NDLI: Efficient mutation analysis by propagating and partitioning infected execution states

Please wait, while we are loading the content...

Runtime prevention of concurrency related type-state violations in multithreaded applications

Hybrid security analysis of web JavaScript code via dynamic partial evaluation

Covrig: a framework for the analysis of code, test, and coverage evolution in real software

ARC++: effective typestate and lifetime dependency analysis

Using test case reduction and prioritization to improve symbolic execution

CrashLocator: locating crashing faults based on crash stacks

Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform

Reducing GUI test suites via program slicing

Efficient mutation analysis by propagating and partitioning infected execution states

Feedback-driven dynamic invariant discovery

Legend: an agile DSL toolset for web acceptance testing

Reusing constraint proofs for scalable program analysis

Performance regression testing of concurrent classes

Virtual DOM coverage for effective testing of dynamic web applications

CoREBench: studying complexity of regression errors

A type system for format strings

FLOWER: optimal test suite reduction as a network maximum flow

Efficient predicated bug signature mining via hierarchical instrumentation

Automated testing for SQL injection vulnerabilities: an input mutation approach

SunCat: helping developers understand and predict performance problems in smartphone applications

Lightweight automated detection of unsafe information leakage via exceptions

Link: exploiting the web of data to generate test inputs

ProCrawl: mining test models from multi-user web applications

Effective test generation and adequacy assessment for JavaScript-based web applications

Verifying atomicity via data independence

DOM-based test adequacy criteria for web applications

Scalable detection of missed cross-function refactorings

Coverage and fault detection of the output-uniqueness test selection criteria

Semantic differential repair for input validation and sanitization

A variability-based testing approach for synthesizing video sequences

Integrated energy-directed test suite optimization

Empirically revisiting the test independence assumption

X-PERT: a web application testing tool for cross-browser inconsistency detection

Efficient statistical debugging via hierarchical instrumentation

Verification-aided regression testing

Cross-platform feature matching for web applications

Tailored source code transformations to synthesize computationally diverse program variants

Dodona: automated oracle data set selection

Automatic repair for multi-threaded programs with Deadlock/Livelock using maximum satisfiability

Robust test automation using contextual clues

Identifying optimal trade-offs between CPU time usage and temporal constraints using search

An empirical study of injected versus actual interface errors

Extending a search-based test generator with adaptive dynamic symbolic execution

Canalyze: a static bug-finding tool for C programs

MuCheck: an extensible tool for mutation testing of haskell programs

The major mutation framework: efficient and scalable mutation analysis for Java

Defects4J: a database of existing faults to enable controlled testing studies for Java programs

A format string checker for Java

Constructing coding duels in Pex4Fun and code hunt

Efficient mutation analysis by propagating and partitioning infected execution states

Content Provider	ACM Digital Library
Author	Just, René Fraser, Gordon Ernst, Michael D.
Abstract	Mutation analysis evaluates a testing technique by measur- ing how well it detects seeded faults (mutants). Mutation analysis is hampered by inherent scalability problems — a test suite is executed for each of a large number of mutants. Despite numerous optimizations presented in the literature, this scalability issue remains, and this is one of the reasons why mutation analysis is hardly used in practice. Whereas most previous optimizations attempted to stati- cally reduce the number of executions or their computational overhead, this paper exploits information available only at run time to further reduce the number of executions. First, state infection conditions can reveal — with a single test execution of the unmutated program — which mutants would lead to a different state, thus avoiding unnecessary test executions. Second, determining whether an infected execution state propagates can further reduce the number of executions. Mutants that are embedded in compound expressions may infect the state locally without affecting the outcome of the compound expression. Third, those mutants that do infect the state can be partitioned based on the resulting infected state — if two mutants lead to the same infected state, only one needs to be executed as the result of the other can be inferred. We have implemented these optimizations in the Major mu- tation framework and empirically evaluated them on 14 open source programs. The optimizations reduced the mutation analysis time by 40% on average. .
Starting Page	315
Ending Page	326
Page Count	12
File Format	PDF
ISBN	9781450326452
DOI	10.1145/2610384.2610388
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-07-21
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Software testing Dynamic analysis Mutation analysis
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in