Lars Grunske

• Professor
• Professor at Humboldt-Universität zu Berlin

Fault localization is a fundamental aspect of debugging, aiming to identify code regions likely responsible for failures. Traditional techniques primarily correlate statement execution with failures, yet program behavior is influenced by diverse execution features-such as variable values, branch conditions, and definition-use pairs-that can provide...

Deep learning (DL) components have been broadly applied in diverse applications. Similar to traditional software engineering, effective test case generation methods are needed by industry to enhance the quality and robustness of these deep learning components. To this end, we propose a novel automatic software testing technique, TAEFuzz (Automatic...

Complex relations between cybernetic and physical components of a cyber-physical system (CPS) in tandem with continuous environment changes represent a challenge to engineering robust CPSs. To help engineers determine the cause of violations, there is a need for a systematic approach that helps understanding the system behaviors that lead to critic...

Context Computational materials science (CMS) focuses on in silico experiments to compute the properties of known and novel materials, where many software packages are used in the community. The NOMAD Laboratory (Draxl C, Scheffler) offers to store the input and output files in its FAIR data repository. Since the file formats of these software pack...

Context Ensuring safety for any sophisticated system is getting more complex due to the rising number of features and functionalities. This calls for formal methods to entrust confidence in such systems. Nevertheless, using formal methods in industry is demanding because of their lack of usability and the difficulty of understanding verification re...

Context: Ensuring safety for any sophisticated system is getting more complex due to the rising number of features and functionalities. This calls for formal methods to entrust confidence in such systems. Nevertheless, using formal methods in industry is demanding because of their lack of usability and the difficulty of understanding verification r...

To accurately make adaptation decisions, a self-adaptive system needs precise means to analyze itself at runtime. To this end, runtime verification can be used in the feedback loop to check that the managed system satisfies its requirements formalized as temporal-logic properties. These requirements, however, may change due to system evolution or u...

Context: Computational materials science (CMS) focuses on in silico experiments to compute the properties of known and novel materials, where many software packages are used in the community. The NOMAD Laboratory1 offers to store the input and output files in its FAIR data repository. Since the file formats of these software packages are non-standa...

Model matching algorithms are used to identify common elements in input models, which is a fundamental precondition for many software engineering tasks, such as merging software variants or views. If there are multiple input models, an n-way matching algorithm that simultaneously processes all models typically produces better results than the seque...

Context: The goal of specification pattern catalogs for real-time requirements is to mask the complexity of specifying such requirements in a timed temporal logic for verification. For this purpose, they provide frontends to express and translate pattern-based natural language requirements to formulae in a suitable logic. However, the widely used r...

Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introduced to support research in the field of self-adaptive systems. While these artifacts have shown their value, it is not clear to what extent these artifacts support resear...

Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introduced to support research in the field of self-adaptive systems. While these artifacts have shown their value, it is not clear to what extent these artifacts support resear...

Context: Safety is of paramount importance for cyber–physical systems in domains such as automotive, robotics, and avionics. Formal methods such as model checking are one way to ensure the safety of cyber–physical systems. However, adoption of formal methods in industry is hindered by usability issues, particularly the difficulty of understanding m...

Context Identifying potential vulnerable code is important to improve the security of our software systems. However, the manual detection of software vulnerabilities requires expert knowledge and is time-consuming, and must be supported by automated techniques. Objective Such automated vulnerability detection techniques should achieve a high accur...

A popular metric to evaluate the performance of fuzzers is branch coverage. However, we argue that focusing solely on covering many different branches (i.e., the richness) is not sufficient since the majority of the covered branches may have been exercised only once, which does not inspire a high confidence in the reliability of the covered code. I...

Context: Identifying potential vulnerable code is important to improve the security of our software systems. However, the manual detection of software vulnerabilities requires expert knowledge and is time-consuming, and must be supported by automated techniques. Objective: Such automated vulnerability detection techniques should achieve a high accu...

Context: Safety is of paramount importance for cyber-physical systems in domains such as automotive, robotics, and avionics. Formal methods such as model checking are one way to ensure the safety of cyber-physical systems. However, adoption of formal methods in industry is hindered by usability issues, particularly the difficulty of understanding m...

The comparison of a model of a process against event data recorded during its execution, known as conformance checking, is an important means in process analysis. Yet, common conformance checking techniques are computationally expensive, which makes a complete analysis infeasible for large logs. To mitigate this problem, existing techniques levera...

Context: The complexity of modern safety-critical systems in industries keep on increasing due to the rising number of features and functionalities. This calls for formal methods in order to entrust confidence in such systems. Nevertheless, using formal methods in industry is demanding because of usability issues, e.g., the difficulty of understand...

Software bugs significantly contribute to software cost and increase the risk of system malfunctioning. In recent years, many automated program-repair approaches have been proposed to automatically fix undesired program behavior. Despite of their great success, specific problems such as fixing bugs with partial fixes still remain unresolved. A part...

Automated program repair reduces the manual effort in fixing program errors. However, existing repair techniques modify a buggy program such that it passes given tests. Such repair techniques do not discriminate between correct patches and patches that overfit the available tests (breaking untested but desired functionality). We propose an integrat...

In this article, we introduce a probabilistic verification algorithm for stochastic regular expressions over a probabilistic extension of the Action based Computation Tree Logic (ACTL*). The main results include a novel model checking algorithm and a semantics on the probabilistic action logic for stochastic regular expressions (SREs). Specific to...

Models in Model-driven Engineering are primary development artifacts that are heavily edited in all stages of software development and that can become temporarily inconsistent during editing. In general, there are many alternatives to resolve an inconsistency, and which one is the most suitable depends on a variety of factors. As also proposed by r...

Context: In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. We consider the problem of generating test suites for mobile...

Context: In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. We consider the problem of generating test suites for mobile...

Contract-based design (CBD) is an emerging paradigm for complex systems, specifying the input-output behavior of a component by defining what the component guarantees, provided its environment satisfies the given assumptions. Under certain circumstances, it is possible to verify the decomposition of contracts to conclude the correctness of the top-...

Anyone working in the technology sector is probably familiar with the question: “Have you tried turning it off and on again?”, as this is usually the default question asked by tech support. Similarly, it is known in search-based testing that metaheuristics might get trapped in a plateau during a search. As a human, one can look at the gradient of t...

A fuzzer provides randomly generated inputs to a targeted software to expose erroneous behavior. To efficiently detect defects, generated inputs should conform to the structure of the input format and thus, grammars can be used to generate syntactically correct inputs. In this context, fuzzing can be guided by probabilities attached to competing ru...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Grammars can serve as producers for structured test inputs that are syntactically correct by construction. A probabilistic grammar assigns probabilities to individual productions, thus controlling the distribution of input elements. Using the grammar...

A fuzzer provides randomly generated inputs to a targeted software to expose erroneous behavior. To efficiently detect defects, generated inputs should conform to the structure of the input format and thus, grammars can be used to generate syntactically correct inputs. In this context, fuzzing can be guided by probabilities attached to competing ru...

Anyone working in the technology sector is probably familiar with the question: "Have you tried turning it off and on again?", as this is usually the default question asked by tech support. Similarly, it is known in search based testing that metaheuristics might get trapped in a plateau during a search. As a human, one can look at the gradient of t...

Java Path nder (JPF) was originally developed as an explicit- state software model checker, and subsequently evolved into an extensible Java bytecode analysis framework that has been suc- cessfully used to implement techniques such as symbolic and con- colic execution, compositional veri cation, parallel execution, in- cremental program analysis, a...

Regression testing ensures the correctness of the software during its evolution, with special attention on the absence of unintended side-e ects that might be introduced by changes. However, the manual creation of regression test cases, which expose divergent behavior, needs a lot of e ort. A solution is the idea of shadow symbolic execution, which...

To deal with the rising system complexity, Model-Based System Development (MBSD) approaches are becoming popular due to their promise to improve consistency between different views of the system model. For dependable systems, safety analysis is one of the important views. Model-Based Safety Analysis (MBSA) can partially automate the generation of s...

Many fields of science rely on software systems to answer different research questions. For valid results researchers need to trust the results scientific software produces, and consequently quality assurance is of utmost importance. In this paper we are investigating the impact of quality assurance in the domain of computational materials science...

In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. To obtain better results while avoiding trial-and-error experiments, a...

Successful system evolution is dependent on knowledge about the system itself, its past and its present, as well as the environment of the system. This chapter presents several approaches to automate the acquisition of knowledge about the system’s past, for example past evolution steps, and its present, for example models of its behaviour. Based on...

Many fields of science rely on software systems to answer different research questions. For valid results researchers need to trust the results scientific software produces, and consequently quality assurance is of utmost importance. In this paper we are investigating the impact of quality assurance in the domain of computational materials science...

In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. To obtain better results while avoiding trial-and-error experiments, a...

Pure spectrum‐based fault localization (SBFL) is a well‐studied statistical debugging technique that only takes a set of test cases (some failing and some passing) and their code coverage as input and produces a ranked list of suspicious program elements to help the developer identify the location of a bug that causes a failed test case. Studies sh...

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an e...

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an e...

Generating structured input files to test programs can be performed by techniques that produce them from a grammar that serves as the specification for syntactically correct input files. Two interesting scenarios then arise for effective testing. In the first scenario, software engineers would like to generate inputs that are as similar as possible...

Automated test suite generation (ATSG) is an important topic in software engineering, with a wide range of techniques and tools being used in academia and industry. While their usefulness is widely recognized, due to the labor-intensive nature of the task, the effectiveness of the different techniques in automatically generating test cases for diff...

Automated program repair has been studied via the use of techniques involving search, semantic analysis and artificial intelligence. Most of these techniques rely on tests as the correctness criteria, which causes the test overfitting problem. Although various approaches such as learning from code corpus have been proposed to address this problem,...

With the increasing availability of business process related event logs, the scalability of techniques that discover a process model from such logs becomes a performance bottleneck. In particular, exploratory analysis that investigates manifold parameter settings of discovery algorithms, potentially using a software-as-a-service tool, relies on fas...

During the whole life-cycle of software-intensive systems in safety-critical domains, system models must consistently co-evolve with quality evaluation models like fault trees. However, performing these co-evolution steps is a cumbersome and often manual task. To understand this problem in detail, we have analyzed the evolution and mined common cha...

Search-based software testing automatically derives test inputs for a software system with the goal of improving various criteria, such as branch coverage. In many cases, evolutionary algorithms are implemented to find near-optimal test suites for software systems. The result of the search is usually received without any indication of how successfu...

Complex software systems experience failures at runtime even though a lot of effort is put into the development and operation. Reactive approaches detect these failures after they have occurred and already caused serious consequences. In order to execute proactive actions, the goal of online failure prediction is to detect these failures in advance...

This chapter gives a summary of the state-of-the-art approaches from different research fields that can be applied to continuously forecast future developments of time series data streams. More specifically, the input time series data contains continuously monitored metrics that quantify the amount of incoming workload units to a self-aware system....

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an e...

Debugging is a costly process that consumes much of developer time and energy. To help reduce debugging effort, many studies have proposed various fault localization approaches. These approaches take as input a set of test cases (some failing, some passing) and produce a ranked list of program elements that are likely to be the root cause of the fa...

Failures in software systems during operation are inevitable. They cause system downtime, which needs to be minimized to reduce or avoid unnecessary costs and customer dissatisfaction. Online failure prediction aims at identifying upcoming failures at runtime to enable proactive maintenance actions. Existing online failure prediction approaches foc...

Agile and iterative development with changing requirements lead to continuously changing models. In particular, the researchers are faced with the problem of consistently co-evolving different views of a model-based system. Whenever one model undergoes changes, corresponding models should co-evolve with respect to this change. On the other hand, do...

Formal methods offer an effective means to assert the correctness of software systems through mathematical reasoning. However, the need to formulate system properties in a purely mathematical fashion can create pragmatic barriers to the application of these techniques. For this reason, Dwyer et al. invented property specification patterns which is...

Software-Evolutionsforschung ist essenziell, um langlebige Software verlässlich und effizient zu entwickeln. Dieser Beitrag plädiert auf Basis der Erfahrungen aus dem DFG-Schwerpunktprogramm (SPP) ,,Design for Future – Managed Software Evolution“ für eine stärkere Rolle von empirischer Forschung zu Phänomenen im Kontext von Software-Evolution und d...

Software testing is a crucial part of software development. It enables quality assurance, such as correctness, completeness and high reliability of the software systems. Current state-of-the-art software testing techniques employ search-based optimisation methods, such as genetic algorithms to handle the difficult and laborious task of test data ge...

Model transformations are a crucial part of Model-Driven Engineering (MDE) technologies but are usually hard to specify and maintain for many engineers. Most current approaches use meta-model-driven transformation specification via textual scripting languages. These are often hard to specify, understand and maintain. We present a novel approach tha...

Software testing is a crucial part of software development. It enables quality assurance, such as correctness, completeness and high reliability of the software systems. Current state-of-the-art software testing techniques employ search-based optimisation methods, such as genetic algorithms to handle the difficult and laborious task of test data ge...

Failure mode and effects analysis (FMEA), is a widely used deductive failure analysis for safety critical systems. Since modern safety critical systems tend to increased complexity, automation and tool support have a long history in research and industry. Whereas compact embedded systems can be analyzed using FMEA in a manually maintained table usi...

Online failure prediction for large-scale software systems is a challenging task. One reason is the complex structure of many-partially inter-dependent-hardware and software components. State-of-the-art approaches use separate prediction models for parameters of interest or a monolithic prediction model which includes different parameters of all co...

A self-adaptive software system modifies its behavior at runtime in response to changes within the system or in its execution environment. The fulfillment of the system requirements needs to be guaranteed even in the presence of adverse conditions and adaptations. Thus, a key challenge for self-adaptive software systems is assurance. Traditionally,...

This paper summarizes our earlier contributions on reactive and proactive detection of quality of service problems. The first contribution is applying statistical control charts to reactively detect QoS violations. The second contribution is applying time series modeling to proactively detect potential QoS violations.

Recommendation systems support users and developers of various computer and software systems to overcome information overload, perform information discovery tasks, and approximate computation, among others. They have recently become popular and have attracted a wide variety of application scenarios ranging from business process modeling to source c...

Complex model transformation is crucial in several domains, including Model-Driven Engineering (MDE), information visualisation and data mapping. Most current approaches use meta-model-driven transformation specification via coding in textual scripting languages. This paper demonstrates a novel approach and tool support that instead provides for sp...

Abstract All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iterat...

This special issue of the Journal of Systems and Software presents novel software architecture optimisation frameworks. The majority of the approaches consider the problem of optimising conflicting quality attributes simultaneously. Other approaches focus on effectively searching,for better software architectures by either using smart problem-depen...

Reliability is the key factor for software system quality. Several models have been introduced to estimate and predict reliability based on results of software testing activities. Software Reliability Growth Models (SRGMs) are considered the most commonly used to achieve this goal. Over the past decades, many researchers have discussed SRGMs’ assum...

Failures or unexpected events are inevitable in critical and complex systems. Proactive failure detection is an approach that aims to detect such events in advance so that preventative or recovery measures can be planned, thus improving system availability. Machine learning techniques have been successfully applied to learn patterns from available...

Performance analysis is often conducted before achieving full knowledge of a software system, in other words under a certain degree of uncertainty. Uncertainty is particularly critical in the performance domain when it relates to values of parameters such as workload, operational profile, resource demand of services, service time of hardware device...

Self-adaptive software systems modify their behaviour at runtime in response to changes in the system or its environment. The fulfilment of the system requirements and reachability of the system goals needs to be guaranteed even in the presence of adaptations. Thus, a key challenge for self-adaptive software systems is assurance. Traditionally, con...

Safety-critical systems are subject to rigorous safety analyses, e.g., hazard analyses. Fault trees are a deductive technique to derive the combination of faults which cause a hazard. There is a tight relationship between fault trees and system architecture as the components contain the faults and the component structure influences the fault combin...

Probabilistic models are commonly used to evaluate quality at-tributes, such as reliability, availability, safety, and performance, of software-intensive systems. The accuracy of the evaluation results depends on a num-ber of system properties which have to be estimated, such as environmental factors or system usage. Researchers have tackled this p...

It is currently considered good software engineering practice to decide between design alternatives based on quantitative architecture evaluations for different quality attributes, such as reliability and performance. However, the results of these quantitative architecture evaluations are dependent on design-time estimates for a series of model-par...

Predicting future values of Quality of Service (QoS) attributes can assist in the control of software intensive systems by preventing QoS violations before they happen. Currently, many approaches prefer Autoregressive Integrated Moving Average (ARIMA) models for this task, and assume the QoS attributes' behavior can be linearly modeled. However, th...

Probabilistic models are commonly used to evaluate quality attributes, such as reliability, availability, safety and performance of software-intensive systems. The accuracy of the evaluation results depends on a number of system properties which have to be estimated, such as environmental factors or system usage. Researchers have tackled this probl...

Availability of several web services having a similar functionality has led to using quality of service (QoS) attributes to support services selection and management. To improve these operations and be performed proactively, time series ARIMA models have been used to forecast the future QoS values. However, the problem is that in this extremely dyn...

Currently software systems operate in highly dynamic contexts, and consequently they have to adapt their behavior in response to changes in their contexts or/and requirements. Existing approaches trigger adaptations after detecting violations in quality of service (QoS) requirements by just comparing observed QoS values to predefined thresholds wit...