A systematic literature review of techniques and metrics to reduce the cost of mutation testing

AV Pizzoleto, FC Ferrari, J Offutt, L Fernandes… - Journal of Systems and …, 2019 - Elsevier
Historically, researchers have proposed and applied many techniques to reduce the cost of
mutation testing. It has become difficult to find all techniques and to understand the cost …

Reviewing software testing models and optimization techniques: an analysis of efficiency and advancement needs

S Kumar - Journal of Computers, Mechanical and Management, 2023 - jcmm.co.in
Software testing is a crucial component of software engineering that aims to confirm the
intended functionality of software modules and minimize the likelihood of future failures. This …

Large language models for software engineering: Survey and open problems

A Fan, B Gokkaya, M Harman… - 2023 IEEE/ACM …, 2023 - ieeexplore.ieee.org
This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …

Unsupervised translation of programming languages

B Roziere, MA Lachaux… - Advances in neural …, 2020 - proceedings.neurips.cc
A transcompiler, also known as source-to-source translator, is a system that converts source
code from a high-level programming language (such as C++ or Python) to another …

Agentless: Demystifying llm-based software engineering agents

CS **a, Y Deng, S Dunn, L Zhang - arxiv preprint arxiv:2407.01489, 2024 - arxiv.org
Recent advancements in large language models (LLMs) have significantly advanced the
automation of software development tasks, including code synthesis, program repair, and …

Echidna: effective, usable, and fast fuzzing for smart contracts

G Grieco, W Song, A Cygan, J Feist… - Proceedings of the 29th …, 2020 - dl.acm.org
Ethereum smart contracts---autonomous programs that run on a blockchain---often control
transactions of financial and intellectual property. Because of the critical role they play, smart …

Deep learning library testing via effective model generation

Z Wang, M Yan, J Chen, S Liu, D Zhang - … of the 28th ACM Joint Meeting …, 2020 - dl.acm.org
Deep learning (DL) techniques are rapidly developed and have been widely adopted in
practice. However, similar to traditional software systems, DL systems also contain bugs …

Effective test generation using pre-trained large language models and mutation testing

AM Dakhel, A Nikanjam, V Majdinasab… - Information and …, 2024 - Elsevier
Context: One of the critical phases in the software development life cycle is software testing.
Testing helps with identifying potential bugs and reducing maintenance costs. The goal of …

Predictive mutation testing

J Zhang, Z Wang, L Zhang, D Hao, L Zang… - Proceedings of the 25th …, 2016 - dl.acm.org
Mutation testing is a powerful methodology for evaluating test suite quality. In mutation
testing, a large number of mutants are generated and executed against the test suite to …

Code generation tools (almost) for free? a study of few-shot, pre-trained language models on code

P Bareiß, B Souza, M d'Amorim, M Pradel - arxiv preprint arxiv …, 2022 - arxiv.org
Few-shot learning with large-scale, pre-trained language models is a powerful way to
answer questions about code, eg, how to complete a given code example, or even generate …