Papers test driven development
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CoreCodeBench: A Configurable Multi-Scenario Repository-Level Benchmark
As Large Language Models (LLMs) demonstrate increasingly sophisticated code processing capabilities, evaluating their performance on engineering-level code remains challenging. Existing repository-level benchmarks primar…
Bug fixingCode Generationtest driven developmentUse Property-Based Testing to Bridge LLM Code Generation and Validation
Large Language Models (LLMs) excel at code generation, but ensuring their outputs to be functionally correct, especially in complex programming tasks, is a persistent challenge. While traditional Test-Driven Development …
Code Generationtest driven developmentSWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner
We introduce **SWE-Flow**, a novel data synthesis framework grounded in Test-Driven Development (TDD). Unlike existing software engineering data that rely on human-submitted issues, **SWE-Flow** automatically infers incr…
test driven developmentGenerating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems
Developing safety-critical automotive software presents significant challenges due to increasing system complexity and strict regulatory demands. This paper proposes a novel framework integrating Generative Artificial In…
BenchmarkingCode GenerationModel Selectiontest driven developmentTests as Prompt: A Test-Driven-Development Benchmark for LLM Code Generation
We introduce WebApp1K, a novel benchmark for evaluating large language models (LLMs) in test-driven development (TDD) tasks, where test cases serve as both prompt and verification for code generation. Unlike traditional …
Code GenerationIn-Context LearningInstruction Followingtest driven developmentOtter: Generating Tests from Issues to Validate SWE Patches
While there has been plenty of work on generating tests from existing code, there has been limited work on generating tests from issues. A correct test must validate the code patch that resolves the issue. This paper foc…
test driven developmentFrom Defects to Demands: A Unified, Iterative, and Heuristically Guided LLM-Based Framework for Automated Software Repair and Requirement Realization
This manuscript signals a new era in the integration of artificial intelligence with software engineering, placing machines at the pinnacle of coding capability. We present a formalized, iterative methodology proving tha…
Ingenuitytest driven developmentTDD-Bench Verified: Can LLMs Generate Tests for Issues Before They Get Resolved?
Test-driven development (TDD) is the practice of writing tests first and coding later, and the proponents of TDD expound its numerous benefits. For instance, given an issue on a source code repository, tests can clarify …
test driven developmentOpen Source Evolutionary Computation with Chips-n-Salsa
When it was first introduced, the Chips-n-Salsa Java library provided stochastic local search and related algorithms, with a focus on self-adaptation and parallel execution. For the past four years, we expanded its scope…
Evolutionary Algorithmstest driven developmentEvaluation-Driven Development of LLM Agents: A Process Model and Reference Architecture
Large Language Models (LLMs) have enabled the emergence of LLM agents: autonomous systems capable of achieving under-specified goals and adapting post-deployment, often without explicit code or model changes. Evaluating …
test driven developmentA Comparative Study on the Impact of Test-Driven Development (TDD) and Behavior-Driven Development (BDD) on Enterprise Software Delivery Effectiveness
This paper compares the impact of Test-Driven Development (TDD) and Behavior-Driven Development (BDD) on software delivery effectiveness within enterprise environments. Using a qualitative research design, data were coll…
test driven developmentComprehensive Evaluation and Insights into the Use of Large Language Models in the Automation of Behavior-Driven Development Acceptance Test Formulation
Behavior-driven development (BDD) is an Agile testing methodology fostering collaboration among developers, QA analysts, and stakeholders. In this manuscript, we propose a novel approach to enhance BDD practices using la…
Few-Shot LearningIn-Context LearningLarge Language ModelPrompt Engineering+4Test-Driven Development for Code Generation
Recent Large Language Models (LLMs) have demonstrated significant capabilities in generating code snippets directly from problem statements. This increasingly automated process mirrors traditional human-led software deve…
Code GenerationHumanEvalmbpptest driven developmentUnit Testing in ASP Revisited: Language and Test-Driven Development Environment
Unit testing frameworks are nowadays considered a best practice, included in almost all modern software development processes, to achieve rapid development of correct specifications. Knowledge representation and reasonin…
test driven developmentSafety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment
The size of deep learning models in artificial intelligence (AI) software is increasing rapidly, hindering the large-scale deployment on resource-restricted devices (e.g., smartphones). To mitigate this issue, AI softwar…
Inference AttackMembership Inference AttackModel Compressiontest driven developmentLLM4TDD: Best Practices for Test Driven Development Using Large Language Models
In today's society, we are becoming increasingly dependent on software systems. However, we also constantly witness the negative impacts of buggy software. Program synthesis aims to improve software correctness by automa…
Program Synthesistest driven developmentTesting LLMs on Code Generation with Varying Levels of Prompt Specificity
Large language models (LLMs) have demonstrated unparalleled prowess in mimicking human-like text generation and processing. Among the myriad of applications that benefit from LLMs, automated code generation is increasing…
Code GenerationSpecificitytest driven developmentText GenerationSafety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software Deployment
The size of deep learning models in artificial intelligence (AI) software is increasing rapidly, which hinders the large-scale deployment on resource-restricted devices (e.g., smartphones). To mitigate this issue, AI sof…
Inference AttackMembership Inference AttackModel Compressiontest driven developmentTimeGym: Debugging for Time Series Modeling in Python
We introduce the TimeGym Forecasting Debugging Toolkit, a Python library for testing and debugging time series forecasting pipelines. TimeGym simplifies the testing forecasting pipeline by providing generic tests for for…
test driven developmentTime SeriesTime Series AnalysisTime Series ForecastingUnit Test Case Generation with Transformers and Focal Context
Automated unit test case generation tools facilitate test-driven development and support developers by suggesting tests intended to identify flaws in their code. Existing approaches are usually guided by the test coverag…
Denoisingtest driven development