What Am I Testing and Where? Comparing Testing Procedures based on Lightweight Requirements Annotations

[Context] The testing of software-intensive systems is performed in different test stages each having a large number of test cases. These test cases are commonly derived from requirements. Each test stages exhibits specific demands and constraints with respect to their degree of detail and what can be tested. Therefore, specific test suites are defined for each test stage. In this paper, the focus is on the domain of embedded systems, where, among others, typical test stages are Software- and Hardware-in-the-loop. [Objective] Monitoring and controlling which requirements are verified in which detail and in which test stage is a challenge for engineers. However, this information is necessary to assure a certain test coverage, to minimize redundant testing procedures, and to avoid inconsistencies between test stages. In addition, engineers are reluctant to state their requirements in terms of structured languages or models that would facilitate the relation of requirements to test executions. [Method] With our approach, we close the gap between requirements specifications and test executions. Previously, we have proposed a lightweight markup language for requirements which provides a set of annotations that can be applied to natural language requirements. The annotations are mapped to events and signals in test executions. As a result, meaningful insights from a set of test executions can be directly related to artifacts in the requirements specification. In this paper, we use the markup language to compare different test stages with one another. [Results] We annotate 443 natural language requirements of a driver assistance system with the means of our lightweight markup language. The annotations are then linked to 1300 test executions from a simulation environment and 53 test executions from test drives with human drivers. Based on the annotations, we are able to analyze how similar the test stages are and how well test stages and test cases are aligned with the requirements. Further, we highlight the general applicability of our approach through this extensive experimental evaluation. [Conclusion] With our approach, the results of several test levels are linked to the requirements and enable the evaluation of complex test executions. By this means, practitioners can easily evaluate how well a systems performs with regards to its specification and, additionally, can reason about the expressiveness of the applied test stage.TU Berlin, Open-Access-Mittel - 202

Identifying and Evaluating Change Patterns and Change Support Features in Process-Aware Information Systems.

In order to provide effective support, the introduction of process-aware information systems (PAIS) must not freeze existing business processes. Instead PAIS should allow authorized users to flexibly deviate from the predefined processes if required and to evolve business processes in a controlled manner over time. Many software vendors promise flexible system solutions for realizing such adaptive PAIS, but are often unable to cope with fundamental issues elated to process change (e.g., correctness and robustness). The existence of different process support paradigms and the lack of methods for comparing existing change approaches makes it difficult for PAIS engineers to choose the adequate technology. In this paper we suggest a set of changes patterns and change support features to foster systematic comparison of existing process management technology with respect to change support. Based on these change patterns and features, we provide a detailed analysis and evaluation of selected systems from both academia and industry

A Requirements-Based Exploration of Open-Source Software Development Projects – Towards a Natural Language Processing Software Analysis Framework

Open source projects do have requirements; they are, however, mostly informal, text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requirements is time-consuming, and for large projects, error-prone. Automated analysis of natural language requirements, even partial, will be of great benefit. Towards that end, I describe the design and validation of an automated natural language requirements classifier for open source software development projects. I compare two strategies for recognizing requirements in open forums of software features. The results suggest that classifying text at the forum post aggregation and sentence aggregation levels may be effective. Initial results suggest that it can reduce the effort required to analyze requirements of open source software development projects. Software development organizations and communities currently employ a large number of software development techniques and methodologies. This implied complexity is also enhanced by a wide range of software project types and development environments. The resulting lack of consistency in the software development domain leads to one important challenge that researchers encounter while exploring this area: specificity. This results in an increased difficulty of maintaining a consistent unit of measure or analysis approach while exploring a wide variety of software development projects and environments. The problem of specificity is more prominently exhibited in an area of software development characterized by a dynamic evolution, a unique development environment, and a relatively young history of research when compared to traditional software development: the open-source domain. While performing research on open source and the associated communities of developers, one can notice the same challenge of specificity being present in requirements engineering research as in the case of closed-source software development. Whether research is aimed at performing longitudinal or cross-sectional analyses, or attempts to link requirements to other aspects of software development projects and their management, specificity calls for a flexible analysis tool capable of adapting to the needs and specifics of the explored context. This dissertation covers the design, implementation, and evaluation of a model, a method, and a software tool comprising a flexible software development analysis framework. These design artifacts use a rule-based natural language processing approach and are built to meet the specifics of a requirements-based analysis of software development projects in the open-source domain. This research follows the principles of design science research as defined by Hevner et. al. and includes stages of problem awareness, suggestion, development, evaluation, and results and conclusion (Hevner et al. 2004; Vaishnavi and Kuechler 2007). The long-term goal of the research stream stemming from this dissertation is to propose a flexible, customizable, requirements-based natural language processing software analysis framework which can be adapted to meet the research needs of multiple different types of domains or different categories of analyses

Understanding Variability-Aware Analysis in Low-Maturity Variant-Rich Systems

Context: Software systems often exist in many variants to support varying stakeholder requirements, such as specific market segments or hardware constraints. Systems with many variants (a.k.a. variant-rich systems) are highly complex due to the variability introduced to support customization. As such, assuring the quality of these systems is also challenging since traditional single-system analysis techniques do not scale when applied. To tackle this complexity, several variability-aware analysis techniques have been conceived in the last two decades to assure the quality of a branch of variant-rich systems called software product lines. Unfortunately, these techniques find little application in practice since many organizations do use product-line engineering techniques, but instead rely on low-maturity \clo~strategies to manage their software variants. For instance, to perform an analysis that checks that all possible variants that can be configured by customers (or vendors) in a car personalization system conform to specified performance requirements, an organization needs to explicitly model system variability. However, in low-maturity variant-rich systems, this and similar kinds of analyses are challenging to perform due to (i) immature architectures that do not systematically account for variability, (ii) redundancy that is not exploited to reduce analysis effort, and (iii) missing essential meta-information, such as relationships between features and their implementation in source code.Objective: The overarching goal of the PhD is to facilitate quality assurance in low-maturity variant-rich systems. Consequently, in the first part of the PhD (comprising this thesis) we focus on gaining a better understanding of quality assurance needs in such systems and of their properties.Method: Our objectives are met by means of (i) knowledge-seeking research through case studies of open-source systems as well as surveys and interviews with practitioners; and (ii) solution-seeking research through the implementation and systematic evaluation of a recommender system that supports recording the information necessary for quality assurance in low-maturity variant-rich systems. With the former, we investigate, among other things, industrial needs and practices for analyzing variant-rich systems; and with the latter, we seek to understand how to obtain information necessary to leverage variability-aware analyses.Results: Four main results emerge from this thesis: first, we present the state-of-practice in assuring the quality of variant-rich systems, second, we present our empirical understanding of features and their characteristics, including information sources for locating them; third, we present our understanding of how best developers\u27 proactive feature location activities can be supported during development; and lastly, we present our understanding of how features are used in the code of non-modular variant-rich systems, taking the case of feature scattering in the Linux kernel.Future work: In the second part of the PhD, we will focus on processes for adapting variability-aware analyses to low-maturity variant-rich systems.Keywords:\ua0Variant-rich Systems, Quality Assurance, Low Maturity Software Systems, Recommender Syste

Integrating model checking with HiP-HOPS in model-based safety analysis

The ability to perform an effective and robust safety analysis on the design of modern safety–critical systems is crucial. Model-based safety analysis (MBSA) has been introduced in recent years to support the assessment of complex system design by focusing on the system model as the central artefact, and by automating the synthesis and analysis of failure-extended models. Model checking and failure logic synthesis and analysis (FLSA) are two prominent MBSA paradigms. Extensive research has placed emphasis on the development of these techniques, but discussion on their integration remains limited. In this paper, we propose a technique in which model checking and Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) – an advanced FLSA technique – can be applied synergistically with benefit for the MBSA process. The application of the technique is illustrated through an example of a brake-by-wire system

Seamless Variability Management With the Virtual Platform

Customization is a general trend in software engineering, demanding systems that support variable stakeholder requirements. Two opposing strategies are commonly used to create variants: software clone & own and software configuration with an integrated platform. Organizations often start with the former, which is cheap, agile, and supports quick innovation, but does not scale. The latter scales by establishing an integrated platform that shares software assets between variants, but requires high up-front investments or risky migration processes. So, could we have a method that allows an easy transition or even combine the benefits of both strategies? We propose a method and tool that supports a truly incremental development of variant-rich systems, exploiting a spectrum between both opposing strategies. We design, formalize, and prototype the variability-management framework virtual platform. It bridges clone & own and platform-oriented development. Relying on programming-language-independent conceptual structures representing software assets, it offers operators for engineering and evolving a system, comprising: traditional, asset-oriented operators and novel, feature-oriented operators for incrementally adopting concepts of an integrated platform. The operators record meta-data that is exploited by other operators to support the transition. Among others, they eliminate expensive feature-location effort or the need to trace clones. Our evaluation simulates the evolution of a real-world, clone-based system, measuring its costs and benefits.Comment: 13 pages, 10 figures; accepted for publication at the 43rd International Conference on Software Engineering (ICSE 2021), main technical trac

Change Support in Process-Aware Information Systems - A Pattern-Based Analysis

In today's dynamic business world the economic success of an enterprise increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Process-aware information systems (PAIS) offer promising perspectives in this respect and are increasingly employed for operationally supporting business processes. To provide effective business process support, flexible PAIS are needed which do not freeze existing business processes, but allow for loosely specified processes, which can be detailed during run-time. In addition, PAIS should enable authorized users to flexibly deviate from the predefined processes if required (e.g., by allowing them to dynamically add, delete, or move process activities) and to evolve business processes over time. At the same time PAIS must ensure consistency and robustness. The emergence of different process support paradigms and the lack of methods for comparing existing change approaches have made it difficult for PAIS engineers to choose the adequate technology. In this paper we suggest a set of changes patterns and change support features to foster the systematic comparison of existing process management technology with respect to process change support. Based on these change patterns and features, we provide a detailed analysis and evaluation of selected systems from both academia and industry. The identified change patterns and change support features facilitate the comparison of change support frameworks, and consequently will support PAIS engineers in selecting the right technology for realizing flexible PAIS. In addition, this work can be used as a reference for implementing more flexible PAIS

Natural Language Requirements Processing: A 4D Vision

The future evolution of the application of natural language processing technologies in requirements engineering can be viewed from four dimensions: discipline, dynamism, domain knowledge, and datasets

The state of adoption and the challenges of systematic variability management in industry

Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering—an approach to systematically develop portfolios of products—is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on re-engineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium- to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.This work is supported by Vinnova Sweden, Fond Unique Interminist´eriel (FUI) France, and the Swedish Research Council. Open access funding provided by University of Gothenbur