Case Study: Project Management Using Cross Project Software Reliability Growth Model, accepted at IEEE International Workshop on Trustworthy Computing collocated with QRS 2016

Kiyoshi Honda, Nobuhiro Nakamuray, Hironori Washizaki and Yoshiaki Fukazawa, “Case Study: Project Management Using Cross Project Software Reliability Growth Model,” IEEE International Workshop on Trustworthy Computing, collocated with QRS 2016, Vienna, Austria, August 1-3, 2016 (to appear)

We propose a method to compare software products developed by the same company in the same domain. Our method, which measures the time series of the number of detected faults, employs software reliability growth models (SRGMs). SRGMs describe the relations between faults and the time necessary to detect them. Although several researchers have studied cross project defect predictions to determine defect locations using the features of previous software product’s code such as lines of codes and complexities, past works on SRGMs did not compare products or develop comparison methods. Herein we propose a method to compare SRGMs across products. To provide managers and developers insight on advances of its products, our method is applied to the datasets for nine projects developed by Sumitomo Electric Industries, Ltd. SRGMs based on person hours are between 13% and 97% more precise than those based on calendar time.

Case Study: Project Management Using Cross Project Software Reliability Growth Model, accepted at QRS 2016 (CORE Rank B) as Poster

Kiyoshi Honda, Nobuhiro Nakamuray, Hironori Washizaki and Yoshiaki Fukazawa, “Case Study: Project Management Using Cross Project Software Reliability Growth Model,” Poster, The 2016 IEEE International Conference on Software Quality, Reliability & Security (QRS 2016)(CORE Rank B), Vienna, Austria, August 1-3, 2016 (to appear)

We propose a method to compare software products developed by the same company in the same domain. Our method, which measures the time series of the number of detected faults, employs software reliability growth models (SRGMs). SRGMs describe the relations between faults and the time necessary to detect them. Although several researchers have studied cross project defect predictions to determine defect locations using the features of previous software product’s code such as lines of codes and complexities, past works on SRGMs did not compare products or develop comparison methods. Herein we propose a method to compare SRGMs across products. To provide managers and developers insight on advances of its products, our method is applied to the datasets for nine projects developed by Sumitomo Electric Industries, Ltd. SRGMs based on person hours are between 13% and 97% more precise than those based on calendar time.

Initial Framework for a Software Quality Evaluation based on ISO/IEC 25022 and ISO/IEC 25023, accepted at QRS 2016 (CORE Rank B) as Poster

Hidenori Nakai, Naohiko Tsuda, Kiyoshi Honda, Hironori Washizaki, and Yoshiaki Fukazawa, “Initial Framework for a Software Quality Evaluation based on ISO/IEC 25022 and ISO/IEC 25023,” Poster, The 2016 IEEE International Conference on Software Quality, Reliability & Security (QRS 2016)(CORE Rank B), Vienna, Austria, August 1-3, 2016 (to appear)

Although the high quality of software is important for software stakeholders, quality of software products is not effectively defined. Some quality models have been proposed, but they cannot measure and evaluate software product quality comprehensively. Additionally, some companies define their own quality models. However, the quality measured and evaluated based on company-specified quality models cannot be compared to the quality of other software products. To alleviate this problem, ISO/IEC tried to define an international standard for comprehensive quality measurement and evaluation, but this standard includes ambiguous measurements, making it difficult to apply. Herein an initial comprehensive quality measurement framework, which includes a clear measurement plan based on ISO/IEC, is proposed. A case study confirms the usefulness of this framework. However, this framework should be revised to increase its effectiveness.

Prof. Washizaki presented our paper titled GO-MUC: A Strategy Design Method Considering Requirements of User and Business by Goal-Oriented Measurement, at CHASE2016 ICSE Workshop Austin.

Chihiro Uchida, Kiyoshi Honda, Hironori Washizaki, Yoshiaki Fukazawa, Kentaro Ogawa, Tomoaki Yagi, Mikako Ishigaki, Masashi Nakagawa, “GO-MUC: A Strategy Design Method Considering Requirements of User and Business by Goal-Oriented Measurement,” 9th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE 2016), short paper, collocated with ICSE 2016, Autin, Texas, USA, May 16, 2016.

Poster-CHASE2016

A Metamodel for Security and Privacy Knowledge in Cloud Services, accepted at IEEE Services 2016 as Poster Paper.

Hironori Washizaki, Sota Fukumoto, Misato Yamamoto, Masatoshi Yoshizawa, Yoshiaki Fukazawa, Shinpei Ogata, Eduardo B. Fernandez, Nobukazu Yoshioka, Takehisa Kato, Haruhiko Kaiya, Hideyuki Kanuka, Yuki Kondo, Takao Okubo, Atsuo Hazeyama, “A Metamodel for Security and Privacy Knowledge in Cloud Services,” 12th IEEE World Congress on Services (IEEE SERVICES 2016), Poster Paper, June 27 – July 2, 2016, San Francisco, USA. (to appear)

It is important to ensure security and privacy in cloud services. Although there are many security and privacy patterns and much non-pattern-based knowledge such as practices and principles in cloud services, it is difficult to select and combine the right ones due to the large number of those items and the nature of the layered cloud stack. In this paper, we propose a metamodel for handling security and privacy in cloud service development and operation. The metamodel is expected to be utilized for building a knowledge base to accumulate, classify and reuse existing cloud security and privacy patterns and practices in a consistent and uniform way. Moreover the metamodel and knowledge base are expected to be utilized for designing and maintaining architectures for cloud service systems incorporating security and privacy.

Requirements Analysis for Privacy Protection and Third Party Awareness using Logging Models, accepted at SoMeT 2016 (CORE Rank B).

Haruhiko Kaiya, Nobukazu Yoshioka, Takao Okubo, Hironori Washizaki and Atsuo Hazeyama, “Requirements Analysis for Privacy Protection and Third Party Awareness using Logging Models,” 15th International Conference on Intelligent Software Methodologies, Tools and Techniques (SOMET 2016), September 12-14, 2016, Larnaca, Cyprus.

Prof. Washizaki presented our paper titled “Pairwise Coverage-based Testing with Selected Elements in a Query for Database Applications” at IWCT 2016 (ICST Workshop)

Koji Tsumura, Hironori Washizaki, Yoshiaki Fukazawa, Keishi Oshima, Ryota Mibe, “Pairwise Coverage-based Testing with Selected Elements in a Query for Database Applications,” 5th International Workshop on Combinatorial Testing (IWCT 2016), collocated with ICST 2016, Chicago, USA, April 10, 2016.

http://www.slideshare.net/hironoriwashizaki/pairwise-coveragebased-testing-with-selected-elements-in-a-query-for-database-applications

Because program behaviors of database applications depend on the data used, code coverages do not effectively test database applications. Additionally, test coverages for database applications that focus on predicates in Structured Query Language (SQL) queries are not useful if the necessary predicates are omitted. In this paper, we present two new database applications using Plain Pairwise Coverage (PPC) and Selected Pairwise Coverage (SPC) for SQL queries called Plain Pairwise Coverage Testing (PPCT) and Selected Pairwise Coverage Testing (SPCT), respectively. These coverages are based on pairwise testing coverage, which employs selected elements in the SQL SELECT query as parameters. We also implement a coverage calculation tool and conduct case studies on two open source software systems. PPCT and SPCT can detect many bugs, which are not detected by existing test methods based on predicates in the query. Furthermore, the case study suggests that SPCT can detect bugs more efficiently than PPCT and the costs of SPCT can be further reduced by ignoring records filtered out by the conditions of the query.