writing them can be costly and challenging.
To address this situation we propose BEAPI, a tool that given a Java class under test, generates a bounded exhaustive set of objects of the class solely employing the methods of the class, without the need for a specification. BEAPI creates sequences of calls to methods from the class' public API, and executes them to generate inputs. BEAPI implements very effective pruning techniques that allow it to generate inputs efficiently.
We experimentally assessed BEAPI in several case studies from the literature, and showed that it performs comparably to the best existing specification-based bounded exhaustive generation tool (Korat), without requiring a specification of the valid inputs.
期刊介绍:
Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design.
The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice.
The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including
• Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software;
• Design, implementation and evaluation of programming languages;
• Programming environments, development tools, visualisation and animation;
• Management of the development process;
• Human factors in software, software for social interaction, software for social computing;
• Cyber physical systems, and software for the interaction between the physical and the machine;
• Software aspects of infrastructure services, system administration, and network management.