Pub Date : 2015-09-01DOI: 10.1109/MEMCOD.2015.7340483
P. Clements
Summary form only given. A product line is a family of similar products with variations in features and functions. Product Line Engineering (PLE) is an engineering discipline for product lines using a shared set of engineering assets, a managed set of features, and an efficient means of production. It takes advantage of the commonality shared across the family while efficiently and systematically managing the variation among the products. PLE can trace its roots in software back to the 1970s; its roots in manufacturing go back centuries. But only the relatively recent (2000s or so) advent of industrial-strength automation and methodology has enabled Systems and Software PLE to emerge as a reliably repeatable engineering paradigm. It is worth studying because of the phenomenal improvements in product time to market, engineering productivity, portfolio scalability, and system quality that PLE has shown, over and over, to bring to organizations that apply it. This talk explains the fundamentals of modern PLE, shares some brief case studies, and discusses how the underpinnings of formal methods and notations are enabling PLE to achieve its remarkable results.
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Pub Date : 2015-09-01DOI: 10.1109/MEMCOD.2015.7340467
Peter Milder
The skyline query operation (also called the “maximum vector problem”) is used to identify potentially interesting or useful data points in large sets of multi-dimensional data. When the data change over time (through addition and subtraction of points), this is called the “continuous skyline” query. The 2015 MEMOCODE Design Contest problem is to implement a system to efficiently compute the continuous skyline of dynamic data. Contestants were given one month to develop a system to perform the skyline query, aiming to maximize performance or cost-adjusted performance. Teams were encouraged to consider a variety of computational targets including CPUs, FPGAs, and GPGPUs. The two winning teams, which have been invited to contribute papers describing their techniques, combined careful algorithmic and implementation optimizations; both implemented the system on multicore CPUs.
{"title":"MEMOCODE 2015 design contest: Continuous skyline computation","authors":"Peter Milder","doi":"10.1109/MEMCOD.2015.7340467","DOIUrl":"https://doi.org/10.1109/MEMCOD.2015.7340467","url":null,"abstract":"The skyline query operation (also called the “maximum vector problem”) is used to identify potentially interesting or useful data points in large sets of multi-dimensional data. When the data change over time (through addition and subtraction of points), this is called the “continuous skyline” query. The 2015 MEMOCODE Design Contest problem is to implement a system to efficiently compute the continuous skyline of dynamic data. Contestants were given one month to develop a system to perform the skyline query, aiming to maximize performance or cost-adjusted performance. Teams were encouraged to consider a variety of computational targets including CPUs, FPGAs, and GPGPUs. The two winning teams, which have been invited to contribute papers describing their techniques, combined careful algorithmic and implementation optimizations; both implemented the system on multicore CPUs.","PeriodicalId":106851,"journal":{"name":"2015 ACM/IEEE International Conference on Formal Methods and Models for Codesign (MEMOCODE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133232622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the subtractive model repair problem: given a finite Kripke structure M and a CTL formula η, determine if M contains a substructure M' that satisfies η. Thus, M can be repaired to satisfy η by deleting states and/or transitions. We give a reduction to boolean satisfiability, and implement the repair method using this reduction. We also extend the basic repair method in three directions: (1) the use of abstraction, and (2) the repair of concurrent Kripke structures and concurrent programs, and (3) the repair of hierarchical Kripke structures. These last two extensions both avoid state-explosion.
{"title":"Model and program repair via SAT solving","authors":"P. Attie, K. Bab, Mouhammad Sakr","doi":"10.1145/3147426","DOIUrl":"https://doi.org/10.1145/3147426","url":null,"abstract":"We consider the subtractive model repair problem: given a finite Kripke structure M and a CTL formula η, determine if M contains a substructure M' that satisfies η. Thus, M can be repaired to satisfy η by deleting states and/or transitions. We give a reduction to boolean satisfiability, and implement the repair method using this reduction. We also extend the basic repair method in three directions: (1) the use of abstraction, and (2) the repair of concurrent Kripke structures and concurrent programs, and (3) the repair of hierarchical Kripke structures. These last two extensions both avoid state-explosion.","PeriodicalId":106851,"journal":{"name":"2015 ACM/IEEE International Conference on Formal Methods and Models for Codesign (MEMOCODE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134641216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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