Code search plays a role in bridging code and query. However, recent code search studies mainly rely on affinity-matrix-based cross-modal attention to learn the word alignments between code and query, which may lead to incorrect alignments. In this paper, we propose a Global Alignment Learning Model (GALM) to learn global alignments and demonstrate that better-learned correct alignments can significantly improve code search performance. Specifically, GALM characterizes the query and code embedding into an alignment graph to enhance the feature representation and further learns global alignments by a dense graph convolutional network. To evaluate the performance of GALM, we compared it with several baseline models on two pop-ular datasets. The results demonstrate that GALM outperforms the best baseline models by 9.8% and 6.8% with the Top@1 accuracy of 0.601 and 0.671 on two datasets, respectively.

Software specification quality significantly influ-ences overall software quality. Ambiguity in natural language specifications has been identified as a major obstacle to achieving high quality. Formal methods have been proposed as a solution to mitigate this issue, but their adoption in software development remains limited. While previous studies have primarily focused on the challenges of introducing formal methods, few reports exist on the effects of applying formal methods in software development. To tackle this issue, this study analyzes the trends in OSS (open source software) with and without formal methods, based on issues collected from GitHub repositories. We employed BERTopic, a topic modeling technique, to extract topics associated with issues. Subsequently, we labeled the issues and statistically compared topics of issues in OSS with and without formal methods. The results indicate a significant difference in the tendency of issues between OSSs with formal methods and without formal methods, particularly in the frequency of reported errors. These findings suggest the existence of issues specific to OSSs with formal methods and highlight the potential benefits of formal methods in reducing errors during development.

SZZ is the de facto standard method for identifying bug-inducing commits. The accuracy of this method heavily relies on source code management systems, such as Git, as it requires tracing the history of source code changes (i.e., commit histories) to bug-inducing commits. However, it has been reported that these systems introduce biases in commit histories because they only store line-level changes. It is known that such coarse-grained line-level changes can result in the failure to accurately track the commit history and reduce the performance of SZZ. To relieve this challenge, we explore the accuracy of SZZ in token-level changes, which provide finer-grained information to trace commit histories compared to line-level ones, and we discuss the potential benefits and pitfalls of utilizing token-level changes for SZZ. As a result of experiments on 68 OSS projects, we found that SZZ, which uses token-level histories, identifies two new bug-inducing commits that are missed when using line-level histories. Furthermore, our manual analysis of the identified commits indicates that they reduce false-positive bug-inducing commits caused by source code formatting and whitespace changes. However, this improvement in detecting bug-inducing commits comes with a trade-off of 0.081 decrease in overall accuracy, as measured by the F1 score. Consequently, we summarized three potential benefits and five pitfalls of using token-level and line-level tracking for SZZ.

Abstract Faulty Interaction Localization (FIL) is a process to identify which combination of input parameter values induced test failures in combinatorial testing. An accurate and fast FIL provides helpful information to fix defects causing the test failure. One type of conventional FIL approach, which analyzes test results of whole test cases and estimates the suspiciousness of each combination, has two main concerns; (1) the accuracy is not enough, (2) the huge time cost is sometimes needed. In this paper, we propose two novel approaches to improve those concerns. attempts to estimate suspiciousness more accurately using logistic regression analysis. attempts to estimate failure-inducing combinations at high speed by estimating the subsets of them using logistic regression analysis and exploring just their supersets. Through evaluation experiments using a large number of artificial test results based on several real software systems, we observed that has very high accuracy, and can drastically reduce time cost for targets that have been difficult to complete by the conventional method.

We have proposed the Ticket-based Access Control Method. It provides access control with a token called a ticket and Tag ID. A token has an ID for data acquisition tied to multiple devices. The Ticket-based Access Control Method realizes the IoT data distribution infrastructure that supports the collection/analysis, scalability, and security of various types of IoT data. It includes the TAAI node (Ticket Authentication and Authorization Infrastructure node), which acts as a role of Broker in the Pub/Sub communication model. It is always involved in authentication and authorization. The TAAI is a single point of failure because when the TAAI fails, the entire system will go down. Therefore, to eliminate the single point of failure in the Tag ID-based Pub/Sub model using Ticket-based AC, we propose a method to distribute the processing performed by the TAAI to each node by applying blockchain (BC) technology. Having the BC take charge of authentication can reduce the load on each node.

We have proposed Information-Centric Networking-based Wireless Sensor Networks (ICSN) to realize multiple IoT services. In ICSN, data in FIB (Forwarding Information Base) must be statically assigned in advance to set up routes between each sensor node. Therefore, the dynamic routing method to build a sensor network automatically is required to reduce set-up time. We propose the dynamic route setup method for ICSNs and confirm the effectiveness of the proposed method by emulation and trial manufacture.

COVID-19 has transformed face-to-face software development into distributed development (e. g., remote work). While the company authors belong to studies microtask programming, an open source software (OSS) -like development, as a solution to employ distributed development, a prior study reports a challenge: online communication in microtask programming takes longer; such lengthy communication discourages developers and affects their completion of assigned tasks. OSS, however, is successfully developed using online communication, such as issues. Hence, we have a question: how does OSS address the online communication challenge? In this experience report, we answer this question based on an empirical study on OSS communication. We found that (1) OSS prefers burst communication similar to face-to-face development, and (2) attracting developers’ attention may be a possible solution. Based on the findings, we discuss the direction of future studies to achieve better online communication in microtask programming in the company. The main contributions of this report are (1) to empirically reveal the actual communication times in OSS and (2) to show how an empirical approach helps industrial collaborators.

Sensor networks to autonomously collect data and send it to the cloud via gateways are expecting for providing various IoT services. In many cases, the service providers need to build their own sensor network and many sensors to measure same data will place in a narrow area. To solve this problem, we have proposed an Information-Centric Networking based wireless Sensor Network (ICSN) to provide multiple IoT services. Also, we have proposed an ICSN Platform (ICSNP) that provides the functions of executing IoT services in sink nodes. However, the number of requests increases due to increasing number of services simultaneously at the sink node. It causes performance degradation due to rising processing load. Therefore, we have proposed the cloud-based load distribution model for application to an environment of multiple IoT services. In this paper, we evaluated the node load focusing on the sensor data acquisition interval by implementing the proposed model. As a result, the proposed method can reduce the load on the sink node compared to the conventional method even in an environment with many concurrently connected applications and short sensor data acquisition intervals. Therefore, the relationship between the acquisition interval and load in actual operation are indicated.

Microtask programming [4] is a solution to promote distributed development in industry. The key idea of microtask programming is to reduce face-to-face communication across developers by splitting the development task of software into independent microtasks. Such microtasks can be completed by crowd workers who work remotely and at their preferable time such as early morning. Dedicated developers who have the responsibility for the progress of development split the task into microtasks, and distribute them to crowd workers. Hence, microtask programming has these two actors. Our research team reported that microtask programming has potential benefits such as the fluidity of project assignments in industrial companies [4]. However, we suppose it still has challenges. In addition, it is still unclear what are future research direction to support both actors in microtask programming, though our research team has conducted three studies for microtask programming so far [2--4].

Abstract The accuracy of the SZZ algorithm is pivotal for just-in-time defect prediction because most prior studies have used the SZZ algorithm to detect defect-inducing commits to construct and evaluate their defect prediction models. The SZZ algorithm has two phases to detect defect-inducing commits: (1) linking issue reports in an issue-tracking system to possible defect-fixing commits in a version control system by using an issue-link algorithm (ILA); and (2) tracing the modifications of defect-fixing commits back to possible defect-inducing commits. Researchers and practitioners can address the second phase by using existing solutions such as a tool called . In contrast, although various ILAs have been proposed for the first phase, no large-scale studies exist in which such ILAs are evaluated under the same experimental conditions. Hence, we still have no conclusions regarding the best-performing ILA for the first phase. In this paper, we compare 10 ILAs collected from our systematic literature study with regards to the accuracy of detecting defect-fixing commits. In addition, we compare the defect prediction performance of ILAs and their combinations that can detect defect-fixing commits accurately. We conducted experiments on five open-source software projects. We found that all ILAs and their combinations prevented the defect prediction model from being affected by missing defect-fixing commits. In particular, the combination of a natural language text similarity approach, Phantom heuristics, a random forest approach, and a support vector machine approach is the best way to statistically significantly reduced the absolute differences from the ground-truth defect prediction performance. We summarized the guidelines to use ILAs as our recommendations.

In recent years, a configuration management tool is adopted to manage complicated and huge systems such as bare-metal servers, cloud computing resources and our personal computers. Such a tool makes the operations to deploy services more efficient and eliminates dependencies on the specific system operators. The operations are required to be idempotent for reproducible deployment. However, the imperative modules whose operations may not be idempotent are used frequently to execute user-defined scripts on the target system; it is unclear why and how they are used, though using them frequently is believed to be a bad practice. In this paper, we studied why and how imperative modules are used in a configuration management tool, Ansible. We found that imperative modules are mainly used to perform operations that are not supported by Ansible, and about 45% of imperative modules are replaceable by other modules; the replaceable modules might be idempotent. We, therefore, recommend developers to look at replaceable modules before using imperative modules since replaceable modules might make their operations idempotent.

GitHub is a huge publicly available development platform for hosting a version control system based on Git; software developers prefer to host their various software projects in GitHub. Therefore researchers who are interested in mining software repository frequently use GitHub to collect software projects as datasets. GitHub provides us with repository metrics such as popularity, contribution, and interest. We believe that such metrics are related to the quality of software; we use them to opt for studied repositories according to our research purpose. However, to the best of our knowledge, nobody has any evidence to support this assumption.Our main purpose is to provide researchers who study software quality, especially issue management, with repository metrics to select appropriate repositories for their studies. In this paper, we study the relationship between the characteristics of the issue pages of repositories that are selected by repository metrics in order to figure out the best repository metric to select proper repositories. The following findings are the highlights of our study: (1) The number of contributors that indicates the number of developers who contribute to a GitHub repository can be used to select the repositories having issue pages that are well-maintained. More specifically, such issue pages include more issues and in which developers use the labels more frequently rather than those that are selected by other metrics. (2) The number of dependencies opts for the repositories that have fewer issues and in which developers use the labels less often rather than those that are selected by other metrics.

V2X task offloading, which moves computational tasks to nearby edge nodes (ENs) with available computing resources, has attracted attention. The task is offloaded to ENs that satisfies the task delay constraints, including the transmission delay and the calculation delay when the task is offloaded. However, since many existing methods assume a static environment in which nodes are fixed, communication may be disconnected in the dynamic environment in which nodes move. On the other hand, the task offloading methods in a dynamic environment, they do not consider the case where the node turning behavior, since they assume only the case where the nodes move in a straight line. Therefore, in order to establish appropriate ENs selection method in dynamic environment, we propose a V2V task offloading method considering automobile behavior including both going straight line and turning in urban area. And the effectiveness of the proposed method is shown in comparison with the existing method by simulation.

Combinatorial testing is a widely used technique to detect failures caused by interactions of system under test (SUT) parameters. Faulty interaction localization (FIL) is a problem to locate parameter-value combinations that trigger failures from combinatorial test cases and their testing results. FIL is important for debugging, but is expensive for large test suites and SUTs since the number of candidates of faulty interactions increases exponentially with the number of parameters and the size of interactions. To address this problem, this paper proposes a method employing logistic regression. The proposed FIL based on Regression coefficients Of loGistic regression analysis (called FROG) computes the suspiciousness of each parameter-value combination to be included in a faulty interaction from its corresponding regression coefficient. We evaluate the proposed method by applying FROG to combinatorial t-way test cases (2 ≤ t ≤ 4) for real application SUT models, e.g. TCAS, GCC, and Apache. Our experiment results show that FROG can effectively locate faulty interactions injected while efficiently reducing the number of candidates of potential faulty interactions to be checked.

Many industries expect M2M services which collect a variety of data through sensor networks. However, in general, a sensor network is designed for applying a single service. On the other hand, ICN (Information-Centric Networking) is known as one of new generation networks. Applying ICN for sensor network, the sensor network platform to provide a variety of M2M services can be built. Additionally, sensors are mainly battery driven. However, many sensors will locate at the place where difficult to human access. For that reason, it is required that saving energy consumption of nodes. We propose the route switching method for prolonging network lifetime in providing multiple services via wireless sensor network. We evaluated the proposed method by simulation experiments and discussed its effectiveness.

Open Shortest Path First (OSPF) is a popular routing protocol for the Internet services. OSPF causes network congestion if specific path becomes bottle neck links. However, OSPF can't avoid this congestion dynamically. In this paper, we propose the routing method using available bandwidth and degree. It is confirmed that the proposed method shows lower packet loss rate, shorter transmission time and higher throughput than those of OSPF.

This paper proposes a novel approach to combinatorial test generation, which achieves an increase of not only the number of new combinations but also the distance between test cases. We applied our distance-integrated approach to a state-of-the-art greedy algorithm for traditional combinatorial test generation by using two distance metrics, Hamming distance, and a modified chi-square distance. Experimental results using numerous benchmark models show that combinatorial test suites generated by our approach using both distance metrics can improve interaction coverage for higher interaction strengths with low computational overhead.

Combinatorial testing is a widely-used technique to detect system interaction failures. To improve test effectiveness with given priority weights of parameter values in a system under test, prioritized combinatorial testing constructs test suites where highly weighted parameter values appear earlier or more frequently. Such order-focused and frequency-focused combinatorial test generation algorithms have been evaluated using metrics called weight coverage and KL divergence but not sufficiently with fault detection effectiveness so far. We evaluate the fault detection effectiveness on a collection of open source utilities, applying prioritized combinatorial test generation and investigating its correlation with weight coverage and KL divergence.

Once a bug in software is reported, developers have to determine which source files are related to the bug. This process is referred to as bug localization, and an automatic way of bug localization is important to improve developers' productivity. This paper proposes an approach called DrewBL to efficiently localize faulty files for a given bug report using a natural language processing tool, word2vec. In DrewBL, we first build a vector space model named semantic-VSM which represents a distributed representation of words in the bug report and source code files and next compute the relevance between them by feeding the constructed model to word2vec. We also present an approach called CombBL to further improve the accuracy of bug localization which employs not only the proposed DrewBL but also existing bug localization techniques, such as BugLocator based on textual similarity and Bugspots based on bug-fixing history, in a combinational manner. This paper gives our early experimental results to show the effectiveness and efficiency of the proposed approaches using two open source projects.

This paper presents a low-invasive framework for estimating changes in a cognitive performance using heart rate variability (HRV). Although HRV is a common physiological indicator of autonomous nerve activity or central nervous fatigue, there are individual differences in the relationship between HRV and such internal state. The new framework enables an estimation model to be determined using the HRV characteristics of individuals performing tasks through cognitive efforts. They also enable users working in a chair to have their changes in the cognitive performance estimated without interrupting their work or having to use a lot of devices as most previous methods require. Experimental results show the framework can estimate mental fatigue; defined based on cognitive performance, using HRV as the same level as the previous work did using higher-invasive method(using multi-channel electroencephalogram (EEG) sensor or multiple vital sensors). It can also estimate changes in a cognitive performance for most of subjects, and one of our proposed method in the framework realizes more effective and useful estimation than the others. It therefore has the potential to help managerial personnel in making performance change reports for their workers, suggesting reasons for changes in the performance, and urging them to change their working styles using HRV.

We propose a machine-to-machine service platform that employs various types of sensor nodes and can provide many different services. The platform has three requirements: connectivity for many types of sensor node, flexible sensor node configuration, and “Many-to-Many” communication. NetInf, a type of Information Centric Network, realizes flexible sensor node configuration. To meet the other requirements, we propose two methods, a distributed routing method that divides data along two paths, and a cache data location method that caches data that may be requested by subscribers. Simulations have been performed for a network assuming a smart city. The results of the simulations confirm the validity of the proposed methods.

We have developed a head care robot equipped with scrubbing fingers that washes hair and provides scalp cares in hospitals and care facilities to ease the burden on healthcare professionals and care workers. Our robot provides frequent hair washing and a higher Quality Of Life (QOL) to patients and others who need such nursing care. Its elemental technologies include the following: a cylindrical rack mechanism for self-aligning and a drive-force transmission from an electric motor to multiple fingers, a five-bar closed link mechanism to expand the area of the head that can be washed by extension motion, and rear pressure force control by a coordinated double arm motion to switch between supporting and washing the head. In addition, we introduce an orientation correction mechanism into our five-bar closed link mechanism to keep the end effector's contact face aligned along the head's surface. This paper presents several elemental technologies and the kinematics of a five-bar closed link mechanism and discusses the improvement of the head shape following capability using an orientation correction mechanism.

In Japan, major earthquakes are predicted to occur in the metropolitan area. In the time of such a disaster, communication systems will play an important role to transfer mitigation information such as instruction for people to move the evacuate area and for contractors to recover city functions. However, mitigation information may be unable to transfer smoothly, because of telecom infrastructure damage and conflicting information. Objective of this research is to clarify system requirements in order to build the mitigation network using wireless LAN systems. Use cases for network design are created based on reports and actions of public organizations when the great East Japan earthquake was happened. We propose the mitigation information network composed of three sub networks; the long-distance wireless LAN for connecting to the backup station in non-disaster area, the midrange wireless LAN for connecting between countermeasures offices, the information gathering and distribution network in disaster area. In order to decide specification of wireless systems and position of antenna, we measure throughput of 2.5GHz and 4.9GHz band between Shinjuku and Hachioji for the long-distance wireless LAN. Also we measure throughput of 4.9GHz band in Nishi-Shinjuku area, where is forest of tall buildings, for the information gathering and distribution network. The mitigation network will be built with these results.

We have developed the world's first hair-washing robot equipped with scrubbing fingers. This robot assists in washing hair in hospitals or care facilities, and it eases the burden of healthcare professionals and care workers while it brings a higher quality of life to patients and others in need of nursing care. It features the mechanical and control technologies needed for touching someone gently on the head. These include, for instance, the self-aligning mechanism and the cylindrical rack mechanism of the robot's end effector, the parallel link mechanism of its pressing arm, and the compliance control for providing an appropriate sense of pressure.

There have been many bug prediction models built with historical metrics, which are mined from version histories of software modules. Many studies have reported the effectiveness of these historical metrics. For prediction levels, most studies have targeted package and file levels. Prediction on a fine-grained level, which represents the method level, is required because there may be interesting results compared to coarse-grained (package and file levels) prediction. These results include good performance when considering quality assurance efforts, and new findings about the correlations between bugs and histories. However, fine-grained prediction has been a challenge because obtaining method histories from existing version control systems is a difficult problem. To tackle this problem, we have developed a fine-grained version control system for Java, Historage. With this system, we target Java software and conduct fine-grained prediction with well-known historical metrics. The results indicate that fine-grained (method-level) prediction outperforms coarse-grained (package and file levels) prediction when taking the efforts necessary to find bugs into account. Using a correlation analysis, we show that past bug information does not contribute to method-level bug prediction.

Link aggregation bundles multiple physical links on a single virtual link, enabling very high-speed and large-capacity data communications. It also enables redundant communications. Several link aggregation methods have been proposed. These methods utilize transport layer link aggregation. In this paper, a new application level link aggregation is proposed and implemented on Android OS, which is one of the popular OSs for mobile devices such as smartphones and tablet PCs. The proposed application level link aggregation method is verified with use of an implemented terminal.

ABSTRACT Link aggregation bundles multiple physical links on a single virtual link, enabling very high‐speed and large‐capacity data communications. It also enables redundant communications. Several link aggregation methods have been proposed. These methods utilize transport/or lower layer link aggregation. In this paper, a new application‐level link aggregation is proposed and implemented on Android operating system (OS), which is one of the popular OSs for mobile devices such as smartphones and tablet PCs. The proposed application‐level link aggregation method is verified with use of an implemented terminal. Copyright © 2012 John Wiley & Sons, Ltd.

In order to assure the quality of software, early detection of defects is highly recommended. Code review is one of effective way for such early detection of defects in software. Code review activities must contain various useful insights for software quality. However, especially in open source software developments, records of code review merely exist. In this study, we try to analyze a code review repository of an open source software, Chromium, which adopts a code review tool in its development.Before analyzing the code review data, we address 7 research questions. We can find interesting answers for these questions by repositories mining.

Comment lines in the software source code include descriptions of codes, usage of codes, copyrights, unused codes, comments, and so on. It is required for comments to explain the content of written code adequately, since the wrong description in the comment may causes further bug and confusion in maintenance.

We demonstrate a mock-up that enables the sharing of existing Web contents between the caller and receiver in a phone call. Two methods for this sharing are described. One is a mash-up method using APIs that existing Web contents provide. The other is a proxy method that uses existing Web contents as is. Both methods can be used with basic Web browsers.

To increase the Web contents of the call-to-Web session linkage system that we have proposed, we discuss a method that enables the use of existing Web contents without any modification for sharing. The proposed method uses a proxy server to detect and convert the transitioning URLs. We evaluated the ability of the proposed method to correspond to the form of the content and considered the correspondence for dynamic contents.

In order to assure the quality of software product, early detection of fault-prone products is necessary. Fault-prone module detection is one of the major and traditional area of software engineering. However, comparative study using the fair environment rarely conducted so far because there is little data publicly available. This paper tries to conduct a comparative study of fault-prone module detection approaches.

We demonstrate a prototype of a call-to-Web session linkage system for sharing a Web application between caller and receiver. The system makes a session linkage between Web browsers based on call session information of SIP, which is an application-layer control protocol mainly used for IP telephony systems. After that, the system offers Web servers information for the linkage so that Web servers can provide a shared Web service easily. This system can even be uses by a browser of home appliances, which are difficult to upgrade because those linkage protocols consist of basic browser functions such as HTTP redirect and JavaScript.

We demonstrate a prototype of Dial-to-Connect (D2C) VPN system for transmitting DLNA (Digital Living Network Alliance) protocols between home networks. Research studies implemented proxy systems over VPN so that DLNA devices could communicate remotely, but they were not designed for how to easily establish VPN tunnels. D2C VPN system uses SIP to execute an indication and authentication of the destination based on a telephone number, which is the most common information to connect two network devices. D2C VPN system enables novice PC users to establish an on-demand VPN with ease and enjoy remote DLNA communication with home appliances. D2C VPN system has two functions: SIP-VPN function and DLNA proxy function. A user requests a VPN tunnel using the SIP-VPN function by inputting a destination phone number to which he/she wants to connect, and if a gateway of the destination accepts the request based on his/her phone number successfully, the VPN tunnel is established. After that, the DLNA proxy function liaises with the SIP-VPN function. D2C VPN system can also use QoS that a SIP network provides because VPN packets are sent through a channel negotiated by the SIP.

We have developed a new on-demand VPN system that works over a managed SIP network such as the next-generation network (NGN). The system achieves a stable broadband VPN connection between two home networks in an easy-to-use manner by using SIP for session management. The system uses telephone numbers, QoS management, and packet-filtering capabilities that are provided by the NGN. In this paper, we describe the system and focus on how IKEv2 and IPsec, with a slight extension to the port-number handling, can be adapted to an NGN that has NAT- or 5-tuple-based packet filtering within the network.

Fault-prone module detection is important for assurance of software quality. We have proposed a novel approach for detecting fault-prone modules using spam filtering technique, named Fault-proneness filtering. In order to show the effectiveness of fault-proneness filtering, we conducted comparative study with a static code analysis tool, PMD. In the study, Fault-proneness filtering obtains higher F1than PMD.

Fault-prone module detection in source code is important for assurance of software quality. Most previous fault-prone detection approaches have been based on software metrics. Such approaches, however, have difficulties in collecting the metrics and in constructing mathematical models based on the metrics. To mitigate such difficulties, we have proposed a novel approach for detecting fault-prone modules using a spam-filtering technique, named Fault-Prone Filtering. In our approach, fault-prone modules are detected in such a way that the source code modules are considered as text files and are applied to the spam filter directly. In practice, we use the training only errors procedure and apply this procedure to fault-prone. Since no pre-training is required, this procedure can be applied to an actual development field immediately. This paper describes an extension of the training only errors procedures. We introduce a precise unit of training, "modified lines of code," instead of methods. In addition, we introduce the dynamic threshold for classification. The result of the experiment shows that our extension leads to twice the precision with about the same recall, and improves 15% on the best F1 measurement.

We demonstrate a prototype of a mobile phone based authentication service that can easily be used by home appliance users. The system employs the mobile phone's strong user identification capabilities such as UIMs, device identifiers or digital certificates to authenticate users over the mobile phone network while services are delivered to their appliances via the Internet. The authentication method is targeted to be used on home appliances such as digital televisions with web browsers which do not have rich interfaces. Therefore it is designed not to require users to enter any user information or to install any hardware and/or software into the appliance. This is achieved by binding a service session on the Internet and mobile network session using a barcode scanner on a mobile phone terminal. The prototype also provides an alternative method for mobile phone terminals which does not have a barcode scanner function to complement user availability.

The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous conventional fault-prone detection approaches have been based on using software metrics. Such approaches, however, have difficulties in collecting the metrics and constructing mathematical models based on the metrics. In order to mitigate such difficulties, we propose a novel approach for detecting fault-prone modules using a spam filtering technique. Because of the increase of needs for spam e-mail detection, the spam filtering technique has been progressed as a convenient and effective technique for text mining. In our approach, fault-prone modules are detected in a way that the source code modules are considered as text files and are applied to the spam filter directly. In order to show the usefulness of our approach, we conducted an experiment using source code repository of a Java based open source development. The result of experiment shows that our approach can classify more than 70% of software modules correctly.

The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous fault-prone detection approaches are based on software metrics. Such approaches, however, have difficulties in collecting the metrics and constructing mathematical models based on the metrics. In order to mitigate such difficulties, we propose a novel approach for detecting fault-prone modules using a spam filtering technique, named Fault-Prone Filtering. Because of the increase of needs for spam e-mail detection, the spam filtering technique has been progressed as a convenient and effective technique for text mining. In our approach, fault-prone modules are detected in a way that the source code modules are considered as text files and are applied to the spam filter directly. This paper describes the training on errors procedure to apply fault-prone filtering in practice. Since no pre-training is required, this procedure can be applied to actual development field immediately. In order to show the usefulness of our approach, we conducted an experiment using a large source code repository of Java based open source project. The result of experiment shows that our approach can classify about 85% of software modules correctly. The result also indicates that fault-prone modules can be detected relatively low cost at an early stage.

The software projects are considered to be successful if the cost and the duration are within the estimated ones and the quality is satisfactory. To attain project success, the project management, in which the final status of project is estimated, must be incorporated.In this paper, we consider estimation of the final status(that is, successful or unsuccessful) of project by applying Bayesian classifier to metrics data collected from project. In order to attain high estimation accuracy rate, we must select only a set of appropriate metrics to be applied. Here we consider two selection methods: the first method by the experts and the second method by the statistical test.Then we conducted an experiment using 28 project data and 29 metrics data in an organization of a certain company. The result showed that the method by the test gave higher accuracy rates than the method by the experts, and Bayesian classifier with the test method is effective to estimate project success.

Recent software systems contain a lot of functions to provide various services. According to this tendency, it is difficult to ensure software quality and to eliminate crucial faults by conventional software testing methods. Especially, in the conventional method, the detail level of test items are widely varied, according to the engineers' skill, and this causes an immature software quality. In this paper, we discuss the effects of test engineer skill on test item generation, and propose a new test item generation method, that enables the generation of test items for illegal behavior of the system. The proposed method can generate test items based on use-case analysis, deviation analysis for legal behavior, and fault tree analysis for system fault situations. From the result of the experimental applications, we confirmed that test items for illegal behavior of the system were effectively generated, and also the proposed method could effectively assist test item generation by poorly skilled engineers.

To predict software quality, we must consider various factors because software development consists of various activities, which the software reliability growth model (SRGM) does not consider. In this paper, we propose a model to predict the final quality of a software product by using the Bayesian belief network (BBN) model. By using the BBN, we can construct a prediction model that focuses on the structure of the software development process explicitly representing complex relationships between metrics, and handling uncertain metrics, such as residual faults in the software products. In order to evaluate the constructed model, we perform an empirical experiment based on the metrics data collected from development projects in a certain company. As a result of the empirical evaluation, we confirm that the proposed model can predict the amount of residual faults that the SRGM cannot handle.

This paper describes an automatic content indexing system for news programs, with a special emphasis on its segmentation process. The process can successfully segment an entire news program into topic-centered news stories; the primary tool is a linguistic topic segmentation algorithm. Experiments show that the resulting speech-based segments are fairly accurate, and scene change points supplied by an external video processor can be of help in improving segmentation effectiveness.

According to a progress of the software process improvement, the time series data on the number of faults detected by the software testing are collected extensively. In this paper, we perform statistical analyses of relationships between the time series data and the field quality of software products. At first, we apply the rank correlation coefficient /spl tau/ to the time series data collected from actual software testing in a certain company, and classify these data into four types of trends: strict increasing, almost increasing, almost decreasing, and strict decreasing. We then investigate, for each type of trend, the field quality of software products developed by the corresponding software projects. As a result of statistical analyses, we showed that software projects having trend of almost or strict decreasing in the number of faults detected by the software testing could produce the software products with high quality.

In practical software development, software quality is generally evaluated by the number of residual defects. To keep the number of residual defects within a permissible value, too much effort is often assigned to software testing. We try to develop a statistical model to determine the amount of testing effort which is needed to assure the field quality. The model explicitly includes design, review, and test (including debug) activities. Firstly, we construct a linear multiple regression model that can clarify the relationship among the number of residual defects and the efforts assigned to design, review, and test activities. We then confirm the applicability of the model by statistical analysis using actual project data. Next, we obtain an equation based on the model to determine the test effort. As parameters in the equation, the permissible number of residual defects, the design effort, and the review effort are included. Then, the equation determines the test effort that is needed to assure the permissible residual defects. Finally, we conduct an experimental evaluation using actual project data and show the usefulness of the equation.

The needs for accessibility of cellular phones to Web based client-server systems are increasing. For this access, efficient management of the context data must be implemented on the cellular phone. However, physical restrictions of the cellular phone make it difficult to manage context data by applying the conventional methods. Additionally the conventional methods do not show sufficient performance to tolerate heavy accesses from cellular phones. We therefore design a new session management mechanism that enables cellular phone to use Web client-server system efficiently. To do so, we decide to utilize key concepts in the CDS mechanism, which was previously developed by us in order to implement session management on the Web. By utilizing the CDS mechanism, we develop a new session management mechanism that connects cellular phone and Web systems. Then, we can actually implement the session management with high safety and reliability. The result of a benchmark evaluation shows that proposed mechanism has higher performance than the conventional mechanism.

Even for electrical appliances, testing for illegal behaviors becomes difficult since the software system in an electrical appliance has already, become large in size. Actually the conventional method cannot generate sufficient test items for illegal behaviors. But testing illegal behaviors becomes more and more important, since the failure of electrical appliances would cause fatal effects on our daily life. We therefore propose a new method for generating appropriate test items to check illegal behaviors, which consists of the following steps: (1) describe software behavior using use case notation; (2) analyze illegal behavior by the deviation analysis technique; (3) construct a software fault tree using the above information; and (4) generate test items from the software fault tree. This paper also reports the experimental applications to actual development of an electrical appliance. The evaluation results identified that all necessary, test items for illegal behaviors are included in the resultant test items.

The authors identify key attributes of projects in which the number of problem reports after release is remarkable in the communication software. After several interviews with software project managers, we derived candidate attributes of importance to the projects. To find out the most influential attributes of the projects, we conducted statistical analysis using a set of metrics data related to the candidate attributes and the number of problem reports after release. As a result we successfully found that two metrics concerning the origin's quality and the changes in specification are useful to estimate the field quality.

During the process of software development, senior managers often find indications that projects are risky and take appropriate actions to recover them from this dangerous status. If senior managers fail to detect such risks, it is possible that such projects may collapse completely.

Discusses the estimation of the effort needed to update programs according to a given requirement change. In object-oriented prototyping development (OO prototyping), the requirement changes occur frequently and regularly. Thus, a simple and fast estimation of effort is strongly required by both developers and managers. However, existing estimation methods cannot be applied to OO prototyping. Therefore, we propose a straightforward approach to effort estimation, which reflects the specific properties of OO prototyping. First, we analyze the following characteristics of OO prototyping: (1) updating activities consist of creation, deletion and modification; (2) the target to be updated has four kinds of types (void type, basic type, library type and custom type); and (3) the degree of information hiding is classified into private, protected and public. Then, we present a new formula E(P,/spl sigma/) to calculate the effort needed to update a program P according to a set of requirement changes /spl sigma/. The formula E(P,/spl sigma/) includes the weighting parameters w/sub upd/, w/sub type/ and w/sub inf-h/ according to the characteristics (1), (2) and (3), respectively. Finally, we conduct experimental evaluations by applying the formula E(P,/spl sigma/) to actual project data in a certain company. The evaluation results prove statistically (to some extent) the validity of the proposed approach.

This paper discusses the effects of estimation accuracy for software development cost on both the quality of the delivered code and the productivity of the development team. The estimation accuracy is measured by metric RE (relative error). The quality and productivity are measured by metrics FQ (field quality) and TP (team productivity). Using actual project data on thirty-one projects at a certain company, the following are verified by correlation analysis and testing of statistical hypotheses. There is a high correlation between the faithfulness of the development plan to standards and the value of RE (a coefficient of correlation between them is -0.60). Both FQ and TP are significantly different between projects with -10%<RE<+10% and projects with RE/spl ges/+10% (the level of significance is chosen as 0.05).

The Multi-layered Speech/Sound Synthesis Control Language (MSCL) proposed herein facilitates the syn-thesizing of several speech modes such as nuance, mental state and emotion, and allows speech to be synchronized to other media easily. MSCL is a multi-layered linguis-tic system and encompasses three layers: and seman-tic level layer (The S-layer), interpretation level layer (The I-layer), and parameter level layer (The P-layer). The S-layer is the description level of semantics such as emotional and emphasized speech. The I-layer is the description level of prosodic feature controls and inter-prets The S-layer scripts to for control on I-layer level. The P-layer represents prosodic parameters for speech synthesis. This multi-level description system is conve-nient for both laymen and professional users. MSCL also encompasses many eective prosodic feature con-trol functions such as a time-varying pattern descrip-tion function, absolute and relative control forms, and SDS(Speaker Dependent Scale). MSCL enables more emotional and expressive synthetic speech than conven-tional TTS systems. This paper describes these func-tions and the eective prosodic feature controls possible with MSCL. 1

In order to manage software projects quantitatively, we have presented a new model far software project based on generalized stochastic Petri-net model which can take influence of human factors into account, and we have already developed software project simulator based on GSPN model. This paper proposes methods for calculating model parameters in the new model and estimating the number of faults in the design and debug phases of software process. Then we present experimental evaluation of proposed method using a data of actual software development project on a certain company. As the result of case study, we confirmed its effectiveness with respect to estimating the number of faults in the software process.

In this paper, we propose a new model for software projects and an estimation method for the quality, cost and delivery date.The new model consists of Project model and Process model.Project model focuses on three key components: activity, product and developer of the project.Process model includes a set of Activity models, each of which specifies design, coding, review, test, and debug activities respectively using GSPN.Moreover, the new model can take the influence of human factors into account by introducing the concept of "workload".Next, we develop a simulator which supports description of the target process, executes the process described by Activity model and analyses the simulation results statistically.Then, we apply the simulator to real software projects at certain organization and compare the estimated values with actual data.The experimental results show the applicability of the proposed simulator to manage real software project in the future.

An automation environment which produces high-quality high-productivity communication service software (CSS) is described. It is a computer-aided interactive specification environment (ISE) for CSS. ISE consists of a CSS specification description system and a prototyping system of a communication node. The specification description system uses a CSS specification description language (newly developed LSDL and CCITT SDL) composed of three steps and a choice of language and graph forms. An intelligent graphic editor supports LSDL graphic input of CSS specification. The prototyping system controls the switching equipment by a general-purpose computer in command form, using a concurrent process environment for control software to switching equipment and a service control process which runs based on one-call-through. The time taken for CSS specification description is reduced to 30% to 70% of the time taken for C language description. By introducing ISE into CSS development, the reduction in total CSS development time is expected to be about 15%.>