Companies struggle to continuously develop and deploy AI models complex production systems due characteristics while assuring quality. To ease the development process, continuous pipelines for have become an active research area where consolidated in-depth analysis regarding terminology, triggers, tasks, challenges is required. This paper includes a Multivocal Literature Review we 151 relevant formal informal sources. In addition, nine-semi structured interviews with participants from...

Software Product Lines (SPLs) are families of related software systems distinguished by the set features each one provides. Over past decades SPLs have been subject extensive research and application both in academia industry. practices proven benefits such as better product customization reduced time to market. Testing pose additional challenges stemming from typically large number variants which make it infeasible test every single them. In recent years, there has an on applying...

We propose Guided Random Testing (GRT), which uses static and dynamic analysis to include information on program types, data, dependencies in various stages of automated test generation. Static extracts knowledge from the system under test. Test coverage is further improved through state fuzzing continuous analysis. evaluated GRT 32 real-world projects found that outperforms major peer techniques terms code (by 13 %) mutation score 9 %). On four studied benchmarks Defects4J, contain 224 real...

Testing is a major cost factor in software development. Test automation has been proposed as one solution to reduce these costs. tools promise increase the number of tests they run and frequency at which them. So why not automate every test? In this paper we discuss question "When should test be automated?" trade-off between automated manual testing. We reveal problems overly simplistic models commonly used make decisions about automating introduce an alternative model based on opportunity...

The main challenges are discussed together with the lessons learned from past and ongoing research along development cycle of machine learning systems. This will be done by taking into account intrinsic conditions nowadays deep models, data software quality issues human-centered artificial intelligence (AI) postulates, including confidentiality ethical aspects. analysis outlines a fundamental theory-practice gap which superimposes AI system engineering at level assurance, model building,...

Static code analysis techniques examine programs without actually executing them. The main benefits lie in improving software quality by detecting problematic constructs and potential defects early development stages. Today, static is a widely used assurance technique numerous tools are available for established programming languages like C/C++, Java, or C#. However, the domain of programmable logic controller (PLC) programming, still rare, although many properties PLC beneficial techniques....

High data quality is fundamental for today's AI-based systems. However, although has been an object of research decades, there a clear lack on potential issues (e.g., ambiguous, extraneous values). These kinds are latent in nature and thus often not obvious. Nevertheless, they can be associated with increased risk future problems systems technical debt, data-induced faults). As counterpart to code smells software engineering, we refer such as Data Smells. This article conceptualizes...

Microservice-based systems have emerged as an effective architecture for countless industry applications. They provide applications small, independent, and modular services. With the increasing interest in such systems, it is important to tackle challenges related their quality assurance. However, advance research this area, are required evaluate new approaches tools. In paper, we perform a systematic literature search used testing monitoring microservice-based aid future research. We...

Practitioners report that experience plays an important role in effective software testing. We investigate the of a multiple case study about three successful projects conducted at Siemens Austria and document state practice testing systems. The studied were employed from domains telecommunications, insurance banking, as well safety-critical railway shows test design is to considerable extent based on all experience-based supplementary approach requirements-based further analyzes different...

Static code analysis techniques analyze programs by examining the source without actually executing them. The main benefits lie in improving software quality detecting potential defects and problematic constructs early development stages. Today, static is widely used numerous tools are available for established programming languages like C/C++, Java, C# others. However, domain of PLC programming, still rare. In this paper we present an approach tool support programs. discusses opportunities...

Artificial intelligence and software engineering complement each other in various ways. This special issue highlights how this relationship is developing over time to address the challenges faced modern-day computing.

The integration of Large Language Models (LLMs), such as ChatGPT and GitHub Copilot, into software engineering workflows has shown potential to enhance productivity, particularly in testing. This paper investigates whether LLM support improves defect detection effectiveness during unit Building on prior studies comparing manual tool-supported testing, we replicated extended an experiment where participants wrote tests for a Java-based system with seeded defects within time-boxed session,...

Testing via graphical user interfaces (GUI) is a complex and labor-intensive task. Numerous techniques, tools frameworks have been proposed for automating GUI testing. In many projects, however, the introduction of automated tests did not reduce overall effort testing but shifted it from manual test execution to script development maintenance. As pragmatic solution, random approaches (aka "monkey testing") suggested exploration system under GUI. This paper presents versatile framework monkey...

Background: Testing is an essential activity in safety-critical software development, following high standards terms of code coverage. Mutation testing allows assessing the effectiveness and helps to further improve test cases. However, mutation not widely practiced due scalability problems when applied real-world systems. Objective: The objective study investigate applicability usefulness for improving quality unit context Method: A case has been conducted together with engineering company...

The readability of software code is a key success criterion for understanding and maintaining systems tests. In industry practice, limited number guidelines aim improving assessing the (test) code. Although several studies focus on investigating code, we observed research work that focuses test this paper systematically characteristics, factors, assessment criteria have an impact We build Systematic Mapping Study (SMS) to identify readability, legibility, understandability support improve...

In this paper we describe our experience from developing and testing a visual graphical user interface (GUI) editor for mobile multimedia devices. Testing of the editor's highly interactive is critical its success, yet remains challenge due to specification often intangible quality characteristics GUI proneness change. The approach provide supporting exploratory with tools integrated tested object. Thus step-by-step guide manual can be enhanced automated elements that directly manipulate...

Unit testing of legacy code is often characterized by the goal to find a maximum number defects with minimal effort. In context restrictive time frames and limited resources, approaches for generating test cases promise increased defect detection effectiveness. This paper presents results an empirical study investigating effectiveness (a) manual unit conducted 48 master students within limit 60 minutes (b) tool-supported random case generation Randoop. Both have been applied on Java...