Deokyoon Ko

Where Is Current Research on Blockchain Technology?-A Systematic Review.

Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain technology from the technical perspective. We have extracted 41 primary papers from scientific databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.

API Document Quality for Resolving Deprecated APIs

Using deprecated APIs often results in security vulnerability or performance degradation. Thus, invocations to deprecated APIs should be immediately replaced by alternative APIs. To resolve deprecated APIs, most developers rely on API documents provided by service API libraries. However, the documents often do not have sufficient information. This makes many deprecated API usages remain unresolved, which leads programs to vulnerable states. This paper reports a result of studying document quality for deprecated APIs. We first collected 260 deprecated APIs of eight Java libraries as well as the corresponding API documents. These documents were manually investigated to figure out whether it provides alternative APIs, rationales, or examples. Then, we examined 2,126 API usages in 249 client applications and figured out whether those were resolved in the subsequent versions. This study revealed that 1) 3.6 APIs was deprecated and 3.6 deprecated APIs are removed from the library a month on average, 2) only 61% of API documents provided alternative APIs while rationale and examples were rarely documented, and 3) 62% of deprecate API usages in client applications were resolved if the corresponding API documents provided alternative APIs while 49% were resolved when the documents provided no alternative APIs. Based on these results, we draw future directions to encourage resolving deprecated APIs.

Suggesting Alternative Scenarios Using Use Case Specification Patterns for Requirement Completeness

Completeness in software requirements specification is one of the key factors for successful software development. For specifying software requirements, scenario-based approach is broadly used, comprising a basic flow regarding the successful use of the system, and alternative flows describing abnormal or less frequent interactions of the system. However, alternative flows tend to be frequently missed in many cases, because of the relative lower significance rather than the basic flow, which eventually have an influence on achieving the completeness of software requirements. In order to address the issue, we propose an approach for automatically recommending alternative flows from a basic flow by extracting the essential use case patterns based on the occurrence patterns of the agents and measuring the verb similarity between the main verbs of each scenario. In order to validate our approach, we apply it to three industrial case studies, and show comprehensiveness of the suggested alternative flows and synergic effectiveness for inexperienced developers.

An approach to building domain architectures using domain component model and architectural tactics

In constructing software architecture, domain architecture is broadly adopted because it handles common functional requirements (FRs) and non-functional requirements (NFRs) and suggests both fundamental software structure and architectural strategy. In spite of the usefulness of the domain architecture, an approach to building domain architecture is carried out in an ad hoc manner. This paper presents an approach to building domain architecture by using domain requirements and architectural tactics. At first, application requirements are classified into domain FRs and NFRs, application specific FRs and NFRs. Then, domain components are derived from domain FRs, and architectural tactics are selected by using a quantitative approach to handle domain NFRs. Finally, domain architecture is produced after composing domain components and architectural tactic semantics. As all components are specified at UML meta-model level, it contains a feature that automatically instantiates application architectures in our p...

Automatic recommendation to omitted steps in use case specification

Completeness is one of the key attributes for a high-quality software requirements specification. Although incomplete requirements frequently occur in the requirements specification, it is rarely discovered. This turns out to be one of the major causes of software project failure. In order to handle this issue, this paper proposes an automatic approach to recommending omitted steps in a use case-based requirements specification. First, we automatically extract diverse scenario patterns by using the verb clustering algorithm and scenario flow graphs. Based on the scenario patterns, our approach detects omitted steps of user’s scenarios by the pattern matching algorithm and automatically recommends appropriate steps for the omitted parts. For validation of our approach, we have developed tool support, named ScenarioAmigo, and collected 231 use case specifications composing of 1874 scenario steps from 12 academic or proprietary projects. We first carried out the preliminary study to decide appropriate thresholds and weights. Then, we conducted three experiments as a quantitative performance evaluation. First, the cross-validation for the collected scenarios shows the 76% precision and 80% recall. Second, the comparison of recall of ScenarioAmigo to that of human experts obtained the 20% higher score. As the last experiment, we compared the result of ScenarioAmigo and human experts in terms of severity of each scenario and found that our approach could recommend normal as well as important scenarios, compared to the human experts.

Automatic Software Requirement Pattern Extraction Method Using Machine Learning of Requirement Scenario

Software requirement analysis is necessary for successful software development project. Specially, incomplete requirement is the most influential causes of software project failure. Incomplete requirement can bring late delay and over budget because of the misunderstanding and ambiguous criteria for project validation. Software requirement patterns can help writing more complete requirement. These can be a reference model and standards when author writing or validating software requirement. Furthermore, when a novice writes the software scenario, the requirement patterns can be one of the guideline. In this paper proposes an automatic approach to identifying software scenario patterns from various software scenarios. In this paper, we gathered 83 scenarios from eight industrial systems, and show how to extract 54 scenario patterns and how to find omitted action of the scenario using extracted patterns for the feasibility of the approach.