Natural Language (NL) is the root cause of ambiguity in the SRS document. The quality of the software development process can be improved by mitigating the risk with the use of semantically controlled representation. A possible solution to handle ambiguity can be the use of a mathematical formal logic representation in place of NL to capture software requirements. However, the use of formal logic is

Information technology outsourcing (ITO) is a USD multi-trillion industry. There is growing competition among ITO service providers to improve their service deliveries. Natural language processing (NLP) is a technique, which can be leveraged to gain a competitive advantage in the ITO industry. This paper explores the information security implications of using NLP in ITO. First, it explores the use

Android framework-specific app crashes are hard to debug. Indeed, the callback-based event-driven mechanism of Android challenges crash localization techniques that are developed for traditional Java programs. The key challenge stems from the fact that the buggy code location may not even be listed within the stack trace. For example, our empirical study on 500 framework-specific crashes from an open

Correlated quality metrics extracted from a source code repository can be utilized to design a model to automatically predict defects in a software system. It is obvious that the extracted metrics will result in a highly unbalanced data, since the number of defects in a good quality software system should be far less than the number of normal instances. It is also a fact that the selection of the best

Software reliability models are one of the most generally used mathematical tool for estimation of reliability, failure rate and number of remaining faults in the software. Existing software reliability models are designed to follow waterfall software development life cycle process. These existing models do not take advantage of iterative software development process. In this paper, a new failure rate

Automatic recovery of traceability between software artifacts may promote early detection of issues and better calculate change impact. Information Retrieval (IR) techniques have been proposed for the task, but they differ considerably in input parameters and results. It is difficult to assess results when those techniques are applied in isolation, usually in small or medium-sized software projects

Mobile applications and game development are attractive fields in software engineering. Despite the advancement of programming languages and integrated development environments, there have always been many challenges for software and mobile game developers. Model-Driven Engineering (MDE) is a software engineering methodology that applies software modeling languages for modeling the problem domain.

With the generalization of mobile devices and Web applications, GUI frameworks evolve at a fast pace: JavaFX replaced Swing, Angular 8 replaced Angular 1.4 which had replaced Google Web Toolkit (GWT). This situation forces organizations to migrate their applications to modern frameworks regularly so they do not become obsolete. There has been research in the past on automatic GUI migration. However

Open source software development (OSS) team members often need to figure out how to initiate a collaboration with a new remote collaborator. An inappropriate strategy could lead to failures in developing cooperation. In this paper, we propose an approach and corresponding intelligent system called IIAG (Initial Interaction Assistant based on Game theory analytics), which identifies and advises its

It is vitally important to fix quality issues in security-critical code as they may be sources of vulnerabilities in the future. These quality issues may increase the attack surface if they are not quickly refactored. In this paper, we use the history of vulnerabilities and security bug reports along with a set of keywords to automatically identify a project’s security-critical files based on its source

To guide software development, the estimation of the impact of decision making on the development process can be helpful in planning. For this estimation, often prediction models are used which can be learned from project data. In this paper, an approach for the usage of agent-based simulation for the prediction of software evolution trends is presented. The specialty of the proposed approach lies

In recent years, the number of smartphone users has increased dramatically. These users download millions of apps and use them for various services. Due to the significant demand for mobile apps, developers often seek faster development methods and more effective tools and techniques to generate these apps. Many of these apps are location-based apps in which users receive services based on their geographical

Software development teams need to deal with several open reports of critical bugs to be addressed urgently and simultaneously. The management of these bugs is a complex problem due to the limited resources and the deadlines-pressure. Most of the existing studies treated bug reports in isolation when assigning them to developers. Thus, developers may spend considerable cognitive efforts moving between

Software defects are well-known in software development and might cause several problems for users and developers aside. As a result, researches employed distinct techniques to mitigate the impacts of these defects in the source code. One of the most notable techniques focuses on defect prediction using machine learning methods, which could support developers in handling these defects before they are

Analyzing real-world software is challenging due to complexity of the software frameworks or APIs they depend on. In this paper, we present a tool, PROMPT, that facilitates the analysis of software components using API model guided symbolic execution. PROMPT has a specification component, PROSE, that lets users define an API model, which consists of a set of data constraints and life-cycle rules that

Modern Code review is one of the most critical tasks in software maintenance and evolution. A rigorous code review leads to fewer bugs and reduced overall maintenance costs. Most existing studies focus on automatically identifying the most qualified reviewers, based on their expertise, to review pull-up requests. However, the management of code reviews is a complex problem in practice due to a project’s

REST APIs are gaining a tremendous attraction in industry and a growing usage in mobile platforms. They are well suited for providing content to apps running on small devices, like smartphones and tablets. Several research works studied REST APIs development practices for mobile apps. However, little is known about how Android apps use/consume these APIs in practice. Consequently, we propose a multi-dimensional

Sharing Economy apps, such as Uber, Airbnb, and TaskRabbit, have generated a substantial consumer interest over the past decade. The unique form of peer-to-peer business exchange these apps have enabled has been linked to significant levels of economic growth, helping people in resource-constrained communities to build social capital and move up the economic ladder. However, due to the multidimensional

Stakeholders of configurable systems are often interested in knowing how configuration options influence the performance of a system to facilitate, for example, the debugging and optimization processes of these systems. Several black-box approaches can be used to obtain this information, but they either sample a large number of configurations to make accurate predictions or miss important performance-influencing

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

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

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

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,

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

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

This section of the Automated Software Engineering journal is devoted to the theme of Artificial Intelligence for Requirements Engineering. The synergies between these two domains bear the potential to improve requirements quality, among other things through automated models, natural language processing, machine learning, reasoning about uncertainties and ambiguities, knowledge acquisition and representation

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

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

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

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

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

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

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

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 change

Collaboration with other people is a major theme in the information-seeking process. However, most existing works that address the location of features during the maintenance or evolution of software do not support collaboration, or they are focused on code as the main software artifact. Hence, collaborative feature location in models has not enjoyed much attention to date. In this work, we address

Cloud computing is a rapidly growing paradigm in software engineering that offers different services. The hybrid cloud is the best choice for the enterprise to benefit by taking resources on lease from the public cloud only if private cloud resources are not sufficient. However, the key is how to provide better cloud services and improve software performance in the hybrid cloud for software engineers

Faults in spreadsheets can represent a major risk for businesses. To minimize such risks, various automated testing and debugging approaches for spreadsheets were proposed. In such approaches, often one main assumption is that the spreadsheet developer is able to indicate if the outcomes of certain calculations correspond to the intended values. This, however, might require that the user performs calculations

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

As software systems grow in size and complexity, the process of configuring them to meet individual needs becomes more and more challenging. Users, especially those that are new to a system, are faced with an ever increasing number of configuration possibilities, making the task of choosing the right one more and more daunting. However, users are rarely alone in using a software system. Crowds of other

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

AbstractIn software testing, different testers focus on different aspects of the software such as functionality, performance, design, and other attributes. While many tools and coverage metrics exist to support testers at the code level, not much support is targeted for testers who want to inspect the output of a program such as a dynamic web application. To support this category of testers, we propose

Welcome to the special issue of the Automated Software Engineering journal. Software now flourishes at many scales, from giant service-oriented cloud systems to tiny embedded IOT devices. Automation approaches for software design, construction, verification, and deployment are now regularly applied by practitioners to build scalable and robust software systems. As software engineering researchers,

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 the

It is well recognized that traceability links between software artifacts provide crucial support in comprehension, efficient development, and effective management of a software system. However, automated traceability systems to date have been faced with two major open research challenges: how to extract traceability links with both high precision and high recall, and how to efficiently visualize links

Formal verification has advanced to the point that developers can verify the correctness of small, critical modules. Unfortunately, despite considerable efforts, determining if a “verification” verifies what the author intends is still difficult. Previous approaches are difficult to understand and often limited in applicability. Developers need verification coverage in terms of the software they are

Copy-paste-modify is a form of software reuse in which developers explicitly duplicate source code. This duplicated source code, amounting to a code clone, is adapted for a new purpose. Copy-paste-modify is popular among software developers, however, empirical evidence shows that it complicates software maintenance and increases the frequency of bugs. To allow developers to use copy-paste-modify without

Visual contracts model the operation of components or services by pre- and post-conditions formalised as graph transformation rules. They provide a precise intuitive notation to support testing, understanding and analysis of software. Their detailed specification of internal data states and transformations, referred to as deep behavioural modelling, is an error-prone activity. In this paper we propose

Complex software-intensive systems are often described as systems of systems (SoS) due to their heterogeneous architectural elements. As SoS behavior is often only understandable during operation, runtime monitoring is needed to detect deviations from requirements. Today, while diverse monitoring approaches exist, most do not provide what is needed to monitor SoS, e.g., support for dynamically defining

Software information sites such as StackOverflow and Freeecode enable information sharing and communication for developers around the world. To facilitate correct classification and efficient search, developers need to provide tags for their postings. However, tagging is inherently an uncoordinated process that depends not only on developers’ understanding of their own postings but also on other factors

This work develops a static analysis to create a model of the behavior of an Android application’s GUI. We propose the window transition graph (WTG), a model representing the possible GUI window sequences and their associated events and callbacks. A key component and contribution of our work is the careful modeling of the stack of currently-active windows, the changes to this stack, and the effects

An increasingly used method for the engineering of software systems with strict quality-of-service (QoS) requirements involves the synthesis and verification of probabilistic models for many alternative architectures and instantiations of system parameters. Using manual trial-and-error or simple heuristics for this task often produces suboptimal models, while the exhaustive synthesis of all possible

Self-adaptation improves the resilience of software-intensive systems, enabling them to adapt their structure and behavior to run-time changes (e.g., in workload and resource availability). Many of these approaches reason about the best way of adapting by synthesizing adaptation plans online via planning or model checking tools. This method enables the exploration of a rich solution space, but optimal

AbstractThe paper proposes QoS based service allocation optimization in hybrid mobile cloud. The optimization formulation of the hybrid mobile cloud utility adopts a network utility maximization framework. The proposed hybrid cloud service allocation framework leads to a decomposition of the overall hybrid mobile cloud system problem into a separate problem for mobile user and one for the hybrid cloud

To identify defects and security risks in many real-world applications structured test cases, including test cases structured as trees are required. A simple approach is to generate random trees as test cases [random testing (RT)]; however, the RT approach is not very effective. In this work, we investigate and extend the black-box tree test case generation approaches. We introduce a novel model to

Software systems are often released without formal specifications. To deal with the problem of lack of and outdated specifications, rule-based specification mining approaches have been proposed. These approaches analyze execution traces of a system to infer the rules that characterize the protocols, typically of a library, that its clients must obey. Rule-based specification mining approaches work

Argument-based assurance cases, often represented and organized using graphical argument structures, are increasingly being used in practice to provide assurance to stakeholders, e.g., regulatory authorities, that a system is acceptable for its intended use with respect to dependability and safety concerns. In general, comprehensive system-wide assurance arguments aggregate a substantial amount of

Software applications often receive a large number of enhancement requests that suggest developers to fulfill additional functions. Such requests are usually checked manually by the developers, which is time consuming and tedious. Consequently, an approach that can automatically predict whether a new enhancement report will be approved is beneficial for both the developers and enhancement suggesters