Context: Cross-project defect prediction applies to the scenarios that the target projects are new projects. Most of the previous studies tried to utilize the training data from other projects (i.e., the source projects). However, metrics used by practitioners to measure the extracted program modules from different projects may not be the same, and performing heterogeneous defect prediction (HDP) is

Software Engineering and Advanced Applications (SEAA) is a long-standing international forum for researchers, practitioners, and students to present and discuss the latest innovations, trends, experiences, and concerns in the field of Software Engineering and Advanced Applications in information technology for software-intensive systems. In this special issue, we present a selection of papers which

Context: Generally, there are more non-defective instances than defective instances in the datasets used for software defect prediction (SDP), which is referred to as the class imbalance problem. Oversampling techniques are frequently adopted to alleviate the problem by generating new synthetic defective instances. Existing techniques generate either near-duplicated instances which result in overgeneralization

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 applications (apps) and rely on Sapienz, a state-of-the-art

Context: There is a growing demand for information on how IT companies look for candidates to their open positions. Objective: This paper investigates which hard and soft skills are more required in IT companies by analyzing the description of 20,000 job opportunities. Method: We applied open card sorting to perform a high-level analysis on which types of hard skills are more requested. Further, we

Context: In integration testing, the order in which classes are integrated and tested is significant for the construction of test stubs. With the existing approaches, it is usually difficult to generate the sub-optimal test orders for real applications, which have large numbers of classes. Objective: There exist moderately large numbers of classes in software systems, which is one of the main factors

Context: The prevalent application of Deep Learning (DL) models has raised concerns about their reliability. Due to the data-driven programming paradigm, the quality of test datasets is extremely important to gain accurate assessment of DL models. Recently, researchers have introduced mutation testing into DL testing, which applies mutation operators to generate mutants from DL models, and observes

Context Exploiting software development related data from software-development intensive organizations to support tactical and strategic decision making is a challenge. Combining data-driven approaches with expert knowledge has been highlighted as a sensible approach for leading software-development intensive organizations to rightful decision-making improvements. However, most of the existing proposals

Context: Debugging is the most challenging and time consuming task in software development. However, it is not properly integrated in the software development cycle, because the result of so much effort is not available in further iterations of the cycle, and the debugging process itself does not benefit from the outcome of other phases such as testing. Objective: We propose to integrate debugging

Context: Leveraging machine learning techniques to address feature location on models has been gaining attention. Machine learning techniques empower software product companies to take advantage of the knowledge and the experience to improve the performance of the feature location process. Most of the machine learning-based works for feature location on models report the machine learning techniques

Context Making architectural decisions is a crucial task but also very difficult, considering the scope of the decisions and their impact on quality attributes. To make matters worse, architectural decisions need to combine both technical and business factors, which are very dissimilar by nature. Objectives We provide a cost-benefit approach and supporting tooling that treats architectural decisions

Context: Software testing is a pivotal activity in the development of high-quality software. As software is evolving through its life cycle, the need for a fault-revealing criterion assessing the effectiveness of the test suite grows. Over the years, researchers have proposed coverage-based criteria, including statement and branch coverage, to solve this issue. In literature, the effectiveness of such

Context: Quality Assessment (QA) of reviewed literature is paramount to a Systematic Literature Review (SLR) as the quality of conclusions completely depends on the quality of selected literature. A number of researchers in Software Engineering (SE) have developed a variety of QA instruments and also reported their challenges. We previously conducted a tertiary study on SLRs with QA from 2004 to 2013

Context The changes that are taking place with respect to environmental sensitivity are forcing organizations to adopt a new approach to this problem. Implementing sustainability initiatives has become a priority for the social and environmental awareness of organizations that want to stay ahead of the curve. One of the business areas that has, more than others, proven to be a vital asset and a potential

Context:Latent Dirichlet Allocation (LDA) has been successfully used in the literature to extract topics from software documents and support developers in various software engineering tasks. While LDA has been mostly used with default settings, previous studies showed that default hyperparameter values generate sub-optimal topics from software documents. Objective: Recent studies applied meta-heuristic

Context:Deep Neural Networks (DNN) have shown great promise in various domains, for example to support pattern recognition in medical imagery. However, DNNs need to be tested for robustness before being deployed in safety critical applications. One common challenge occurs when the model is exposed to data samples outside of the training data domain, which can yield to outputs with high confidence despite

Context: Code changes to software occur due to various reasons such as bug fixing, new feature addition, and code refactoring. Change intents have been studied for years to help developers understand the rationale behind code commits. However, in most existing studies, the intent of the change is rarely leveraged to provide more specific, context aware analysis. Objective: In this paper, we present

Context: Creativity is one of the essential ingredients in successful software engineering. However, majority of the work related to creativity in software engineering has focused on creativity in requirement engineering. Furthermore, there are very few studies that examine programmer creativity and the impact of individual and contextual factors on it. Objective: The objective of the study is to analyze

Context : Reporting usability defects is a critical part of improving software. Accurately classifying these reported usability defects is critical for reporting, understanding, triaging, prioritizing and ultimately fixing such defects. However, existing usability defect classification taxonomies have several limitations when used for open source software (OSS) development. This includes incomplete

Context: The adoption of Software Product Line Engineering (SPLE) is usually only based on its theoretical benefits instead of empirical evidences. In fact, there is no work that synthesizes the empirical studies on SPLE. This makes it difficult for researchers to base their contributions on previous works validated with an empirical strategy. Objective: The objective of this work is to discover and

Context Systematic Literature Reviews (SLRs) are frequently used to synthesize evidence in Software Engineering (SE), however replicating and keeping SLRs up-to-date is a major challenge. The activity of studies selection in SLR is labor intensive due to the large number of studies that must be analyzed. Different approaches have been investigated to support SLR processes, such as: Visual Text Mining

Context Demonstrating high reliability and safety for safety-critical systems (SCSs) remains a hard problem. Diverse evidence needs to be combined in a rigorous way: in particular, results of operational testing with other evidence from design and verification. Growing use of machine learning in SCSs, by precluding most established methods for gaining assurance, makes evidence from operational testing

Context: Continuous Integration (CI) is a common practice in modern software development and it is increasingly adopted in the open-source as well as the software industry markets. CI aims at supporting developers in integrating code changes constantly and quickly through an automated build process. However, in such context, the build process is typically time and resource-consuming which requires

Context The cornerstones of technical debt (TD) are two concepts borrowed from economics: principal and interest. Although in economics the two terms are related, in TD there is no study on this direction so as to validate the strength of the metaphor. Objective We study the relation between Principal and Interest, and subsequently dig further into the ‘ingredients’ of each concept (since they are

Minimizing the resource wastage reduces the energy cost of operating a data center, but may also lead to a considerably high resource overcommitment affecting the Quality of Service (QoS) of the running applications. The effective tradeoff between resource wastage and overcommitment is a challenging task in virtualized Clouds and depends on the allocation of virtual machines (VMs) to physical resources

Context: Even if evolutionary coupling between files has been widely used for various studies, such as change impact analysis, defect prediction, and software design analysis etc., there has little work focusing on studying the linkage among evolutionary coupled files. Objective: In this paper, we propose a novel model, evolutionary clique (EClique), to characterize evolutionary coupled files as maintainable

Context. Among the static analysis tools available, SonarQube is one of the most used. SonarQube detects Technical Debt (TD) items—i.e., violations of coding rules—and then estimates TD as the time needed to remedy TD items. However, practitioners are still skeptical about the accuracy of remediation time estimated by the tool. Objective. In this paper, we analyze both diffuseness of TD items and accuracy

Context: Training deep learning models for code readability classification requires large datasets of quality pre-labeled data. However, it is almost always time-consuming and expensive to acquire readability data with manual labels.Objective: We thus propose to introduce data augmentation approaches to artificially increase the size of training set, this is to reduce the risk of overfitting caused

Code commenting is a common programming practice of practical importance to help developers review and comprehend source code. There are two main types of code comments for a method: header comments that summarize the method functionality located before a method, and block comments that describe the functionality of the code snippets within a method. Inspired by the effectiveness of deep learning techniques

Context: The development of software systems is a complex activity because of its nature and the management of its construction. It is challenging to create and follow a plan. Moreover, budget overrun is a common consequence of this situation. Agile methods, like Scrum, help to mitigate this problem using incremental and iterative development. Agile methods jump start new developments, but it is difficult

Context Modern software systems employ large IT infrastructures hosted in on-premise clouds or using “rented” cloud resources from specific vendors. The unifying force across any cloud strategy is incremental product and application improvement against conservation of those resources. This is where monitoring of cloud applications becomes a key asset Objective To shed light over the status of monitoring

Context:Kotlin is a new programming language representing an alternative to Java; they both target the same JVM and can safely coexist in the same application. Kotlin is advertised as capable to solve several known limitations of Java. Recent surveys show that Kotlin achieved a relevant diffusion among Java developers. Goal:We planned to empirically assess a few typical promises of Kotlin w.r.t. known

Context Search-Based Software Engineering (SBSE) is the research field where Software Engineering (SE) problems are modelled as search problems to be solved by search-based techniques. The Symposium on Search Based Software Engineering (SSBSE) is the premier event on SBSE, which had its 11th edition in 2019. Objective In order to better understand the characteristics and evolution of papers published

Background: Developing and maintaining large scale machine learning (ML) based software systems in an industrial setting is challenging. There are no well-established development guidelines, but the literature contains reports on how companies develop and maintain deployed ML-based software systems. Objective: This study aims to survey the literature related to development and maintenance of large

Context Program slicing is very useful in program analysis and software engineering. It computes the slice, which is a part of program and contains all the statements related to the given slicing criterion. The more accurate a slicing technique could be, the smaller the slice is. Objective This paper aims to improve the current slicing accuracy for object-oriented programs. The slicing accuracy is

Context: A Software Product Line (SPL) can express the variability of a system through the specification of configuration options. Evaluating performance characteristics, such as the system response time and resource utilization, of a software product is challenging, even more so in the presence of uncertain values of the attributes. Objective: The goal of this paper is to automate the generation of

Context – During the development of complex software systems, programmers look for external resources to understand better how to use specific APIs and to get advice related to their current tasks. Stack Overflow provides developers with a broader insight into API usage as well as useful code examples. Given the circumstances, tools and techniques for mining Stack Overflow are highly desirable. Objective

Context Microservices must be composed to provide users with complex and elaborated functionalities. It seems that the decentralized nature of microservices makes a choreography style more appropriate to achieve such cooperation, where lighter solutions based on asynchronous events are generally used. However, a microservice composition based on choreography distributes the flow logic of the composition

Context Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE. Objective The objective of this paper is to propose guidelines on how to best search for evidence

Context Crowdsourced software testing (CST) refers to the use of crowdsourcing techniques in the domain of software testing. CST is an emerging area with its applications rapidly increasing in the last decade. Objective A comprehensive review on CST has been conducted to determine the current studies aiming to improve and assess the value of using CST as well as the challenges identified by these evaluation

Context Code reuse, generally done through software packages, allows developers to reduce time-to-market and improve code quality. The npm ecosystem is a Node.js package management system which contains more than 700 K Node.js packages and to help developers find high-quality packages that meet their needs, npms developed a search engine to rank Node.js packages in terms of quality, popularity, and

Context With the ever-increasing evolution of software systems, their architecture is subject to frequent changes due to multiple reasons, such as new requirements. Appropriate architectural changes driven by non-functional requirements are particularly challenging to identify because they concern quantitative analyses that are usually carried out with specific languages and tools. A considerable number

Context Businesses today must collaborate in a coordinated fashion. To collaborate, they must align their business processes and IT by complying to a common reference architecture. The common reference architecture that addresses their specific collaboration requirements is generally an adaptation of an existing generic reference architecture. However, a design framework for adapting reference architectures

Context Software defect prediction is an important technique that can help practitioners allocate their quality assurance efforts. In recent years, just-in-time (JIT) defect prediction has attracted considerable interest, as it enables developers to identify risky changes at check-in time. Objective Many studies have conducted research from supervised and unsupervised perspectives. A model that does

Context There are several methods to elicit requirements through interviews between an end-user and a team of software developers. The choice of the best method in this context is usually on subjective developers’ preferences instead of objective reasons. There is a lack of empirical evaluations of methods to elicit requirements that help developers to choose the most suitable one. Objective This paper

Context Previous research found that the performance of a team not only depends on the team personality composition, but also on the interactive effects of team climate. Although investigation on personalities associated with software development has been an active research area over the past decades, there has been very limited research in relation to team climate. Objective Our study investigates

Context There are many duplicate bug reports in the semi-structured software repository of various software bug triage systems. The duplicate bug report detection (DBRD) process is a significant problem in software triage systems. Objective The DBRD problem has many issues, such as efficient feature extraction to calculate similarities between bug reports accurately, building a high-performance duplicate

Context Critical systems in application domains such as automotive, railway, aerospace, and healthcare are required to comply with safety standards. The understanding of the safety compliance needs specified in these standards can be difficult from their text. A possible solution is to use models. Objective We aim to evaluate the use of models to understand safety compliance needs. Method We have studied

Context In host-based anomaly detection, feature extraction on the system call traces is important to build an effective anomaly detection model. Different kinds of feature extraction methods are recently proposed and most of them aim at preserving the positional information of the system calls within a trace. These extracted features are generally named from system calls, therefore, cannot be used

Context Recent advancements in the applicability of neural networks across a variety of fields, such as computer vision, natural language processing and others, have re-sparked an interest in program induction methods. (Kitzelman [1], Gulwani et al. [2] or Kant [3].) Problem When performing a program induction task, it is not feasible to search across all possible programs that map an input to an output

Context Software development incorporates numerous people with diverse expertise and expectations. This makes conflict a common phenomenon in software development. Besides human causes, many conflicts in software development root in the tools and processes. Moreover, the growing role of software in any type of system is increasing the heterogeneity in software projects. The number and variety of tools

Context Code refactoring was conceived for enhancing code structures, often in terms of internal quality attributes such as cohesion and coupling. Developers may have to apply multiple refactoring operations to achieve the expected enhancement. Re-refactoring occurs whenever one or more refactoring operations are performed on a previously refactored code element. The literature often assumes each single

Context: Cyber-Physical Systems (CPSs) are gradually and widely introducing autonomous capabilities into everything. However, human participation is required to accomplish tasks that are better performed with humans (often called human-in-the-loop). In this way, human-in-the-loop solutions have the potential to handle complex tasks in unstructured environments, by combining the cognitive skills of

Context: With the current high trends of deploying and using web services in practice, effective techniques for maintaining high quality of Service are becoming critical for both service providers and subscribers/users. Service providers want to predict the quality of service during early stages of development before releasing them to customers. Service clients consider the quality of service when

Context Maintenance activities cannot be completed without locating the set of software artifacts that realize a particular feature of a software system. Manual Feature Location (FL) is widely used in industry, but it becomes challenging (time-consuming and error prone) in large software repositories. To reduce manual efforts, automated FL techniques have been proposed. Research efforts in FL tend

Context The purpose of software restructuring, or refactoring, is to improve software quality and developer productivity. Objective Prior studies have relied mainly on static and dynamic analysis of code to detect and recommend refactoring opportunities, such as code smells. Once identified, these smells are fixed by applying refactorings which then improve a set of quality metrics. While this approach

Context Millions of software developers are using open-source software (OSS) platforms to host their code and collaborate with each other. They possess different programming skills, styles, and preferences, etc., and it is important to understand them for making collaborative decisions such as programming task assignment. Existing OSS platforms do not provide sufficient information about developers

Context To reduce manual effort of extracting test cases from natural-language requirements, many approaches based on Natural Language Processing (NLP) have been proposed in the literature. Given the large amount of approaches in this area, and since many practitioners are eager to utilize such techniques, it is important to synthesize and provide an overview of the state-of-the-art in this area. Objective