Algorithm selection is the task of choosing an algorithm from a given set of candidate algorithms when faced with a particular problem instance. Algorithm selection via machine learning (ML) has recently been successfully applied for various problem classes, including computationally hard problems such as SAT. In this paper, we study algorithm selection for software validation, i.e., the task of choosing

For the systematic development of logical, message-driven architectures, automating parallel decomposition of software components is important to achieve efficient modular and parallel system development. During development, monolithic components that realize multiple independent concerns need to be decomposed to obtain a higher quality architecture of cohesively encapsulated, better comprehensive

Model transformations play an important role in the evolution of systems in various fields such as healthcare, automotive and aerospace industry. Thus, it is important to check the correctness of model transformation programs. Several approaches have been proposed to generate test cases for model transformations based on different coverage criteria (e.g., statements, rules, metamodel elements, etc

Recommendation systems are a key part of almost every modern consumer website. Recommender systems include techniques to filter, explore and rank a huge amount of information and items according to the user’s current interests, and the similarity among users and items. Designing and implementing a recommender system usually requires high programming and machine learning skills. To alleviate these processes

Semantic history slicing solves the problem of extracting changes related to a particular high-level functionality from software version histories. State-of-the-art techniques combine static program analysis and dynamic execution tracing to infer an over-approximated set of changes that can preserve the functional behaviors captured by a test suite. However, due to the conservative nature of such techniques

To improve code search, many query expansion (QE) approaches use APIs or crowd knowledge for expanding a query. However, these approaches may sometimes negatively impact the retrieval performance. This is because they can’t distinguish the relevant terms from the irrelevant ones among a large set of candidate expansion terms and expand a query with irrelevant terms. In this paper, we propose QREC,

Runtime verification can be used to find bugs early, during software development, by monitoring test executions against formal specifications (specs). The quality of runtime verification depends on the quality of the specs. While previous research has produced many specs for the Java API, manually or through automatic mining, there has been no large-scale study of their bug-finding effectiveness. Our

Traces of user interactions with a software system, captured in production, are commonly used as an input source for user experience testing. In this paper, we present an alternative use, introducing a novel approach of modeling user interaction traces enriched with another type of data gathered in production—software fault reports consisting of software exceptions and stack traces. The model described

Heterogeneous defect prediction (HDP) refers to predicting defect-prone software modules in one project (target) using heterogeneous data collected from other projects (source). Recently, several HDP methods have been proposed. However, these methods do not sufficiently incorporate the two characteristics of the defect data: (1) data could be linear inseparable, and (2) data could be highly imbalanced

During requirements elicitation, different stakeholders with diverse backgrounds and skills need to effectively communicate to reach a shared understanding of the problem at hand. Linguistic ambiguity due to terminological discrepancies may occur between stakeholders that belong to different technical domains. If not properly addressed, ambiguity can create frustration and distrust during requirements

The B-method, which provides automated verification for the design of software systems, still requires users to manually repair faulty models. This paper proposes B-repair, an approach that supports automated repair of faulty models written in the B formal specification language. After discovering a fault in a model using the B-method, B-repair is able to suggest possible repairs for the fault, estimate

Sociotechnical systems (STSs) are defined by the interaction between technical systems, like software and machines, and social entities, like humans and organizations. The entities within an STS are autonomous, thus weakly controllable, and the environment where the STS operates is highly dynamic. As a result, the design artifacts that represent the requirements of an STS, such as requirements models

Modern systems are being developed by integrating multiple products within/across product lines that communicate with each other through information networks. Runtime behaviors of such systems are related to product configurations and information networks. Cost-effectively supporting Product Line Engineering (PLE) of such systems is challenging mainly because of lacking the support of automation of

Modern software applications store their data in remote cloud servers. Users interact with these applications using web browsers or thin clients running on mobile devices. A key concern for these applications is the correctness of the actions that update the data store, which are triggered by user requests. Considering that modern applications store and manage data for millions (even billions) of users

Service interface is a critical component in a service-oriented architecture (SOA). As first-class design artifact, a service interface should be properly designed to provide best practice of third-party reuse. However, a very common bad service design practice in existing SOAs is to place semantically unrelated operations implementing several abstractions in a single interface. Poorly designed service

To ensure security and privacy, Android employs a permission mechanism which requires developers to explicitly declare the permissions needed by their applications (apps). Users must grant those permissions before they install apps or during runtime. This mechanism protects users’ private data, but also imposes additional requirements on developers. For permission declaration, developers need knowledge

In this paper, we present the first full regions-and-effects inference algorithm for explicitly parallel fork-join programs. We infer annotations equivalent to those in Deterministic Parallel Java (DPJ) for type-safe C++ programs. We chose the DPJ annotations because they give the strongest safety guarantees of any existing concurrency-checking approach we know of, static or dynamic, and it is also

Automotive systems provide sophisticated functionality and are controlled by networked electronic control units (ECUs). Nowadays, software engineers use component-based development approaches to develop their software. Moreover, software components have to be allocated to ECUs to be executed. Engineers have to cope with topology-, software-, and timing dependencies and memory-, scheduling-, and routing

Abstract Understanding variability is essential to allow the configuration of software systems to diverse requirements. Variability-aware program analysis techniques have been proposed for analyzing the space of program variants. Such techniques are highly beneficial, e.g., to determine the potential impact of changes during maintenance. This article presents an interprocedural and configuration-aware

Abstract Recent development methodologies from the industry and the academia for complex real-time systems define a stage in which system functions are deployed onto an execution platform. The deployment consists of the placement of functions on a distributed network of nodes, the partitioning of functions in tasks and the scheduling of tasks and messages. In this paper, we present two approaches towards