Software defect prediction is an effective approach to save testing resources and improve software quality, which is widely studied in the field of software engineering. The effort-aware just-in-time software defect prediction (JIT-SDP) aims to identify defective software changes in limited software testing resources. Although many methods have been proposed to solve the JIT-SDP, the effort-aware prediction

Mutation testing is a successful and powerful technique, specifically designed for injecting the artificial faults. Although it is effective at revealing the faults, test suite assessment and its reduction, however, suffer from the expense of executing a large number of mutants. The researchers have proposed different types of cost reduction techniques in the literature. These techniques highly depend

Mutation testing is well known as one of the most effective approaches to create test cases, which can detect software faults. However, its drawback is the low scalability — if no special attention is given to improve efficiency — that directly affects its application in practice. This paper shows a replication study focused on emphasizing evidence in which the use of distributed processing structures

As a quantum counterpart of labeled transition system (LTS), quantum labeled transition system (QLTS) is a powerful formalism for modeling quantum programs or protocols, and gives a categorical understanding for quantum computation. With the help of quantum branching monad, QLTS provides a framework extending some ideas in non-deterministic or probabilistic systems to quantum systems. On the other

In the world of the Internet of Things (IoT), heterogeneous systems and devices need to be connected and exchange data with others. How data exchange can be automatically realized becomes a critical issue. An information model (IM) is frequently adopted and utilized to solve the data interoperability problem. Meanwhile, as IoT systems and devices can have different IMs with different modeling methodologies

Software product line engineering (SPLE) is a paradigm to promote systematic software reuse. A Feature Model (FM) is a common means to illustrate the commonality and variability of software products in a family. In most existing FM extraction approaches, keywords in the requirement document or certain types of system behavior or external events are considered features. The resulting FM is a combination

Third-party libraries always evolve and produce multiple versions. Lucene, for example, released ten new versions (from version 7.7.0 to 8.4.0) in 2019. These versions confuse the existing code search methods to retrieve the source code that is not compatible with local programming language. To solve this issue, we propose DCSE, a deep code search model based on evolving information (i.e. evolved code

Component-based software development (CBSD) is an efficient approach used by software developers to develop new software. The commercial off the shelf (COTS) and open-source software (OSS) are two styles to implement CBSD. The COTS provides the interface and depicts the black-box behavior, but does not support several software quality characteristics. On the other hard, OSS is a more efficient approach

Mobile and web applications must operate and be displayed correctly on many different devices and browsers. The visual testing of web or mobile applications is usually a manual process that requires a significant amount of testing time, meaning that applications are tested only on a few devices. It is then assumed that the applications will be displayed correctly on other compatible or similar devices

Development without any defect is unsubstantial. Timely detection of software defects favors the proper resource utilization saving time, effort and money. With the increasing size and complexity of software, demand for accurate and efficient prediction models is increasing. Recently, search-based techniques (SBTs) have fascinated many researchers for Software Defect Prediction (SDP). The goal of this

One of the main aims in the layered software architecture is to divide the code into different layers so that each layer contains related modules and serves its upper layers. Although layered software architecture is matured now; many legacy information systems do not benefit from the advantages of this architecture and their code for the process/business and data access are mostly in a single layer

The purpose of influence maximization problem is to select a small seed set to maximize the number of nodes influenced by the seed set. For viral marketing, the problem of influence maximization plays a vital role. Current works mainly focus on the unsigned social networks, which include only positive relationship between users. However, the influence maximization in the signed social networks including

Paying-off the Architectural Technical Debt by refactoring the flawed code is important to control the debt and to keep it as low as possible. Project Managers tend to delay paying off this debt because they face difficulties in comparing the cost of the refactoring against the benefits gained. These managers need to estimate the cost and the efforts required to conduct these refactoring activities

Data, information, knowledge, and wisdom forms a progressive relationship. Information is formed by data collation. Knowledge is filtered, refined, and processed from relevant information. Wisdom is based on knowledge and is accumulated through experience. This paper uses the progressive relationship of service data, information, knowledge, and wisdom to explain the expression of service knowledge

Design pattern detection can provide useful insights to support software comprehension. Accurate and complete detection of pattern instances are extremely important to enable software usability improvements. However, existing design pattern detection approaches and tools suffer from the following problems: incomplete description of design pattern instances, inaccurate behavioral constraint checking

Question Answering systems over Knowledge Graphs (KG) answer natural language questions using facts contained in a knowledge graph, and Simple Question Answering over Knowledge Graphs (KG-SimpleQA) means that the question can be answered by a single fact. Entity linking, which is a core component of KG-SimpleQA, detects the entities mentioned in questions, and links them to the actual entity in KG

When encountering bug issues, developers tend to search the bug repository and commit repository for references. However, the links between bug reports and commits in version control systems are often missed, and the information in bug repository and commit repository can provide is simple. When developers search a bug issue, they can only get the information of bug reports or commits, which are loose

Do developers postpone fixing Technical Debt (TD) in software systems? TD is a metaphor that refers to short-term decisions in software development that may affect the cost of the software development life cycle. The bad smell is an imperfect solution in the software system that negatively impacts the internal software quality and maintainability. In this paper, we will study five open-source software

Business-to-Business (B-to-B) software development companies develop services to satisfy their customers’ requirements. Developers should prioritize customer satisfaction because customers greatly influence agile software development. However, satisfying current customer’s requirements may not fulfill actual users or future customers’ requirements because customers’ requirements are not always derived

Significant effort is being put into developing industrial applications for artificial intelligence (AI), especially those using machine learning (ML) techniques. Despite the intensive support for building ML applications, there are still challenges when it comes to evaluating, assuring, and improving the quality or dependability. The difficulty stems from the unique nature of ML, namely, system behavior

Software effort estimation models are typically developed based on an underlying assumption that all data points are equally relevant to the prediction of effort for future projects. The dynamic nature of several aspects of the software engineering process could mean that this assumption does not hold in at least some cases. This study employs three kernel estimator functions to test the stationarity

Modern compilers provide a huge number of optional compilation optimization options. It is necessary to select the appropriate compilation optimization options for different programs or applications. To mitigate this problem, machine learning is widely used as an efficient technology. How to ensure the integrity and effectiveness of program information is the key to problem mitigation. In addition

Software dynamic birthmark techniques construct birthmarks using the captured execution traces from running the programs, which serve as one of the most promising methods for obfuscation-resilient software plagiarism detection. However, due to the perturbation caused by non-deterministic thread scheduling in multi-threaded programs, such dynamic approaches optimized for sequential programs may suffer

The activeness of regional business entities, like restaurants, cinemas and shopping malls, represents the evolvement of their corresponding commercial districts, whose prediction helps practitioners grasp the trend of commercial development and provides support for urban layout. On the other hand, online social network services, such as Yelp, are generating massive online reviews toward business entities

Stack Overflow is the most popular programming question and answer community that continuously receives a large number of questions every day. To ensure the quality of questions, the community grants privileges for the moderators and a group of experienced users to review the quality of questions and close the low-quality ones (e.g. duplicate or irrelevant questions). The review process is a typical

In recent years, the amount of user check-in data has significantly increased on social network platforms. Such data is an ideal source for characterizing user behaviors and identifying similar users, contributing to many research areas (e.g. user-based collaborative filtering). However, existing trajectory-based user similarity analysis approaches do not distinguish the effects of geographical factors

With the development of Web 2.0, social media such as Twitter and Sina Weibo have become an essential platform for disseminating hot events. Simultaneously, due to the free policy of microblogging services, users can post user-generated content freely on microblogging platforms. Accordingly, more and more hot events on microblogging platforms have been labeled as spammers. Spammers will not only hurt

Both complexity of code change for bug fixing and bug severity play an important role in release planning when considering which bugs should be fixed in a specific release under certain constraints. This work investigates whether there are significant differences between bugs of different severity levels regarding the complexity of code change for fixing the bugs. Code change complexity is measured

Spiking Neuron Network (SNN) uses spike sequence for data processing, so it has an excellent characteristic of low power consumption. However, due to the immaturity of learning algorithm, the multiplayer network training has difficulty in convergence. Utilizing the mature learning algorithm and fast training speed of the back-propagation network, this paper proposes a method to converse the Convolutional

Selecting a framework and documenting the rationale for choosing it is an essential task for system architects. Different framework selection approaches have been proposed in the literature. However, none of these connect frameworks to qualities based on their implemented patterns and tactics. In this paper, we propose a way to semi-automatically compare the quality attributes of frameworks by extracting

The distributed multiple autonomous network has become the main trend of modern information systems, such as Cloud, Service-Oriented Architecture (SOA) and Internet of Things (IoT). Access control in such a heterogeneous and dynamic system has become a major information security challenge, which hinders the sharing of resources and information. In this work, we present an Attribute-Based Access Control

The unrelenting trend of larger and larger sizes of Software Systems and data has made software comprehensibility an increasingly difficult problem. However, a tacit consensus that human understanding of software is essential for most software related activities, stimulated software developers to embed comprehensibility in their systems’ design. On the other hand, recent empirical successes of Deep

Well-designed software systems, with providers only modules, have been rigorously obtained by algebraic procedures from the software Laplacian Matrices or their respective Modularity Matrices. However, a complete view of the whole software system should display, besides provider relationships, also consumer relationships. Consumers may have two different roles in a system: either internal or external

This paper introduces a mechanism to recover traceability links between the requirements and logical models in the context of critical systems development. Currently, lifecycle processes are covered by a good number of tools that are used to generate different types of artifacts. One of the cornerstone capabilities in the development of critical systems lies in the possibility of automatically recovery

This paper presents a novel method to infer regular expressions from positive examples. The method consists of a candidate’s construction phase and an optimization phase. We first propose multiscaling sample augmentation to capture the cycle patterns from single examples during the candidate’s construction phase. We then use common substrings to build regular expressions that capture patterns across

The paper describes how to formally specify three path finding algorithms in Maude, a rewriting logic-based programming/specification language, and how to model check if they enjoy desired properties with the Maude LTL model checker. The three algorithms are Dijkstra Shortest Path Finding Algorithm (DA), A* Algorithm and LPA* Algorithm. One desired property is that the algorithms always find the shortest

Access and reuse of authoritative phylogenetic knowledge have been a longstanding challenges in the evolutionary biology community — leading to a number of research efforts (e.g. focused on interoperation, standardization of formats, and development of minimum reporting requirements). The Phylotastic project was launched to provide an answer to such challenges — as an architectural concept collaboratively

Because of rapid growth in mobile application markets, competition between companies that provide similar applications has become fierce. To improve user satisfaction for keeping existing users and attracting new users, application developers need to quickly respond to customer feedback regarding functionality and performance defects. In software engineering, specifying an accurate evolution plan according

Feature engineering is one aspect of knowledge engineering. Besides feature selection, the appropriate assignment of feature values is also crucial to the performance of many software applications, such as text categorization (TC) and speech recognition. In this work, we develop a general method to enhance TC performance by the use of context-dependent feature values (aka term weights), which are obtained

There is a growing interest in leveraging Deep Learning (DL) for automating Software Engineering tasks such as program completion. In this paper, we leverage Recurrent Neural Networks (RNNs) for Abstract Syntax Tree (AST)-based code completion. Our approach converts source code into AST nodes and a language model predicts the type and value attributes of next tokens. Our work demonstrates that the

Software testing is a continuous process during the software development stages to ensure quality software products. Researchers, experts and software engineers keep going on studying new techniques, methods and approaches of testing to accommodate changes in software development because of the flexible requirement along with the changing of technology. So, developers and testers need to have effective

Programming in pictures is an approach where pictures and moving pictures are used as super-characters to represent the features of computational algorithms and data structures, as well as for explaining the models and application methods involved. *AIDA is a computer language that supports programming in pictures. This language and its environment have been developed and promoted as a testbed for

Move Method Refactoring (MMR) is used to place highly coupled methods in appropriate classes for making source code more cohesive. Like other refactoring techniques, it is mandatory that applying MMR will preserve applications’ behaviors. However, traditional MMR techniques failed to meet this essential precondition for Action methods in web-based application and API methods in libraries projects.

The color design is one of the important parts of GUI development. To gain an attractive color scheme, designers often seek inspiration from examples. However, transferring an example’s colors to a target web page is time-consuming and tedious. In this paper, we propose a method named AutoWPR to reuse the example web page’s colors for recoloring a web page. To preserve the semantic relations of web

Multi-agent systems and agent-oriented methodologies support analysis, characterization and development of complex software systems. These methodologies introduce different definitions for the essential components of multi-agent systems and cover different phases of the system development life cycle. Therefore, appropriate frameworks for evaluation and comparison of different methodologies would support

In this paper, we address the problem of recognizing the semantic human activities through the analysis of large dataset collected from users’ sensor-based smartphones. Our approach is unique in terms of covering a large number of activities that users could possibly engage in, and considering the multi-level-based classification model. Our model has three properties that never seemed to be addressed

Influence maximization is a problem that aims to select top k influential nodes to maximize the spread of influence in social networks. The classical greedy-based algorithms and their improvements are relatively slow or not scalable. The efficiency of heuristic algorithms is fast but their accuracy is unacceptable. Some algorithms improve the accuracy and efficiency by consuming a large amount of memory

Topic word extraction is the task of identifying single or multi-word expressions that represent the main topics of a document. In this paper, two improved algorithms for extracting and discovering topic words are proposed in the Rapid Topic word Detection (RTD) Algorithm and CategoryTextRank (CTextRank) Algorithm, which can effectively obtain information by extracting and filtering the topic words

Mutation testing aims to evaluate the fault detection capability of a test suite. This evaluation substitutes faults with mutants by transforming program code to be defective. Evidences of the relationship between the detection rates of mutants and real faults have supported the use of mutants. It has also been known that the test suite size was a significant factor affecting the relationship. Our

For the test case prioritization problems, the average percent of faults detected (APFD) and its variant versions are widely used as metrics to evaluate prioritized test suite’s efficiency of fault detection. By a revisit of metrics for test case prioritization, we observe that APFD is only available for the scenarios where all test suites under evaluation contain the same number of test cases. Such

Fixed Sized Candidate Set (FSCS) is the first of a series of methods proposed to enhance the effectiveness of random testing (RT) referred to as Adaptive Random Testing methods or ARTs. Since its inception, test case generation overheads have been a major drawback to the success of ART. In FSCS, the bulk of this cost is embedded in distance computations between a set of randomly generated candidate

Train delay is a serious issue that can spread rapidly in the railway network leading to further delay of other trains and detention of passengers in stations. However, the current practice in the event of the trail delay usually depends on train dispatcher’s experience, which cannot manage train operation effectively and may have safety risks. The application of intelligent railway monitor and control

Accurate prediction of train delay recovery is critical for railway incident management and providing passengers with accurate journey time. In this paper, a two-stage prediction model is proposed to predict the recovery time of train primary-delay based on the real records from High-Speed Railway (HSR). In Stage 1, two models are built to study the influence of feature space and model framework on

The catenary support device inspection is of crucial importance for ensuring safety and reliability of railway systems. At present, visual detection tasks of catenary support devices defect are performed by trained personnel based on the images taken periodically by industrial cameras installed on inspection vehicle in a limited period of time at midnight. However, the inspection mean is inappropriate

In China, the turnout abnormality very easily causes traffic accident or affects the efficiency due to the operating environment of railway transportation. The existing monitoring means are relatively backward, and mature automatic diagnosis method is lacking. In this study, a method based on semi-supervised learning algorithm for abnormal state diagnosis of turnout action curve is proposed, which

The deployment change of SaaS (Software as a Service) software will influence its response time, which is an important performance metric. Therefore, studying the impact of deployment change on the response time of SaaS software could contribute to performance improvement of the software. However, there are few performance analysis methods which can directly analyze the relationship between deployment

Trace links between requirements and software artifacts provide available traceability information and in-depth insights for different stakeholders. Unfortunately, establishing requirements trace links is a tedious, labor-intensive and fallible task. To alleviate this problem, Information Retrieval (IR) methods, such as Vector Space Model (VSM), Latent Semantic Indexing (LSI), and their variants, have

The architecture smells are the poor design practices applied to the software architecture design. The smells in software architecture design can be cascaded to cause the issues in the system implementation and significantly affect the maintainability and reliability attribute of the software system. The prevention of architecture smells at the design phase can therefore improve the overall quality

Understanding user’s search intent in vertical websites like IT service crowdsourcing platform relies heavily on domain knowledge. Meanwhile, searching for services accurately on crowdsourcing platforms is still difficult, because these platforms do not contain enough information to support high-performance search. To solve these problems, we build and leverage a knowledge graph named ITServiceKG to

In the last decade, REST has become the most common approach to provide web services, yet it was not originally designed to handle typical modern applications (e.g. mobile apps). GraphQL was proposed to reduce the number of queries and data exchanged in comparison with REST. Since its release in 2015, it has gained momentum as an alternative approach to REST. However, generating and maintaining GraphQL