Improving regression testing transparency and efficiency with history-based prioritization – an industrial case study

Abstract—Background: History based regression testing was proposed as a basis for automating regression test selection, for the purpose of improving transparency and test efficiency, at the function test level in a large scale software development organization. Aim: The study aims at investigating the current manual regression testing process as well as adopting, implementing and evaluating the effect of the proposed method. Method: A case study was launched including: identification of important factors for prioritization and selection of test cases, implementation of the method, and a quantitative and qualitative evaluation. Results: 10 different factors, of which two are history-based, are identified as important for selection. Most of the information needed is available in the test management and error reporting systems while some is embedded in the process. Transparency is increased through a semi-automated method. Our quantitative evaluation indicates a possibility to improve efficiency, while the qualitative evaluation supports the general principles of history-based testing but suggests changes in implementation details

Construction, corruption, and developing countries

The construction industry accounts for about one-third of gross capital formation. Governments have major roles as clients, regulators, and owners of construction companies. The industry is consistently ranked as one of the most corrupt: large payments to gain or alter contracts and circumvent regulations are common. The impact of corruption goes beyond bribe payments to poor quality construction of infrastructure with low economic returns alongside low funding for maintenance-and this is where the major impact of corruption is felt. Regulation of the sector is necessary, but simplicity, transparency, enforcement, and a focus on the outcomes of poor construction are likely to have a larger impact than voluminous but poorly enforced regulation of theconstruction process. Where government is the client, attempts to counter corruption need to begin at the level of planning and budgeting. Output-based and community-driven approaches show some promise as tools to reduce corruption. At the same time they will need to be complimented by a range of other interventions including publication of procurement documents, independent and community oversight, physical audit, and public-private anticorruption partnerships.Governance Indicators,Poverty Monitoring&Analysis,Corruption&Anitcorruption Law,Public Sector Corruption&Anticorruption Measures,Social Accountability

A review paper: optimal test cases for regression testing using artificial intelligent techniques

The goal of the testing process is to find errors and defects in the software being developed so that they can be fixed and corrected before they are delivered to the customer. Regression testing is an essential quality testing technique during the maintenance phase of the program as it is performed to ensure the integrity of the program after modifications have been made. With the development of the software, the test suite becomes too large to be fully implemented within the given test cost in terms of budget and time. Therefore, the cost of regression testing using different techniques should be reduced, here we dealt many methods such as retest all technique, regression test selection technique (RTS) and test case prioritization technique (TCP). The efficiency of these techniques is evaluated through the use of many metrics such as average percentage of fault detected (APFD), average percentage block coverage (APBC) and average percentage decision coverage (APDC). In this paper we dealt with these different techniques used in test case selection and test case prioritization and the metrics used to evaluate their efficiency by using different techniques of artificial intelligent and describe the best of all

Supply Chain Resilience Meets Quality Management

Purpose: This study is aimed at supply chain resilience and quality management, which are critical in today's volatile global economy marked by various disruptions. The focus is on how these traditionally separate disciplines can be combined to enhance organizational performance.   Theoretical framework:  The theoretical framework revolves around the concepts of supply chain resilience, which includes elements like proactive risk assessment, adaptability, collaborative networks, strategic redundancies, and quality management principles. The research scrutinizes their interplay, revealing significant overlap and implications for organizational outcomes.   Design/Methodology/Approach:  An exploratory case study approach forms the core methodology, primarily utilizing secondary data to gain insights into real-world scenarios. This approach enables a deep understanding of the critical factors influencing supply chain resilience and the impact of quality management concepts on customer satisfaction and product/service quality in supply chain processes. The questionnaire is distributed to get insights into the company's practices.   Findings:  The findings indicate that integrating supply chain resilience with quality management leads to more sustained and improved organizational outcomes. A resilient supply chain is quicker to recover from disruptions, minimizing financial impacts. Concurrently, a steadfast focus on quality ensures customer satisfaction and loyalty. This integration offers synergistic benefits, contributing to operational efficiency, market competitiveness, and a more substantial brand reputation.   Research, Practical & Social implications: The study provides insights into critical factors of supply chain resilience and their interconnections with quality management concepts. These insights can inform strategies for enhancing resilience and quality management in supply chains. Practically, the study offers a guide for organizations to adopt a unified approach that optimizes supply chain resilience and quality management. This approach is particularly relevant for organizations seeking to improve operational efficiency and customer satisfaction through better risk management and quality assurance processes. Socially, the study highlights the importance of resilient and high-quality supply chains in today’s business landscape by maintaining Sustainable Developmental Goals.   Originality/Value:  This research highlights how resilience, characterized by adaptability and robust recovery in disruptive scenarios, and stringent quality management, crucial for meeting customer expectations, are fundamental in modern supply chains. The study emphasizes the importance of a risk management culture and the role of digital technologies in enhancing supply chain resilience, underscoring their vital contributions during crises like the COVID-19 pandemic. Thus, this work offers valuable insights into achieving more resilient and high-quality supply chains in today's challenging business environment through the integration of Quality Management Tools

Governance Impact on Public-Private Partnerships for Member Countries of the World Bank Group

Member countries of the World Bank Group (WBG) increasingly turn to public-private partnerships (PPPs) to finance their transportation infrastructure projects due to the financial burden of undertaking big projects on their own. The World Bank coordinates the PPPs between investors and recipient countries. PPPs are expected to produce positive outcomes that respond to policy objectives. However, the outcomes and benefits of PPPs not only depend on several factors, but more importantly on how those factors interact with one another to yield the expected outcomes. This dissertation has identified good governance, PPP governance, and PPP outcome as the key concepts in the examination of the value that PPPs bring to countries that receive transportation PPP contracts. Using secondary data, the study explores the relationships between the three major concepts and assesses the possible mediating role of the internationally recognized PPP practices on the relationship between good governance and PPP outcome. The relationships are also examined for groups of countries based on their income level. The dissertation uses the overarching theory of good governance to explore these relationships. The dissertation analyzes the relationships using multivariate regression in the generalized structural equation modeling (GSEM) in the STATA package. Most of the hypotheses set in the study were supported. Recommendations are made to the World Bank and member countries to conduct effective transportation PPP contracts. The contribution to theory and practice is discussed. A framework for examining the relationships is provided

A Mapping Study of scientific merit of papers, which subject are web applications test techniques, considering their validity threats

Progress in software engineering requires (1) more empirical studies of quality, (2) increased focus on synthesizing evidence, (3) more theories to be built and tested, and (4) the validity of the experiment is directly related with the level of confidence in the process of experimental investigation. This paper presents the results of a qualitative and quantitative classification of the threats to the validity of software engineering experiments comprising a total of 92 articles published in the period 2001-2015, dealing with software testing of Web applications. Our results show that 29.4% of the analyzed articles do not mention any threats to validity, 44.2% do it briefly, and 14% do it judiciously; that leaves a question: these studies have scientific value