Many embedded systems not only affect their context through actuators but also are affected by the context through sensors. It is important to provide a context-dependent development method for constructing safe and reliable embedded systems. However, most of the current requirements analysis methods do not explicitly provide a systematic way for deciding the boundary of the context that should be taken into account because it is essentially difficult to decide which context element should be included as the targets of requirements analysis. If a developer explores the context boundary in an ad-hoc manner, he or she will be faced with the frame problem because there are unlimited context elements in the real world where the target system exists. To deal with this problem, this paper proposes a context-dependent requirements analysis method called CAMEmb (Context Analysis Method for Embedded systems) in which only the value-context elements are extracted as the associated context elements. Applying the guide words provided by CAMEmb, we can explore only a sequence of context elements directly or indirectly affecting the data value observed or controlled by the system sensors and actuators. Other context elements not affecting the system observation and control are not taken into account because these context elements do not affect the system behavior. Using CAMEmb and lightweight formal tools, we can explore the context boundary that guarantees the expected system behavior. We developed CAMEmbModeler, a support tool consisting of a CAMEmb-based modeling editor and a model compiler that transforms system and context models into the design model reflecting the context boundary.

Water temperature is an important environmental factor for lives in small water bodies like lakes and marshes, but is not fully or never monitored except for some of major water bodies. The authors are therefore developing a water temperature database of small water bodies in Japan using ASTER thermal infrared imagery. The current algorithm for water temperature retrieval is an alternative approach to the ASTER standard processing, which includes recalibration, straylight correction, improved atmospheric correction (a water vapor scaling method; WVS). For algorithm validation, we have deployed water-temperature loggers at Lake Senba in Japan since August 2009. In the present study, we demonstrate early validation results using nine cloud-free ASTER scenes (5 daytime and 4 nighttime scenes) over Lake Senba. The results indicate that the WVS algorithm with recalibration and straylight correction worked successfully.

In this paper, we first reveal an important problem called a state inconsistency problem among tasks based on a design model of a CD/DVD systems.This problem is not only of CD/DVD systems but also of typical embedded software because it may occur in a typical structure that such software has. Thus, we propose a method to detect the problem in the design model with a model checking tool and to derive behavior in which it does not occur.

This paper proposes a context-dependent requirements analysis method called CAMEmb (Context Analysis Method for Embedded systems) consisting of UML-based context modeling and formal verification support. In CAMEmb, a context model is constructed from initial system requirements by using a UML Profile for Context Analysis. This context model clarifies the relations among hardware components and contexts. After that, the context model is verified in order to check whether a target system behaves correctly under the expected contexts.

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.

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.

We describe our experience with domain-oriented software development in the domain of automatic teller machine applications. We systematically proceeded with development in four phases: domain analysis, domain formalization, domain facility building, and product development. In this development, we built domain facilities consisting of a domain framework and domain CASE (Computer Aided Software Engineering) tools, then employed them for application development. The framework shared about 4% of the application, and the remaining 96% was generated by the CASE tools automatically. Our approach was found to realize effective reuse of design and implementation and to enable domain-oriented development in large domains.

The paper describes a quality assurance approach for source code to assure source code quality with less effort than conventional method. The paper introduces the data relation tracking method (DRTM) as a practical instance of data oriented program analysis, a key factor of our new quality assurance approach. DRTM helps comprehension of the source code by extracting the internal logic of the source code in declarative notation. An example and evaluation of DRTM for the C language is also described. The example shows that DRTM can deal in data structures and inter-data relations of any control structure. The evaluation shows that DRTM can extract the internal logic of the source code uniquely and that the extracted internal logic is useful for quality assurance of the source code.