Background: Case studies are regularly published in the software engineering literature, and guidelines for conducting case studies are available. Based on a perception that the label “case study” is assigned to studies that are not case studies, an investigation has been conducted. Objective: The aim was to investigate whether or not the label “case study” is correctly used in software engineering

Context: In the field of software engineering, the most complex and time consuming activity is fault-finding. Due to increasing size and complexity of software, there is a necessity of automated fault detection tool which can detect fault with minimal human intervention. A programmer spends a lot of time and effort on software fault localization. Various Spectrum Based Fault Localization (SBFL) techniques

Context: Agile software development methods advocate the importance of producing working software without comprehensive documentation. While this approach seems to suit the evolutionary nature of realistic software development for many applications, even including safety-critical systems, it faces two major challenges. One is the lack of a comprehensible specification for code evolution and future

Context Pricing is an essential element of software business strategy and tactics. Informed pricing decision-making requires the involvement of different stakeholders and comprehensive data analysis. Achieving both appears to be challenging, and pricing remains one of the most under-managed processes in the software business. Simultaneously, a coherent SaaS pricing body of knowledge and verified solutions

Background: Internet of Things (IoT) enables the interaction among objects to provide services to their users. Areas such as eHealth, smart energy, and smart buildings have been benefiting from the IoT potential. However, the development of IoT systems is still complex because it deals with a highly dynamic, volatile, and heterogeneous environment. These characteristics require discovering devices

Context: Software evolution and maintenance activities in today’s Free/Libre Open Source Software (FLOSS) rely primarily on information extracted from bug reports registered in bug tracking systems. Many studies point out that most bugs that adversely affect the user’s experience across versions of FLOSS projects are long-lived bugs. However, proposed approaches that support bug fixing procedures do

Context: Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These languages introduce new software-engineering challenges, such as: how to maintain the separation of concerns of the codebase? how to model the changing behaviors? how to verify the system behavior? and more. Objective:

Context: Previous studies proposed different kinds of approaches for class integration test order generation, and corresponding systems can be implemented based on these approaches. Such class integration test order generation systems can facilitate the process of software integration testing if they are implemented correctly. Objective: However, a test oracle problem exists in the class integration

Context: Mutual Information is an information theoretic measure designed to quantify the amount of similarity between two random variables ranging over two sets. In this paper, we adapt this concept and show how it can be used to select a good test suite to test from a Finite State Machine (FSM) based on a maximise diversity approach. Objective: The main goal of this paper is to use Mutual Information

Context: Mutation testing techniques, which attempt to construct a set of so-called mutants by seeding various faults into the software under test, have been widely used to generate test cases as well as to evaluate the effectiveness of a test suite. Its popularity in practice is significantly hindered by its high cost, majorly caused by the large number of mutants generated by the technique. Objective:

Context: Mutation analysis is a popular but costly approach to assess the quality of test suites. One recent promising direction in reducing costs of mutation analysis is to identify redundant mutations, i.e., mutations that are subsumed by some other mutations. A previous approach found redundant mutants manually through truth tables but it cannot be applied to all mutations. Another work derives

Context Requirement prioritisation (RP) is often used to select the most important system requirements as perceived by system stakeholders. RP plays a vital role in ensuring the development of a quality system with defined constraints. However, a closer look at existing RP techniques reveals that these techniques suffer from some key challenges, such as scalability, lack of quantification, insufficient

Context Risk event management has become strategic in Project Management, where uncertainties are inevitable. In this sense, the use of concepts of ubiquitous computing, such as contexts, context histories, and mobile computing can assist in proactive project management. Objective This paper proposes a computational model for the reduction of the probability of project failure through the prediction

Context: As a rapidly adopted architectural style in software engineering, Microservices Architecture (MSA) advocates implementing small-scale and independently distributed services, rather than binding all functions into one monolith. Although many initiatives have contributed to the quality improvement of microservices-based systems, there is still a lack of a systematic understanding of the Quality

Context: There are numerous textual notations and techniques that can be used in requirements engineering. Currently, practitioners make a choice without having scientific evidence regarding their suitability for given tasks. This uninformed choice may affect task performance. Objective: In this research, we investigate the adequacy of two well-known notations: use cases and user stories, as a starting

Context: The recent progress of deep learning has shown its promising learning ability in making sense of data, and many fields have utilized this learning ability to learn an effective model, successfully solving their problems. Fault localization has explored and used deep learning to server an aid in debugging, showing the promising results on fault localization. However, as far as we know, there

Context: Software security engineering provides the means to define, implement and verify security in software products. Software security engineering is performed by following a software security development life cycle model or a security capability maturity model. However, agile software development methods and processes, dominant in the software industry, are viewed to be in conflict with these

Context Tracing reports for software repositories have attracted many researchers. Most of them have focused on defect analysis and development processes in relation to open source programs. There exists a gap between open source and industrial software projects, which, in particular, relates to different schemes for creating software repositories and development schemes. This is especially true for

Context: Runtime software architectural models of self-adaptive systems are needed for making adaptation decisions in architecture-based self-adaptive systems. However, when these systems are distributed and highly dynamic, there is an added need to discover the system’s software architecture model at runtime. Current methods of runtime architecture discovery use a centralized approach, in which the

Context:Modern software development demands high levels of technical specialization. These conditions make IT companies focus on creating cross-functional teams, such as frontend, backend, and mobile developers. In this context, the success of software projects is highly influenced by the expertise of these teams in each field. Objective:In this paper, we investigate machine-learning based approaches

Context: The automatically produced crash reports are able to analyze the root of fault causing the crash (crashing fault for short) which is a critical activity for software quality assurance. Objective: Correctly predicting the existence of crashing fault residence in stack traces of crash report can speed up program debugging process and optimize debugging efforts. Existing work focused on the collected

Context: One of the time-consuming maintenance tasks is the localization of bugs especially in large software systems. Developers have to follow a tedious process to reproduce the abnormal behavior then inspect a large number of files. While several studies have been proposed for bugs localization, the majority of them are recommending classes/files as outputs which may still require high inspection

Context Rapidly-changing business requirements expect high business process flexibility that can be achieved using service oriented architecture (SOA). This requires enterprises to adopt SOA and assess their SOA adoption maturity to achieve continuous improvement. SOA realization demands service development with varying levels of granularity. Objectives The research aims to develop a methodical framework

Context Software testing is essential in software engineering to improve software reliability. One goal of software testing strategies is to detect faults faster. Dynamic Random Testing (DRT) strategy uses the testing results to guide the selection of test cases, which has shown to be effective in the fault detection process. Objective Previous studies have demonstrated that DRT is greatly affected

[Context] Software requirements specifications are the main point of reference in traditional software projects. Especially in large projects, these documents get read by multiple people, multiple times. Several guidelines and templates already exist to support writing a good specification. However, not much research has been done in investigating how to support the use of specifications and help readers

Context: Scheduling in cloud is complicated as a result of multi-tenancy. Diverse tenants have different requirements, including service functions, response time, QoS and throughput. Diverse tenants require different scheduling capabilities, resource consumption and competition. Multi-tenancy scheduling approaches have been developed for different service models, such as Software as a Service (SaaS)

Context: A Dynamically Adaptive System (DAS) supports runtime adaptations to handle changes in the operational environment. These adaptations can change the system’s structure or behavior and even the logic of its adaptation mechanism. However, these adaptations may insert defects, leading the system to fail at runtime. Objective: Aiming to identify these failures, testing can be executed to verify

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 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: 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: 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: 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: 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: 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 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. A widely adopted methodology, agile software development provides enhanced flexibility to actively adjust a project scope. In agile teams, particularly in distributed environment, developers interact, manage requirements knowledge, and coordinate primarily in online collaboration tools. Developer conversations become invaluable sources to track and understand developers’ interactions around

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: Research collaborations between software engineering industry and academia can provide significant benefits to both sides, including improved innovation capacity for industry, and real-world environment for motivating and validating research ideas. However, building scalable and effective research collaborations in software engineering is known to be challenging. While such challenges can

Context Tool support for business process management (BPM) is improving more and more. Often, machine learning techniques are used to recognize certain execution patterns, to optimize workflows and to observe or predict processes. Frequently, many organisations cannot meet the fundamental prerequisites of machine learning methods since less data is recorded and therefore available for analysis. Most

Context: The higher availability of software usage data and the influence of the Lean Startup led to the rise of experimentation in software engineering, a new approach for development based on experiments to understand the user needs. In the models proposed to guide this approach, the first step is generally to identify, prioritize, and specify the hypotheses that will be tested through experimentation

Context: Mobile applications (apps) have become deeply personal, constantly demanding access to privacy-sensitive information in exchange for more personalized user experiences. Such privacy-invading practices have generated major multidimensional privacy concerns among app users. Objective: The research on mobile app privacy has experienced rapid growth over the past decade. This line of research

Context: Clustering algorithms, as a modularization technique, are used to modularize a program aiming to understand large software systems as well as software refactoring. These algorithms partition the source code of the software system into smaller and easy-to-manage modules (clusters). The resulting decomposition is called the software system structure (or software architecture). Due to the NP-hardness

Context: In-app advertising is the primary source of revenue for many mobile apps. The cost of advertising (ad cost) is non-negligible for app developers to ensure a good user experience and continuous profits. Previous studies mainly focus on addressing the hidden performance costs generated by ads, including consumption of memory, CPU, data traffic, and battery. However, there is no research on analyzing

Context : A plethora of models are available for open-source software (OSS) usability evaluation. However, these models lack consensus between scholars as well as standard bodies on a specific set of usability evaluation criteria. Retaining irrelevant criteria and omitting essential ones will mislead the direction of the usability evaluation. Objective : This study introduces a three-step method to

Context: Nowadays, the hype around artificial intelligence is at its absolute peak. Large amounts of data are collected every second of the day and a variety of tools exists to enable easy analysis of data. In practice, however, making meaningful use of it is way more challenging. For instance, affected stakeholders often struggle to specify their information needs and to interpret the results of such

Context: Various types of artifacts (requirements, source code, test cases, documents, etc.) are produced throughout the lifecycle of a software. These artifacts are connected with each other via traceability links that are stored in modern application lifecycle management repositories. Throughout the lifecycle of a software, various types of changes can arise in any one of these artifacts. It is important

Context The reuse of software design has been an important issue of software reuse. UML class diagrams are widely applied in software design and has become DE factor standard. As a result, the reuse of UML class diagrams has received more attention. With the increasing number of class diagrams stored in reuse repository, their retrieval becomes a time-consuming job. The clustering can narrow down retrieval

Context: Typically, search-based test data generation methods search on a population of program input values. Program input values can be regarded as solutions to underlying path constraints over program input parameters. One way to discover these path constraints is to use the symbolic execution method. Search-based methods attempt to find input values which are solutions to these path constraints

Context: Over the last decade, Agile methods have changed the software development process in an unparalleled way and with the increasing popularity of Big Data, optimizing development cycles through data analytics is becoming a commodity. Objective: Although a myriad of research exists on software analytics as well as on Agile software development (ASD) practice on itself, there exists no systematic

Context: Clone and Own (CaO) is a widespread approach to generate new software products from existing software products by adding small changes. The Software Product Line (SPL) approach addresses the development of families of products with similar features, moving away from the production of isolated products. Despite the popularity of both approaches, no experiment has yet compared them directly

Context: Bug localization, which locates suspicious snippets related to the bugs mentioned in the bug reports, is time-consuming and laborious. Many automatic bug localization methods have been proposed to speed up the process of bug fixing and reduce the burden on developers. However, these methods have not fully utilized the intra-relations and inter-relations among the bug reports and the source

Context: As companies have become large users of Open Source Software, it is important that they feel comfortable in their Open Source strategies. One of the critical differences between Open Source and Proprietary Software is the communication networks. Objective: This paper tries to set a base for understanding how open source teams are structured and how they change. This is vital to understanding

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: 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: 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: 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