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检索条件"任意字段=5th International Symposium on Search-Based Software Engineering, SSBSE 2013"

共 88 条记录，以下是1-10 订阅

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15th international symposium on search-based software engineering, ssbse 2023

15th International Symposium on Search-Based Software Engine...

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15th international symposium on search-based software engineering, ssbse 2023

ISBN: (纸本)9783031487958

the proceedings contain 14 papers. the special focus in this conference is on search-based software engineering. the topics include: Multi-objective Black-Box Test Case Prioritization based on Wordnet Distances;a Novel Mutation Operator for search-based Test Case Selection;exploring Genetic Improvement of the Carbon Footprint of Web Pages;search-based Mock Generation of External Web Service Interactions;developer Views on software Carbon Footprint and Its Potential for Automated Reduction;searchGEM5: Towards Reliable Gem5 with search based software Testing and Large Language Models;enhancing Genetic Improvement Mutations Using Large Language Models;evaluating Explanations for software Patches Generated by Large Language Models;Improving the Readability of Generated Tests Using GPT-4 and ChatGPT Code Interpreter;preface;expound: A Black-Box Approach for Generating Diversity-Driven Adversarial Examples;generating Android Tests Using Novelty search.

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search-based Optimisation of LLM Learning Shots for Story Point Estimation 15th

Search-Based Optimisation of LLM Learning Shots for Story Po...

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15th international symposium on search-based software engineering (ssbse)

作者： Tawosi, Vali Alamir, Salwa Liu, Xiaomo JP Morgan AI Res London England JP Morgan AI Res New York NY USA

ISBN: (纸本)9783031487958;9783031487965

One of the ways Large Language Models (LLMs) are used to perform machine learning tasks is to provide them with a few examples before asking them to produce a prediction. this is a meta-learning process known as few-shot learning. In this paper, we use available search-based methods to optimise the number and combination of examples that can improve an LLM's estimation performance, when it is used to estimate story points for new agile tasks. Our preliminary results show that our SBSE technique improves the estimation performance of the LLM by 59.34% on average (in terms of mean absolute error of the estimation) over three datasets against a zero-shot setting.

关键词： search-based software Effort Estimation Large Language Model Few-shot Learning Multi-objective Optimisation

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searchGEM5: Towards Reliable Gem5 with search based software Testing and Large Language Models 15th

SearchGEM5: Towards Reliable Gem5 with Search Based Software...

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15th international symposium on search-based software engineering (ssbse)

作者： Dakhama, Aidan Even-Mendoza, Karine Langdon, W. B. Menendez, Hector Petke, Justyna Kings Coll London London England UCL London England

ISBN: (纸本)9783031487958;9783031487965

We introduce a novel automated testing technique that combines LLM and search-based fuzzing. We use ChatGPT to parameterise C programs. We compile the resultant code snippets, and feed compilable ones to searchGEM5, our extension to AFL++ fuzzer with customised new mutation operators. We run thus created 4005 binaries through our system under test, gem5, increasing its existing test coverage by more than 1000 lines. We discover 244 instances where gem5 simulation of the binary differs from the binary's expected behaviour.

关键词： AI LLM SBSE SBFT genetic improvement of tests

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Developer Views on software Carbon Footprint and Its Potential for Automated Reduction 15th

Developer Views on Software Carbon Footprint and Its Potenti...

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15th international symposium on search-based software engineering (ssbse)

作者： Lyu, Haozhou Gay, Gregory Sakamoto, Maiko Chalmers Gothenburg Sweden Univ Gothenburg Gothenburg Sweden Univ Tokyo Tokyo Japan

ISBN: (纸本)9783031487958;9783031487965

Reducing software carbon footprint could contribute to efforts to avert climate change. Past research indicates that developers lack knowledge on energy consumption and carbon footprint, and existing reduction guidelines are difficult to apply. therefore, we propose that automated reduction methods should be explored, e.g., through genetic improvement. However, such tools must be voluntarily adopted and regularly used to have an impact. In this study, we have conducted interviews and a survey (a) to explore developers' existing opinions, knowledge, and practices with regard to carbon footprint and energy consumption, and (b), to identify the requirements that automated reduction tools must meet to ensure adoption. Our findings offer a foundation for future research on practices, guidelines, and automated tools that address software carbon footprint.

关键词： Carbon Footprint Energy Consumption Sustainability Genetic Improvement Genetic Programming

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Multi-objective Black-Box Test Case Prioritization based on Wordnet Distances 15th

Multi-objective Black-Box Test Case Prioritization Based on ...

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15th international symposium on search-based software engineering (ssbse)

作者： van Dinten, Imara Zaidman, Andy Panichella, Annibale Delft Univ Technol Delft Netherlands

ISBN: (纸本)9783031487958;9783031487965

Test case prioritization techniques have emerged as effective strategies to optimize this process and mitigate the regression testing costs. Commonly, black-box heuristics guide optimal test ordering, leveraging information retrieval (e.g., cosine distance) to measure the test case distance and sort them accordingly. However, a challenge arises when dealing with tests of varying granularity levels, as they may employ distinct vocabularies (e.g., name identifiers). In this paper, we propose to measure the distance between test cases based on the shortest path between their identifiers within the WordNet lexical database. this additional heuristic is combined with the traditional cosine distance to prioritize test cases in a multi-objective fashion. Our preliminary study conducted with two different Java projects shows that test cases prioritized with WordNet achieve larger fault detection capability (APFDC) compared to the traditional cosine distance used in the literature.

关键词： Empirical software engineering search-based software testing Test case prioritization Wordnet Natural language processing

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Evaluating Explanations for software Patches Generated by Large Language Models 15th

Evaluating Explanations for Software Patches Generated by La...

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15th international symposium on search-based software engineering (ssbse)

作者： Sobania, Dominik Geiger, Alina Callan, James Brownlee, Alexander Hanna, Carol Moussa, Rebecca Lopez, Mar Zamorano Petke, Justyna Sarro, Federica Johannes Gutenberg Univ Mainz Mainz Germany UCL London England Univ Stirling Stirling Scotland

ISBN: (纸本)9783031487958;9783031487965

Large language models (LLMs) have recently been integrated in a variety of applications including software engineering tasks. In this work, we study the use of LLMs to enhance the explainability of software patches. In particular, we evaluate the performance of GPT 3.5 in explaining patches generated by the search-based automated program repair system ARJA-e for 30 bugs from the popular Defects4J benchmark. We also investigate the performance achieved when explaining the corresponding patches written by software developers. We find that on average 84% of the LLM explanations for machine-generated patches were correct and 54% were complete for the studied categories in at least 1 out of 3 runs. Furthermore, we find that the LLM generates more accurate explanations for machine-generated patches than for human-written ones.

关键词： Large Language Models software Patches AI Explainability Program Repair Genetic Improvement

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search-based Mock Generation of External Web Service Interactions 15th

Search-Based Mock Generation of External Web Service Interac...

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15th international symposium on search-based software engineering (ssbse)

作者： Seran, Susruthan Zhang, Man Arcuri, Andrea Kristiania Univ Coll Oslo Norway Oslo Metropolitan Univ Oslo Norway

ISBN: (纸本)9783031487958;9783031487965

Testing large and complex enterprise software systems can be a challenging task. this is especially the case when the functionality of the system depends on interactions with other external services over a network (e.g., external REST APIs). Although several techniques in the research literature have been shown to be effective at generating test cases in many different software testing contexts, dealing with external services is still a major research challenge. In industry, a common approach is to mock external web services for testing purposes. However, generating and configuring mock web services can be a very time-consuming task. Furthermore, external services may not be under the control of the same developers of the tested application. In this paper, we present a novel search-based approach aimed at fully automated mocking external web services as part of white-box, search-based fuzzing. We rely on code instrumentation to detect all interactions with external services, and how their response data is parsed. We then use such information to enhance a search-based approach for fuzzing. the tested application is automatically modified (by manipulating DNS lookups) to rather interact with instances of mock web servers. the search process not only generates inputs to the tested applications, but also it automatically setups responses in those mock web server instances, aiming at maximizing code coverage and fault-finding. An empirical study on 3 open-source REST APIs from EMB, and one industrial API from an industry partner, shows the effectiveness of our novel techniques, i.e., significantly improves code coverage and fault detection.

关键词： Microservices Automated Mock Generation search-based Test Generation search-based software engineering

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Guess What: Test Case Generation for Javascript with Unsupervised Probabilistic Type Inference 14th

Guess What: Test Case Generation for Javascript with Unsuper...

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14th international symposium on search-based software engineering (ssbse)

作者： Stallenberg, Dimitri Olsthoorn, Mitchell Panichella, Annibale Delft Univ Technol Delft Netherlands

ISBN: (纸本)9783031212505;9783031212512

search-based test case generation approaches make use of static type information to determine which data types should be used for the creation of new test cases. Dynamically typed languages like JavaScript, however, do not have this type information. In this paper, we propose an unsupervised probabilistic type inference approach to infer data types within the test case generation process. We evaluated the proposed approach on a benchmark of 98 units under test (i.e., exported classes and functions) compared to random type sampling w. r. t. branch coverage. Our results show that our type inference approach achieves a statistically significant increase in 56% of the test files with up to 71% of branch coverage compared to the baseline.

关键词： Empirical software engineering search-based software testing Test case generation Javascript Type inference

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Does Diversity Improve the Test Suite Generation for Mobile Applications? 11th

Does Diversity Improve the Test Suite Generation for Mobile ...

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11th international symposium on search-based software engineering (ssbse)

作者： Vogel, thomas Tran, Chinh Grunske, Lars Humboldt Univ Software Engn Grp Berlin Germany

ISBN: (纸本)9783030274559;9783030274542

In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. To obtain better results while avoiding trial-and-error experiments, a fitness landscape analysis is helpful in understanding the search problem, and making an informed decision about the heuristics. In this paper, we investigate the search problem of test suite generation for mobile applications (apps) using SAPIENZ whose heuristic is a default NSGA-II. We analyze the fitness landscape of SAPIENZ with respect to genotypic diversity and use the gained insights to adapt the heuristic of SAPIENZ. these adaptations result in SAPIENZ(div) that aims for preserving the diversity of test suites during the search. To evaluate SAPIENZ(div), we perform a head-to-head comparison with SAPIENZ on 76 open-source apps.

关键词： Fitness landscape analysis Diversity Test generation

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A Prediction of Grain Yield based on Hybrid Intelligent Algorithm 5

A Prediction of Grain Yield Based on Hybrid Intelligent Algo...

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5th international Scientific Conference of Al-Khwarizmi Society, FISCAS 2020

作者： Saleh, Ibrahim Ahmed Alawsi, Wasan Abdallah Alsaif, Omar Ibrahim Alsaif, Khalil University of Mosul Software Engineering Dept. Iraq University of Al- Qadisiyah College Science Iraq Northern Technical University Mosul Technical Institute Iraq University of Mosul Computer Science Dept. Iraq

the prediction is most important goals in economic quantitative studies, it basis in design and plan future economic policies properly process over forecasting accuracy. this paper is aiming at the problem salp swarm algorithm (SSA) for predicting grain yield is prone to fall into the local optimal problem. An improved SSA is proposed with combine with back propagation neural network. Using the different advantages of SSA algorithm in global search capabilities, combining the two for further optimize the weight, improve the accuracy and robustness of the grain yield prediction model. the specific implementation is selected from 1963 to 2013. these methods are used to define agricultural datasets that supports crop growth decision for grain product and its influencing factors were tested as a data set. the results show that, the improved salp swarm optimization can be classified as a good predict tool for the domestic food production trend in recent years compared with the SSA. this paper briefly introduces three artificial methods BP neural networks, SSA and improved SSA optimization algorithm. the natural behavior of salp, barrel-shaped plankton that are mostly water by weight optimization and combined with mixed-group of intelligent algorithm are simulated. the simulation results of grain production prediction illustrate that the predict precision of the improved SSA is much higher than of both conventional BPNN and SSA techniques and it's very efficient and practicable. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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