Applications of Synchronized Pushdown Systems

A precise static data-flow analysis transforms the program into a context-sensitive and field-sensitive approximation of the program. It is challenging to design an analysis of this precision efficiently due to the fact that the analysis is undecidable per se. Synchronized pushdown systems (SPDS) present a highly precise approximation of context-sensitive and field-sensitive data-flow analysis. This chapter presents some data-flow analyses that SPDS can be used for. Further on, this chapter summarizes two other contributions of the thesis “Synchronized Pushdown System for Pointer and Data-Flow Analysis” called Boomerang and IDEal. Boomerang is a demand-driven pointer analysis that builds on top of SPDS and minimizes the highly computational effort of a whole-program pointer analysis by restricting the computation to the minimal program slice necessary for an individual query. IDEal is a generic and efficient framework for data-flow analyses, e.g., typestate analysis. IDEal resolves pointer relations automatically and efficiently by the help of Boomerang. This reduces the burden of implementing pointer relations into an analysis. Further on, IDEal performs strong updates, which makes the analysis sound and precise.

Software Developers’ Work Habits and Expertise: Empirical Studies on Sketching, Code Plagiarism, and Expertise Development

Analyzing and understanding software developers’ work habits and resulting needs is an essential prerequisite to improve software development practice. In our research, we utilize different qualitative and quantitative research methods to empirically investigate three underexplored aspects of software development: First, we analyze how software developers use sketches and diagrams in their daily work and derive requirements for better tool support. Then, we explore to what degree developers copy code from the popular online platform Stack Overflow without adhering to license requirements and motivate why this behavior may lead to legal issues for affected open source software projects. Finally, we describe a novel theory of software development expertise and identify factors fostering or hindering the formation of such expertise. Besides, we report on methodological implications of our research and present the open dataset SOTorrent, which supports researchers in analyzing the origin, evolution, and usage of content on Stack Overflow. The common goal for all studies we conducted was to better understand software developers’ work practices. Our findings support researchers and practitioners in making data-informed decisions when developing new tools or improving processes related to either the specific work habits we studied or expertise development in general.

Same but Different: Consistently Developing and Evolving Software Architecture Models and Their Implementation

As software architecture is a main driver for the software quality, source code is often accompanied by software architecture specifications. When the implementation is changed, the architecture specification is often not updated along with the code, which introduces inconsistencies between these artifacts. Such inconsistencies imply a risk of misunderstandings and errors during the development, maintenance, and evolution, causing serious degradation over the lifetime of the system. In this chapter we present the Explicitly Integrated Architecture approach and its tool Codeling, which remove the necessity for a separate representation of software architecture by integrating software architecture information with the program code. By using our approach, the specification can be extracted from the source code and changes in the specification can be propagated to the code. The integration of architecture information with the code leaves no room for inconsistencies between the artifacts and creates links between artifacts. We evaluate the approach and tool in a use case with real software in development and with a benchmark software, accompanied by a performance evaluation.

Actionable Program Analyses for Improving Software Performance

Nowadays, we have greater expectations of software than ever before. This is followed by the constant pressure to run the same program on smaller and cheaper machines. To meet this demand, the application’s performance has become an essential concern in software development. Unfortunately, many applications still suffer from performance issues: coding or design errors that lead to performance degradation. However, finding performance issues is a challenging task: there is limited knowledge on how performance issues are discovered and fixed in practice, and current profilers report only where resources are spent, but not where resources are wasted. In this chapter, we investigate actionable performance analyses that help developers optimize their software by applying relatively simple code changes. We focus on optimizations that are effective, exploitable, recurring, and out-of-reach for compilers. These properties suggest that proposed optimizations lead to significant performance improvement, that they are easy to understand and apply, applicable across multiple projects, and that the compilers cannot guarantee that these optimizations always preserve the original program semantics. We implement our actionable analyses in practical tools and demonstrate their potential in improving software performance by applying relatively simple code optimizations.

Ernst Denert Software Engineering Awards 2019

The need to improve software engineering practices is continuously rising and software development practitioners are highly interested in improving their software systems and the methods to build them. And well, software engineering research has numerous success stories. The Ernst Denert Software Engineering Award specifically rewards researchers that value the practical impact of their work and aim to improve current software engineering practices. This chapter summarizes the awards history as well as the current reward process and criteria.

Software Engineering

Abstract“A Passion for Software-Engineering.” This was the headline of a 2015 newspaper article about Ernst Denert. And they were absolutely right. Ernst Denert is really passionate about developing software with excellent quality in a predictable and systematic style. Furthermore, he is very much interested in encouraging young people to study computer science or at least to learn how programming and digitalization works, as well as computer science students to focus on software engineering principles and software development. This chapter is a personal view of Ernst Denert on the software engineering discipline.

Applied Artifact-Based Analysis for Architecture Consistency Checking

The usage of models within model-driven software development aims at facilitating complexity management of the system under development and closing the gap between the problem and the solution domain. Utilizing model-driven software development (MDD) tools for agile development can also increase the complexity within a project. The huge number of different artifacts and relations, their different kinds, and the high degree of automation hinder the understanding, maintenance, and evolution within MDD projects. A systematic approach to understand and manage MDD projects with a focus on its artifacts and corresponding relations is necessary to handle the complexity. The artifact-based analysis presented in this paper is such an approach. This paper gives an overview of different contributions of the artifact-based analysis but focuses on a specific kind of analysis: architecture consistency checking of model-driven development projects. By applying this kind of analyses, differences between the desired architecture and the actual architecture of the project at a specific point in time can be revealed.