Relevant bibliographies by topics / APFD metric

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'APFD metric'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "APFD metric"

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Mor, Mr Anil. "Evaluate the Effectiveness of Test Suite Prioritization Techniques Using APFD Metric." IOSR Journal of Computer Engineering 16, no. 4 (2014): 47–51. http://dx.doi.org/10.9790/0661-16414751.

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Gupta, Rahul, and Akhilesh Kumar Yadav. "STUDY OF TEST CASE PRIORITIZATION TECHNIQUE USING APFD." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 3 (2013): 1475–81. http://dx.doi.org/10.24297/ijct.v10i3.3277.

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Regression testing is used to ensure that bugs are fixed and new functionality introduce in a new version of a software that don't adversely affect the original functionality inherited from the previous version.Regression testing is one of the most complaining activities of software development and maintenance.Unluckily, It may have feeble resources to allow for the re-execution of all test cases during regression testing. In this situation the use of test case prioritization is profitable because the best appropriate test cases are executed first. In this paper we are proposing an algorithm t
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Wambua, Anthony Wambua, and Geoffrey Mariga Wambugu. "A Comparative Analysis of Bat and Genetic Algorithms for Test Case Prioritization in Regression Testing." International Journal of Intelligent Systems and Applications 15, no. 1 (2023): 13–21. http://dx.doi.org/10.5815/ijisa.2023.01.02.

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Regression testing is carried out to ensure that software modifications do not introduce new potential bugs to the existing software. Existing test cases are applied in the testing, such test cases can run into thousands, and there is not much time to execute all of them. Test Case Prioritization (TCP) is a technique to order test cases so that the test cases potentially revealing more faults are performed first. With TCP being deemed an optimization problem, several metaheuristic nature-inspired algorithms such as Bat, Genetic, Ant colony, and Firefly algorithms have been proposed for TCP. Th
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Alsukhni, Emad, Ahmad A. Saifan, and Hanadi Alawneh. "A New Data Mining-Based Framework to Test Case Prioritization Using Software Defect Prediction." International Journal of Open Source Software and Processes 8, no. 1 (2017): 21–41. http://dx.doi.org/10.4018/ijossp.2017010102.

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Test cases do not have the same importance when used to detect faults in software; therefore, it is more efficient to test the system with the test cases that have the ability to detect the faults. This research proposes a new framework that combines data mining techniques to prioritize the test cases. It enhances fault prediction and detection using two different techniques: 1) the data mining regression classifier that depends on software metrics to predict defective modules, and 2) the k-means clustering technique that is used to select and prioritize test cases to identify the fault early.
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Hema Shankari, K., and R. Thirumalai Selvi. "Methodology for regression testing with open source tool." International Journal of Engineering & Technology 7, no. 1.1 (2017): 133. http://dx.doi.org/10.14419/ijet.v7i1.1.9212.

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The paper describes our methodology for optimizing regression testing that forms a major part of software maintenance. It necessitates the use of an automated testing tool, and we have selected Selenium, an open source tool. For simple projects, a formula is proposed that has been derived through data mining with Selenium. A genetic algorithm is added to this methodology for industry based projects, where the test cases are so large that they have to be grouped as Test Suites; this algorithm reconfigures Test suites in each cycle of regression testing. Commonly used APFD metric ignores fault s
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Maspupah, Asri, Mumuh Kustino Muharram, and Sophia Gianina Daeli. "Analisis Efektifitas Algoritma FAST Menggunakan Metrik Average Percentage Fault Detection dan Waktu Eksekusi Pada Test Case Prioritization." Journal of Information System Research (JOSH) 4, no. 2 (2023): 451–57. http://dx.doi.org/10.47065/josh.v4i2.2822.

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It uses regression testing to validate the modification results so as not to cause new errors in features that are already functioning correctly. The implementation of regression testing is generally done by re-executing the test suite used in the previous test. One of the crucial issues in regression testing is determining a strategic approach to reuse existing test suites. Testing with retesting all test cases will result in a long and expensive test. Thus, it is necessary to use a test case selection approach. The research study focuses on analyzing the effectiveness of the FAST algorithm,
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Wang, Ziyuan, Chunrong Fang, Lin Chen, and Zhiyi Zhang. "A Revisit of Metrics for Test Case Prioritization Problems." International Journal of Software Engineering and Knowledge Engineering 30, no. 08 (2020): 1139–67. http://dx.doi.org/10.1142/s0218194020500291.

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For the test case prioritization problems, the average percent of faults detected (APFD) and its variant versions are widely used as metrics to evaluate prioritized test suite’s efficiency of fault detection. By a revisit of metrics for test case prioritization, we observe that APFD is only available for the scenarios where all test suites under evaluation contain the same number of test cases. Such a limitation is often overlooked, and lead to incorrect results when comparing fault detection efficiency of test suites with different sizes. Moreover, APFD cannot precisely illustrate the process
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Mizukami, Naoki, Oldrich Rakovec, Andrew J. Newman, et al. "On the choice of calibration metrics for “high-flow” estimation using hydrologic models." Hydrology and Earth System Sciences 23, no. 6 (2019): 2601–14. http://dx.doi.org/10.5194/hess-23-2601-2019.

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Abstract. Calibration is an essential step for improving the accuracy of simulations generated using hydrologic models. A key modeling decision is selecting the performance metric to be optimized. It has been common to use squared error performance metrics, or normalized variants such as Nash–Sutcliffe efficiency (NSE), based on the idea that their squared-error nature will emphasize the estimates of high flows. However, we conclude that NSE-based model calibrations actually result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimat
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Shen, Linshan, Xiang Feng, Li Xu, and Weiyue Ding. "Adaptive prototype few-shot image classification method based on feature pyramid." PeerJ Computer Science 10 (October 1, 2024): e2322. http://dx.doi.org/10.7717/peerj-cs.2322.

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Few-shot learning aims to enable machines to recognize unseen novel classes using limited samples akin to human capabilities. Metric learning is a crucial approach to addressing this challenge, with its performance primarily dependent on the effectiveness of feature extraction and prototype computation. This article introduces an Adaptive Prototype few-shot image classification method based on Feature Pyramid (APFP). APFP employs a novel feature extraction method called FResNet, which builds upon the ResNet architecture and leverages a feature pyramid structure to retain finer details. In the
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Zhang, Long, Ziping Zhao, Chunmei Ma, et al. "End-to-End Automatic Pronunciation Error Detection Based on Improved Hybrid CTC/Attention Architecture." Sensors 20, no. 7 (2020): 1809. http://dx.doi.org/10.3390/s20071809.

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Advanced automatic pronunciation error detection (APED) algorithms are usually based on state-of-the-art automatic speech recognition (ASR) techniques. With the development of deep learning technology, end-to-end ASR technology has gradually matured and achieved positive practical results, which provides us with a new opportunity to update the APED algorithm. We first constructed an end-to-end ASR system based on the hybrid connectionist temporal classification and attention (CTC/attention) architecture. An adaptive parameter was used to enhance the complementarity of the connectionist tempora
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Dissertations / Theses on the topic "APFD metric"

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Ramírez, Abarca Daniel. "Herramienta de gestión cuantitativa de proyectos de software orientada por un proceso de desarrollo." Tesis, Universidad de Chile, 2014. http://www.repositorio.uchile.cl/handle/2250/130391.

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Magíster en Tecnologías de la Información<br>Esta tesis tiene como objetivo definir y diseñar una herramienta de administración de proyectos de software orientada por un proceso de desarrollo, que permita obtener en forma oportuna un conjunto de métricas que apunten a mejorar la calidad del proceso y productos de la organización. Este proyecto está contextualizado en la experiencia de Amisoft Ingeniería Ltda., la cual ha implementado un proceso denominado Amisoft Process Framework (APF), que enmarca las actividades de gestión, ingeniería y soporte, necesarias para guiar cada proyecto en su
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Junior, Marcos de Freitas. "Melhoria na consistência da contagem de pontos de função com base na Árvore de pontos de função." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-02022016-012253/.

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Análise de Pontos de Função (APF) é uma das medidas usadas para obter o tamanho funcional de um software. Determinou-se, no Brasil, que toda contratação pública de desenvolvimento de software deve usar APF. Entretanto, uma das principais críticas realizadas a APF diz respeito à falta de confiabilidade entre diferentes contadores em uma mesma contagem já que, segundo alguns pesquisadores, as regras de APF são subjetivas, obrigando que cada contador faça interpretações individuais a partir delas. Existem diversas propostas para que se possa aumentar a confiabilidade dos resultados gerados com AP
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BARBALHO, Felipe de Oliveira. "Uma Abordagem Comparativa entre duas Técnicas de Medição de Software." Universidade Federal de Pernambuco, 2014. https://repositorio.ufpe.br/handle/123456789/18390.

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Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2017-03-08T19:19:52Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_FelipeOliveiraBarbalho.pdf: 1338681 bytes, checksum: 59450531ef14c232cbd53efcacba8b7e (MD5)<br>Made available in DSpace on 2017-03-08T19:19:52Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_FelipeOliveiraBarbalho.pdf: 1338681 bytes, checksum: 59450531ef14c232cbd53efcacba8b7e (MD5) Previous issue date: 2014-04-28<br>Há uma tendência das organiza
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Books on the topic "APFD metric"

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Pseudo-Callisthenes and Bergson Leif 1927-, eds. Carmina praecipue choliambica apud Pseudo-Callisthenem reperta. Almqvist & Wiksell International, 1989.

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Book chapters on the topic "APFD metric"

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Karthigeyan, P., T. Murugesh Vasan, R. S. Abilash, R. Elavarasu, and M. Senthil Raja. "Performance Metrics of Three-Phase Shunt APF Using Hybrid Control-Based Instantaneous Vector Control Theory." In Advances in Systems, Control and Automation. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4762-6_15.

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Singh Yadav, Dharmendra, Prabhat Singh, Vibhash Choudhary, and Rakesh Murthy Gangadari. "Extensive Investigation on Even-Transistor-Configuration CMOS-based SRAM." In Nanoscale Field Effect Transistors: Emerging Applications. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815165647123010011.

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Designing electronic devices with higher efficiency while using reduced power is a problem in the field of electronics. Digital technology utilization is increasing due to its higher speeds, lower power requirements, and stability. Accessing data requires a lot of time, so a circuit is created that will be close to the CPU to provide the information that is required. Cache memory is a type of SRAM-based faster storing device. To enhance the performance of the SRAM cell, Read Delay (RD), Write Delay (WD), read stability, write stability and power dissipation of the intended circuit should all b
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Conference papers on the topic "APFD metric"

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Hernandes, Vinicius, André Carvalho, Eulanda Santos, et al. "A Method for Regression Testing Plan Ordering for Non-Automated Executions in Black Box Testing." In Congresso Ibero-Americano em Engenharia de Software. Sociedade Brasileira de Computação, 2025. https://doi.org/10.5753/cibse.2025.35296.

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In this paper, we propose a method for prioritizing regression test cases based on the probability of detecting software execution failures without source code analysis. To achieve this, our method employs the SentenceBERT model to extract embeddings from textual information of development commits and test scripts. These embeddings are then used by machine learning models to predict the probability of detecting a failure. Our experiments show that the proposed method achieves results equal to or better than those of human experts in 92.52% to 94.24% of scenarios when evaluating the APFD (Avera
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Journal articles
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